Course Schedules

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Fall 2018 Courses

Course - Section Title Days Time Location
SEIS 601 - 01 Found. of Software Dev-Java - T - - - - - 1745 - 2100 OSS 325

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 325

Course Registration Number:

40106 (View in ClassFinder)

Credit Hours:

3

Instructor:

Chi-Lung Chiang

The primary objective of this course is to provide the experienced programmer with knowledge of and experience with fundamental data structures and algorithms used in software design and development. The secondary objective is to give a fast-paced introduction to the Java programming language. Students will write multiple programs in Java, both to become familiar with Java and to apply data structure concepts. Prerequisite: none

Schedule Details

Location Time Day(s)
SEIS 602 - 01 Intermediate Software Dev - - - - F - - 1745 - 2100 OSS 333

Days of Week:

- - - - F - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

41538 (View in ClassFinder)

Credit Hours:

3

Instructor:

Syed H. Naqvi

This is an introductory software development course, with focus on intermediate-level fundamental and foundational concepts. These concepts include abstract data types such as lists, stacks, queues, and trees/graphs, as well as some of their associated algorithms such as insertion, deletion, searching, sorting, and traversals. Canonical implementations as well as framework supplied implementation alternatives (such as the JDK or other framework alternatives) will be explored and used. To apply the lecture concepts, we will implement software using the Java programming language and explore some of the tools used by software developers. There are many types of tools to be considered, such as integrated development environments (IDEs e.g. eclipse), tools for managing software build, configuration, and version control (e.g. Ant/Maven, Git), tools for testing and debugging (e.g. JUnit, LogBack/Log4J/SLF4J) and other tools used by developers to understand the code they are working with (e.g. GrepCode). In addition, we will discuss intermediate concepts, issues, and techniques including an introduction to concurrency issues, and development practices such as refactoring, logging, and debugging. Prerequisite: SEIS 601 or an equivalent understanding of Foundational Software Development concepts and the ability to use and understand the Java programming language is required.

Schedule Details

Location Time Day(s)
SEIS 603 - 01 Found. Software Dev-Python M - - - - - - 1745 - 2100 OSS 326

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 326

Course Registration Number:

42472 (View in ClassFinder)

Credit Hours:

3

Instructor:

Damodar Chetty

This is an introductory software development course, with focus on fundamental and foundational concepts. These concepts include general problem solving and algorithm creation techniques, data types, constants, variables and expressions, Boolean, control flow, and object-oriented concepts. Applying these concepts, we implement programs using the Python language. We will examine its use as both an interpreted and a compiled language, working with data types such as numbers, strings, lists, dictionaries, and sets. Students will learn how to apply Python in managing data. No previous programming experience in Python or any other programming language is required.

Schedule Details

Location Time Day(s)
SEIS 603 - 02 Found. Software Dev-Python - T - - - - - 1745 - 2100 TMH 254

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

TMH 254

Course Registration Number:

42473 (View in ClassFinder)

Credit Hours:

3

Instructor:

Eric V. Level

This is an introductory software development course, with focus on fundamental and foundational concepts. These concepts include general problem solving and algorithm creation techniques, data types, constants, variables and expressions, Boolean, control flow, and object-oriented concepts. Applying these concepts, we implement programs using the Python language. We will examine its use as both an interpreted and a compiled language, working with data types such as numbers, strings, lists, dictionaries, and sets. Students will learn how to apply Python in managing data. No previous programming experience in Python or any other programming language is required.

Schedule Details

Location Time Day(s)
SEIS 603 - 03 Found. Software Dev-Python - - W - - - - 1745 - 2100 OSS 325

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 325

Course Registration Number:

42474 (View in ClassFinder)

Credit Hours:

3

Instructor:

Eric V. Level

This is an introductory software development course, with focus on fundamental and foundational concepts. These concepts include general problem solving and algorithm creation techniques, data types, constants, variables and expressions, Boolean, control flow, and object-oriented concepts. Applying these concepts, we implement programs using the Python language. We will examine its use as both an interpreted and a compiled language, working with data types such as numbers, strings, lists, dictionaries, and sets. Students will learn how to apply Python in managing data. No previous programming experience in Python or any other programming language is required.

Schedule Details

Location Time Day(s)
SEIS 603 - 04 Found. Software Dev-Python - - - - F - - 1745 - 2100 OSS 326

Days of Week:

- - - - F - -

Time of Day:

1745 - 2100

Location:

OSS 326

Course Registration Number:

42475 (View in ClassFinder)

Credit Hours:

3

Instructor:

Damodar Chetty

This is an introductory software development course, with focus on fundamental and foundational concepts. These concepts include general problem solving and algorithm creation techniques, data types, constants, variables and expressions, Boolean, control flow, and object-oriented concepts. Applying these concepts, we implement programs using the Python language. We will examine its use as both an interpreted and a compiled language, working with data types such as numbers, strings, lists, dictionaries, and sets. Students will learn how to apply Python in managing data. No previous programming experience in Python or any other programming language is required.

Schedule Details

Location Time Day(s)
SEIS 605 - 01 Technical Communications - T - - - - - 1745 - 2100 OSS 127

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 127

Course Registration Number:

40104 (View in ClassFinder)

Credit Hours:

3

Instructor:

Kirk T. Livingston

Teaches the fundamentals of written and oral communication as practiced by IT professionals. The course emphasizes product descriptions, instructions, informative and persuasive oral presentations, the role of graphics, and teamwork on projects. In addition, the course introduces managerial strategies and tactics, such as planning and evaluation, which are critical for meeting an intended audience's needs. Recently, the scope of this course was expanded to include communication issues related to business analysis and project management. After completing this course, students will be more confident about their ability to communicate effectively in the workplace. For MS Software students, this course must be completed before exceeding 12 credits in Software Engineering, Software Management, and Information Technology.

Schedule Details

Location Time Day(s)
SEIS 605 - 02 Technical Communications - - - R - - - 1745 - 2100 MCH 115

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

MCH 115

Course Registration Number:

40418 (View in ClassFinder)

Credit Hours:

3

Instructor:

Dorian G. Harvey

Teaches the fundamentals of written and oral communication as practiced by IT professionals. The course emphasizes product descriptions, instructions, informative and persuasive oral presentations, the role of graphics, and teamwork on projects. In addition, the course introduces managerial strategies and tactics, such as planning and evaluation, which are critical for meeting an intended audience's needs. Recently, the scope of this course was expanded to include communication issues related to business analysis and project management. After completing this course, students will be more confident about their ability to communicate effectively in the workplace. For MS Software students, this course must be completed before exceeding 12 credits in Software Engineering, Software Management, and Information Technology.

Schedule Details

Location Time Day(s)
SEIS 610 - 01 Software Engineering M - - - - - - 1745 - 2100 SCH 127

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

SCH 127

Course Registration Number:

40105 (View in ClassFinder)

Credit Hours:

3

Instructor:

Michael A. Dorin

This is a survey course covering software engineering concepts, techniques, and methodologies. Topics covered include software engineering; software process and its difficulties; software life-cycle models; software metrics; project planning including cost estimation; design methodologies including structured design, and object-oriented design; software testing; and software maintenance. A brief review of data structures is included. Prerequisite: SEIS 601 or SEIS 603. SEIS 610 can be taken concurrently with SEIS 601 or SEIS 603.

Schedule Details

Location Time Day(s)
SEIS 610 - 02 Software Engineering - - - R - - - 1745 - 2100 OSS LL18

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS LL18

Course Registration Number:

40493 (View in ClassFinder)

Credit Hours:

3

Instructor:

Bradford C. Armitage

This is a survey course covering software engineering concepts, techniques, and methodologies. Topics covered include software engineering; software process and its difficulties; software life-cycle models; software metrics; project planning including cost estimation; design methodologies including structured design, and object-oriented design; software testing; and software maintenance. A brief review of data structures is included. Prerequisite: SEIS 601 or SEIS 603. SEIS 610 can be taken concurrently with SEIS 601 or SEIS 603.

Schedule Details

Location Time Day(s)
SEIS 610 - 04 Software Engineering See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

42476 (View in ClassFinder)

Credit Hours:

3

Instructor:

Michael A. Dorin

This is a survey course covering software engineering concepts, techniques, and methodologies. Topics covered include software engineering; software process and its difficulties; software life-cycle models; software metrics; project planning including cost estimation; design methodologies including structured design, and object-oriented design; software testing; and software maintenance. A brief review of data structures is included. Prerequisite: SEIS 601 or SEIS 603. SEIS 610 can be taken concurrently with SEIS 601 or SEIS 603.

Schedule Details

Location Time Day(s)
OSS 3130900-160008 Sep '18
OSS 3130900-160022 Sep '18
OSS 3130900-160006 Oct '18
OSS 3130900-160020 Oct '18
OSS 3130900-160003 Nov '18
OSS 3130900-160017 Nov '18
OSS 3130900-160008 Dec '18
SEIS 625 - 02 Software Project Management See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

41763 (View in ClassFinder)

Credit Hours:

3

Instructor:

Syed H. Naqvi

Students gain a management perspective and a development process for planning, estimating, and controlling software development. They learn to develop a well-defined plan before beginning any software development effort; how to handle changes during the execution of the plan; how to incorporate quality criteria in the development cycle; and how to use methods to keep the project on track. Included in the course is the use of project management software and simulation software in the development and control of the project plan.(If credit is received for this course students cannot receive credit for SEIS621 [CSIS526].) Prerequisite: SEIS610

Schedule Details

Location Time Day(s)
OSS 3290900-160008 Sep '18
OSS 3290900-160022 Sep '18
OSS 3290900-160006 Oct '18
OSS 3290900-160020 Oct '18
OSS 3290900-160003 Nov '18
OSS 3290900-160017 Nov '18
OSS 3290900-160008 Dec '18
SEIS 626 - 01 Sftw Quality Assurance/Control - - W - - - - 1745 - 2100 OSS 313

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 313

Course Registration Number:

40112 (View in ClassFinder)

Credit Hours:

3

Instructor:

Frank S. Haug

This course builds on the project management process through the application of Software Quality Engineering concepts (Quality Assurance, Control and Testing). Students will work through a semester project in which they will think like a Software Quality Engineer. Practical tools and techniques will be applied toward the management and improvement of the quality of a software product and the development process. (If credit is received for this course, students cannot receive credit for SEIS 621 [CSIS526].) Prerequisite: SEIS625. SEIS 626 can be taken concurrently with SEIS 625.

Schedule Details

Location Time Day(s)
SEIS 627 - 01 Software Planning & Testing - - - R - - - 1745 - 2100 OSS 333

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

43117 (View in ClassFinder)

Credit Hours:

Instructor:

Aric B. Aune

This course presents a software planning and quality perspective that guides the selection of tools and application of techniques needed for the successful completion of software development projects. A successful software project must manage many different, yet integrated activities. These activities include software development lifecycle tasks such as requirements gathering, software design, and code implementation. Many other activities also need to be planned and managed, such as project scope, schedule, and cost. In any successful software project, when issues arise (e.g. the requirements change, a defect in the software is discovered, scheduled activities do not go as planned, etc.) they need to be prioritized and appropriately addressed. To minimize the impact of software quality issues, software testing and quality improvement activities need to be planned, executed and coordinated. The purpose of this course is to learn the foundational concepts and practices needed to produce software that is completed on time, within budget, and with the necessary scope and quality required. While software development activities are covered in other courses, this course will focus more on the software planning and testing activities. Project management topics covered include: integration management, scope management, time management, cost management, and quality management from a software planning perspective. Software testing and quality topics covered include: testing terms and concepts, lower-level testing (e.g. unit and integration testing), higher-level testing (e.g. system and acceptance testing), and test automation. Agile Project and Product Management using Scrum will be introduced as an approach for directing these activities and laying the foundation for continuous process improvement and quality assurance. Prerequisite: SEIS 610 AND SEIS 601/603

Schedule Details

Location Time Day(s)
SEIS 630 - 01 Database Mgmt Systems & Design M - - - - - - 1745 - 2100 OSS 333

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

40107 (View in ClassFinder)

Credit Hours:

3

Instructor:

Jeffrey R. Skochil

This course focuses on database management system concepts , database design, and implementation. Conceptual data modeling using Entity Relationships (ER) is used to capture the requirements of a database design. Relational model concepts are introduced and mapping from ER to relational model is discussed. Logical database design (Normalization) and indexing strategies are also discussed to aide system performance. Relational Algebra and Structured Query Language (SQL) are used to work with a database. From a system perspective, the course focuses on query optimization and execution strategies, concurrency control, locking, deadlocks and database back up and recovery concepts. Database security and authorization are also discussed. Students will use Oracle and/or SQL Server to design a database and complete an application using SQL as their project. Prerequisite: SEIS 610. SEIS 630 may be taken concurrently with SEIS610.

Schedule Details

Location Time Day(s)
SEIS 630 - 02 Database Mgmt Systems & Design - - W - - - - 1745 - 2100 OSS 431

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 431

Course Registration Number:

40108 (View in ClassFinder)

Credit Hours:

3

Instructor:

Jordan B. Barlow

This course focuses on database management system concepts , database design, and implementation. Conceptual data modeling using Entity Relationships (ER) is used to capture the requirements of a database design. Relational model concepts are introduced and mapping from ER to relational model is discussed. Logical database design (Normalization) and indexing strategies are also discussed to aide system performance. Relational Algebra and Structured Query Language (SQL) are used to work with a database. From a system perspective, the course focuses on query optimization and execution strategies, concurrency control, locking, deadlocks and database back up and recovery concepts. Database security and authorization are also discussed. Students will use Oracle and/or SQL Server to design a database and complete an application using SQL as their project. Prerequisite: SEIS 610. SEIS 630 may be taken concurrently with SEIS610.

Schedule Details

Location Time Day(s)
SEIS 630 - 03 Database Mgmt Systems & Design - - - - F - - 1745 - 2100 OSS 325

Days of Week:

- - - - F - -

Time of Day:

1745 - 2100

Location:

OSS 325

Course Registration Number:

42477 (View in ClassFinder)

Credit Hours:

3

Instructor:

Jordan B. Barlow

This course focuses on database management system concepts , database design, and implementation. Conceptual data modeling using Entity Relationships (ER) is used to capture the requirements of a database design. Relational model concepts are introduced and mapping from ER to relational model is discussed. Logical database design (Normalization) and indexing strategies are also discussed to aide system performance. Relational Algebra and Structured Query Language (SQL) are used to work with a database. From a system perspective, the course focuses on query optimization and execution strategies, concurrency control, locking, deadlocks and database back up and recovery concepts. Database security and authorization are also discussed. Students will use Oracle and/or SQL Server to design a database and complete an application using SQL as their project. Prerequisite: SEIS 610. SEIS 630 may be taken concurrently with SEIS610.

Schedule Details

Location Time Day(s)
SEIS 630 - 04 Database Mgmt Systems & Design See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

41421 (View in ClassFinder)

Credit Hours:

3

Instructor:

Saeed K. Rahimi

This course focuses on database management system concepts , database design, and implementation. Conceptual data modeling using Entity Relationships (ER) is used to capture the requirements of a database design. Relational model concepts are introduced and mapping from ER to relational model is discussed. Logical database design (Normalization) and indexing strategies are also discussed to aide system performance. Relational Algebra and Structured Query Language (SQL) are used to work with a database. From a system perspective, the course focuses on query optimization and execution strategies, concurrency control, locking, deadlocks and database back up and recovery concepts. Database security and authorization are also discussed. Students will use Oracle and/or SQL Server to design a database and complete an application using SQL as their project. Prerequisite: SEIS 610. SEIS 630 may be taken concurrently with SEIS610.

Schedule Details

Location Time Day(s)
OSS 3330900-160015 Sep '18
OSS 3330900-160029 Sep '18
OSS 3330900-160013 Oct '18
OSS 3330900-160027 Oct '18
OSS 3330900-160010 Nov '18
OSS 3330900-160001 Dec '18
OSS 3330900-160015 Dec '18
SEIS 631 - 01 Foundations of Data Analysis - T - - - - - 1745 - 2100 TMH 253

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

TMH 253

Course Registration Number:

41628 (View in ClassFinder)

Credit Hours:

3

Instructor:

Kristine Kubisiak

This course provides a broad introduction to the subject of data analysis by introducing common techniques that are essential for analyzing and deriving meaningful information from datasets. In particular, the course will focus on relevant methods for performing data collection, representation, transformation, and data-driven decision making. Students will also develop proficiency in the widely used R language which will be used throughout the course to reinforce the topics covered. Prerequisite: SEIS 601 or SEIS 603 (may be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 631 - 02 Foundations of Data Analysis - - - R - - - 1745 - 2100 TMH 253

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

TMH 253

Course Registration Number:

41759 (View in ClassFinder)

Credit Hours:

3

Instructor:

Anne A. Eaton

This course provides a broad introduction to the subject of data analysis by introducing common techniques that are essential for analyzing and deriving meaningful information from datasets. In particular, the course will focus on relevant methods for performing data collection, representation, transformation, and data-driven decision making. Students will also develop proficiency in the widely used R language which will be used throughout the course to reinforce the topics covered. Prerequisite: SEIS 601 or SEIS 603 (may be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 631 - 03 Foundations of Data Analysis - - W - - - - 1745 - 2100 OSS 428

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 428

Course Registration Number:

42478 (View in ClassFinder)

Credit Hours:

3

Instructor:

Aran W. Glancy

This course provides a broad introduction to the subject of data analysis by introducing common techniques that are essential for analyzing and deriving meaningful information from datasets. In particular, the course will focus on relevant methods for performing data collection, representation, transformation, and data-driven decision making. Students will also develop proficiency in the widely used R language which will be used throughout the course to reinforce the topics covered. Prerequisite: SEIS 601 or SEIS 603 (may be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 632 - 01 Data Analytics & Visualization M - - - - - - 1745 - 2100 OSS 325

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 325

Course Registration Number:

41536 (View in ClassFinder)

Credit Hours:

3

Instructor:

Ebrahim F. Kazemzadeh

The course provides an introduction to concepts and techniques used in field of data analytics and visualization. Data analytics is defined to be the science of examining raw data with the purpose of discovering knowledge by analyzing current and historical facts. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery, and best practices for creating effective data visualizations. Through practical application of the above topics, students will also develop proficiency in using analytics tools.

Schedule Details

Location Time Day(s)
SEIS 632 - 02 Data Analytics & Visualization - - W - - - - 1745 - 2100 TMH 253

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

TMH 253

Course Registration Number:

41610 (View in ClassFinder)

Credit Hours:

3

Instructor:

Manjeet Rege

The course provides an introduction to concepts and techniques used in field of data analytics and visualization. Data analytics is defined to be the science of examining raw data with the purpose of discovering knowledge by analyzing current and historical facts. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery, and best practices for creating effective data visualizations. Through practical application of the above topics, students will also develop proficiency in using analytics tools.

Schedule Details

Location Time Day(s)
SEIS 632 - 03 Data Analytics & Visualization See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

41764 (View in ClassFinder)

Credit Hours:

3

Instructor:

Manjeet Rege

The course provides an introduction to concepts and techniques used in field of data analytics and visualization. Data analytics is defined to be the science of examining raw data with the purpose of discovering knowledge by analyzing current and historical facts. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery, and best practices for creating effective data visualizations. Through practical application of the above topics, students will also develop proficiency in using analytics tools.

Schedule Details

Location Time Day(s)
OSS 3260900-160008 Sep '18
OSS 3260900-160022 Sep '18
OSS 3260900-160006 Oct '18
OSS 3260900-160020 Oct '18
OSS 3260900-160003 Nov '18
OSS 3260900-160017 Nov '18
OSS 3260900-160008 Dec '18
SEIS 632 - 04 Data Analytics & Visualization See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

41855 (View in ClassFinder)

Credit Hours:

3

Instructor:

Ebrahim F. Kazemzadeh

The course provides an introduction to concepts and techniques used in field of data analytics and visualization. Data analytics is defined to be the science of examining raw data with the purpose of discovering knowledge by analyzing current and historical facts. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery, and best practices for creating effective data visualizations. Through practical application of the above topics, students will also develop proficiency in using analytics tools.

Schedule Details

Location Time Day(s)
OSS 3260900-160015 Sep '18
OSS 3260900-160029 Sep '18
OSS 3260900-160013 Oct '18
OSS 3260900-160027 Oct '18
OSS 3260900-160010 Nov '18
OSS 3260900-160001 Dec '18
OSS 3260900-160015 Dec '18
SEIS 632 - 05 Data Analytics & Visualization M - - - - - - 1745 - 2100 OSS 428

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 428

Course Registration Number:

43512 (View in ClassFinder)

Credit Hours:

Instructor:

Manjeet Rege

The course provides an introduction to concepts and techniques used in field of data analytics and visualization. Data analytics is defined to be the science of examining raw data with the purpose of discovering knowledge by analyzing current and historical facts. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery, and best practices for creating effective data visualizations. Through practical application of the above topics, students will also develop proficiency in using analytics tools.

Schedule Details

Location Time Day(s)
SEIS 635 - 01 Software Analysis and Design - - - - F - - 1745 - 2100 BIN LL02

Days of Week:

- - - - F - -

Time of Day:

1745 - 2100

Location:

BIN LL02

Course Registration Number:

40109 (View in ClassFinder)

Credit Hours:

3

Instructor:

Eric V. Level

This course covers basic object-oriented techniques for specifying, designing, and implementing software systems. Iterative development methodologies are emphasized. The Unified Modeling Language (UML) is used as a notational system for capturing the development process artifacts. Students will gain experience with a software tool for creating UML diagrams. Other topics include use cases, class discovery and domain modeling, responsibility-driven design, basic design patterns, software class design, converting designs to code, object-oriented testing, packaging, deployment, along with intermediate Java topics relevant to system implementation. This course also introduces ideas in functional and parallel programming. Students will work on an object-oriented team project, apply concepts and techniques to describe and create a working software system. Prerequisite: SEIS 602 and SEIS 610.

Schedule Details

Location Time Day(s)
SEIS 636 - 01 Requirements Analysis See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

41308 (View in ClassFinder)

Credit Hours:

3

Instructor:

Jan M. Gardner

The objective of this course is to introduce the business analyst roles and responsibilities and knowledge areas such as enterprise analysis, requirements planning and measurement, requirements elicitation, requirements communication, requirements analysis and documentation, solution assessment and validation, business analysis fundamentals including tools and techniques. Prerequisite: SEIS 610. SEIS 636 may be taken concurrently with SEIS 610.

Schedule Details

Location Time Day(s)
OSS 3290900-160015 Sep '18
OSS 3290900-160029 Sep '18
OSS 3290900-160013 Oct '18
OSS 3290900-160027 Oct '18
OSS 3290900-160010 Nov '18
OSS 3290900-160001 Dec '18
OSS 3290900-160015 Dec '18
SEIS 640 - 01 Operating Systems Design See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

40113 (View in ClassFinder)

Credit Hours:

3

Instructor:

Michael A. Dorin

An introduction to the concepts and principles involved in operating systems design is provided. Topics in the course include computer-system structures, operating-systems structures, job and process scheduling, process synchronization, deadlock, memory management, virtual memory, file systems, input/output systems, distributed system structures, distributed file systems, protection, system security, and case studies of operating systems. Prerequisite: SEIS610

Schedule Details

Location Time Day(s)
OWS 2501745-210005 Sep '18
OWS 2501745-210019 Sep '18
OWS 2501745-210003 Oct '18
OWS 2501745-210017 Oct '18
OWS 2501745-210031 Oct '18
OWS 2501745-210014 Nov '18
OWS 2501745-210028 Nov '18
SEIS 650 - 01 Legal Issues in Technology - - W - - - - 1745 - 2100 OSS 227

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 227

Course Registration Number:

41534 (View in ClassFinder)

Credit Hours:

3

Instructor:

Thomas R. Sheran

The ability to identify legal issues being raised by computer technology and guidelines for their solution is a continuing requirement for competence in the field of software design and development. Consequently, the students are provided with an examination of a broad range of legal issues in technology including patent law, copyright law, trade secrets, trademarks, contracts, ownership issues in software development, and computer failures and related torts.

Schedule Details

Location Time Day(s)
SEIS 662 - 01 Enterprise Resource Planning M - - - - - - 1745 - 2100 JRC 301

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

JRC 301

Course Registration Number:

41301 (View in ClassFinder)

Credit Hours:

3

Instructor:

William H. Gamble

This course will provide a practical overview of Enterprise Resource Planning, connecting the academic and even marketing elements with real-world, case-based issues as encountered by business and other organizations. ERP has become a critical strategic consideration for many companies, and the course will look at best-practice implementations at leading companies internationally. Course will examine best practice usage of ERP in a global distributed computing environment. In addition, it will look into trends relating to critical issues such as Cloud and Big Data. Professionals currently working in the IT organizations or future IT professionals will benefit from this course. Prerequisite: Minimum grade of C- in SEIS 610

Schedule Details

Location Time Day(s)
SEIS 663 - 01 IT Security and Networking - T - - - - - 1745 - 2100 OSS 313

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 313

Course Registration Number:

41535 (View in ClassFinder)

Credit Hours:

3

Instructor:

Melinda J. Mattox

This course will provide the foundation of information technology security, including authentication, authorization, access management, physical security, network security (firewalls, intrusion detection), application security (software and database), security regulations, and disaster recovery. We will explore social engineering and other human factors and the impact to security. There will be an emphasis on local area networking (LAN) and Internet architecture and protocols, including TCP/IP and the OSI layers. We study protocol details, the way they relate and interact with each other, and how they are applied in real systems. Prerequisite: SEIS610

Schedule Details

Location Time Day(s)
SEIS 663 - 02 IT Security and Networking - - - R - - - 1745 - 2100 BIN LL02

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

BIN LL02

Course Registration Number:

41760 (View in ClassFinder)

Credit Hours:

3

Instructor:

Theodore M. Wallerstedt

This course will provide the foundation of information technology security, including authentication, authorization, access management, physical security, network security (firewalls, intrusion detection), application security (software and database), security regulations, and disaster recovery. We will explore social engineering and other human factors and the impact to security. There will be an emphasis on local area networking (LAN) and Internet architecture and protocols, including TCP/IP and the OSI layers. We study protocol details, the way they relate and interact with each other, and how they are applied in real systems. Prerequisite: SEIS610

Schedule Details

Location Time Day(s)
SEIS 664 - 01 Information Tech. Delivery - - - - F - - 1745 - 2100 OSS 328

Days of Week:

- - - - F - -

Time of Day:

1745 - 2100

Location:

OSS 328

Course Registration Number:

41850 (View in ClassFinder)

Credit Hours:

3

Instructor:

Charles T. Betz

This survey course covers IT delivery, operations, and management in both theory and practice, including Business and consumer needs for IT value, IT infrastructure, cloud, continuous integration/delivery, IT product and service management, work and task management, operations management, organization and culture, project management, process management, change and incident management, IT governance, risk, security, and compliance business continuity, enterprise information and e-records management, enterprise IT architecture and portfolio management, IT management frameworks including ITIL, COBIT, and IT4IT, Agile and Lean influences including Kanban, Scrum, and DevOps, Continuous improvement and IT. Prerequisite: SEIS 610

Schedule Details

Location Time Day(s)
SEIS 665 - 01 Dev Ops & Cloud Infrastructure M - - - - - - 1745 - 2100 OSS 431

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 431

Course Registration Number:

41852 (View in ClassFinder)

Credit Hours:

3

Instructor:

Jason D. Baker

This course covers the engineering and design of IT infrastructure, focusing on cloud-scale distributed systems and modern DevOps practices. IT infrastructure deployment practices are rapidly changing as organizations build "Infrastructure as code" and adopt cloud computing platforms. We will examine the theory behind these modern practices and the real-world implementation challenges faced by IT organizations. While the lessons will cover a number of theoretical concepts, we will primarily learn by doing. Students will gain hands-on experience with several widely-adopted IT platforms including Github, AWS, and Docker. Prerequisite: SEIS 610

Schedule Details

Location Time Day(s)
SEIS 665 - 02 Dev Ops & Cloud Infrastructure - - W - - - - 1745 - 2100 OSS 326

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 326

Course Registration Number:

42479 (View in ClassFinder)

Credit Hours:

3

Instructor:

Chi-Lung Chiang

This course covers the engineering and design of IT infrastructure, focusing on cloud-scale distributed systems and modern DevOps practices. IT infrastructure deployment practices are rapidly changing as organizations build "Infrastructure as code" and adopt cloud computing platforms. We will examine the theory behind these modern practices and the real-world implementation challenges faced by IT organizations. While the lessons will cover a number of theoretical concepts, we will primarily learn by doing. Students will gain hands-on experience with several widely-adopted IT platforms including Github, AWS, and Docker. Prerequisite: SEIS 610

Schedule Details

Location Time Day(s)
SEIS 665 - 03 Dev Ops & Cloud Infrastructure - - - - F - - 1745 - 2100 OSS 431

Days of Week:

- - - - F - -

Time of Day:

1745 - 2100

Location:

OSS 431

Course Registration Number:

42480 (View in ClassFinder)

Credit Hours:

3

Instructor:

Chi-Lung Chiang

This course covers the engineering and design of IT infrastructure, focusing on cloud-scale distributed systems and modern DevOps practices. IT infrastructure deployment practices are rapidly changing as organizations build "Infrastructure as code" and adopt cloud computing platforms. We will examine the theory behind these modern practices and the real-world implementation challenges faced by IT organizations. While the lessons will cover a number of theoretical concepts, we will primarily learn by doing. Students will gain hands-on experience with several widely-adopted IT platforms including Github, AWS, and Docker. Prerequisite: SEIS 610

Schedule Details

Location Time Day(s)
SEIS 720 - 01 Computer Security - T - - - - - 1745 - 2100 OSS 329

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 329

Course Registration Number:

40362 (View in ClassFinder)

Credit Hours:

3

Instructor:

Bradley S. Rubin

This course covers both the engineering and human issues in computer security and the tension between them. The engineering issues include cryptography concepts, building blocks (conventional and public key, digital signatures, certificates, certificate authorities), algorithms, protocols (authentication, key distribution, SSL), biometrics, network security (firewalls, intrusion detection systems, wireless), email protection, malware (viruses, worms, trojans), and applications. This course emphasizes on the application security features of the Java programming platform. The human issues include social engineering, user password management, and computer crime. We also cover weekly current events in computer security. Prerequisites: SEIS 601 and SEIS 610.

Schedule Details

Location Time Day(s)
SEIS 722 - 01 Computer Forensics M - - - - - - 1745 - 2100 OSS 318

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 318

Course Registration Number:

41173 (View in ClassFinder)

Credit Hours:

3

Instructor:

Donald Y. Cheung

This course explores the issues surrounding computers that have been used in connection with criminal or other improper activity, or that have been the direct target of a crime. While the focus of this course is on the computer science issues, the law enforcement perspective is also covered. Topics include disk file system structures (hiding and recovery techniques), networking and email considerations, forensic data collection, evidence preservation and authentication, collection and analysis tools, legal, and privacy issues.

Schedule Details

Location Time Day(s)
SEIS 732 - 01 Data Warehousing & Bus Intel - T - - - - - 1745 - 2100 OSS 333

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

40494 (View in ClassFinder)

Credit Hours:

3

Instructor:

Frank S. Haug

In order to build and maintain a successful data warehouse, it is important to understand all of its components and how they fit together. This course will cover data warehouse and data mart lifecycle phases while focusing on infrastructure, design, and management issues. The course project will provide an opportunity to for hands-on experience with some of the available tools and technologies. Topics include: differences between data warehouses and traditional database systems (OLTP), multidimensional analysis and design, building data warehouses using "cube" vs. RDBMS (Star schema, etc.), planning for data warehouses, extraction transformation and loading (ETL), online analytical processing (OLAP), data mining, quality and cleansing, common pitfalls to avoid when designing, implementing and maintaining data warehouse environments, and the impact of new technologies (data webhouse, clickstream, XML). Prerequisite: SEIS630

Schedule Details

Location Time Day(s)
SEIS 732 - 02 Data Warehousing & Bus Intel - - - R - - - 1745 - 2100 OSS 328

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 328

Course Registration Number:

41858 (View in ClassFinder)

Credit Hours:

3

Instructor:

Frank S. Haug

In order to build and maintain a successful data warehouse, it is important to understand all of its components and how they fit together. This course will cover data warehouse and data mart lifecycle phases while focusing on infrastructure, design, and management issues. The course project will provide an opportunity to for hands-on experience with some of the available tools and technologies. Topics include: differences between data warehouses and traditional database systems (OLTP), multidimensional analysis and design, building data warehouses using "cube" vs. RDBMS (Star schema, etc.), planning for data warehouses, extraction transformation and loading (ETL), online analytical processing (OLAP), data mining, quality and cleansing, common pitfalls to avoid when designing, implementing and maintaining data warehouse environments, and the impact of new technologies (data webhouse, clickstream, XML). Prerequisite: SEIS630

Schedule Details

Location Time Day(s)
SEIS 735 - 01 Healthcare Analytics - - - R - - - 1745 - 2100 OSS 313

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 313

Course Registration Number:

41765 (View in ClassFinder)

Credit Hours:

3

Instructor:

Chih Lai

We can keep improving the quality and safety of health care if the rapid growth of medical knowledge and medical data can be efficiently analyzed and effectively shared. This course will discuss processes in healthcare analytics, including data acquisition, storage, retrieval, management, and analysis of healthcare data in heterogeneous formats (i.e. numeric health records, medical text, and medical images). Major topics include: (1) analyzing patient records and identifying frequent medical sequences for treatment and prevention, (2) evaluating medical text and generating aggregated summary based on hierarchical medical concepts, (3) retrieving information from different types of medical images, (4) building clinic decision support systems to detect possible medical mistakes, and (5) comparing brain connectivity graphs from patients with different neurological conditions. Amazon Cloud will be used to analyze multi-million records of numeric and text data. Prerequisite: SEIS 630

Schedule Details

Location Time Day(s)
SEIS 736 - 01 Big Data Architecture - - - R - - - 1745 - 2100 OSS 326

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 326

Course Registration Number:

41174 (View in ClassFinder)

Credit Hours:

3

Instructor:

Bradley S. Rubin

This course covers emerging big data architectures, predominately Hadoop and related technologies that deal with large amounts of unstructured and semi-structured data. Topics include operating system, architecture, security, big data structure and storage. The primary applications discussed in this class focus on information retrieval, specifically text processing techniques and algorithms, such as parsing, stemming, compression, and string searching. Information retrieval is also a great case study for broader issues in building systems that scale and perform, so we discuss associated issues in data structures, algorithms, computational complexity, and measurement. Prerequisite: (SEIS 601 or SEIS 603) and SEIS 630 (can be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 736 - 02 Big Data Architecture - - - - F - - 1745 - 2100 OSS 432

Days of Week:

- - - - F - -

Time of Day:

1745 - 2100

Location:

OSS 432

Course Registration Number:

41609 (View in ClassFinder)

Credit Hours:

3

Instructor:

Bradley S. Rubin

This course covers emerging big data architectures, predominately Hadoop and related technologies that deal with large amounts of unstructured and semi-structured data. Topics include operating system, architecture, security, big data structure and storage. The primary applications discussed in this class focus on information retrieval, specifically text processing techniques and algorithms, such as parsing, stemming, compression, and string searching. Information retrieval is also a great case study for broader issues in building systems that scale and perform, so we discuss associated issues in data structures, algorithms, computational complexity, and measurement. Prerequisite: (SEIS 601 or SEIS 603) and SEIS 630 (can be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 737 - 01 Big Data Management - T - - - - - 1745 - 2100 OSS 326

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 326

Course Registration Number:

41540 (View in ClassFinder)

Credit Hours:

3

Instructor:

Chakravarthy Sankaraiah

This course covers the technical concepts of managing vast amount of unstructured, semi-structured and structured data, collectively called "Big Data". Due to the sheer volume of Big Data, traditional approaches to managing databases does not work well for Big data and does not perform as expected. A distributed architecture for both the file system and the operating system is needed. Some of the techniques used in managing Big Data have the origins in the research and the developments that have been going on for decades in the area of parallel processing and distributed database management systems. This course focuses on why big data sets must be distributed and the issues that distribution introduces. The basic concepts on which distributed data sets are handled are discussed first. Once a foundation is defined, software tools that we use to work with big data sets are studied to provide an in-depth analysis of the concepts introduced. Specifically, we will study the issues distributed data design, data fragmentation, data replication, distributed fault tolerance/recovery. We will also study the use of Hadoop, Pig, Hive, and HBase in dealing big data sets and use real life examples of how these open source software are used. Prerequisite: SEIS 630 (Database Management Systems and Design) or override is required. Familiarity with Java is strongly recommended. Prerequisite: SEIS 630.

Schedule Details

Location Time Day(s)
SEIS 737 - 02 Big Data Management - - W - - - - 1745 - 2100 OSS 333

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

41998 (View in ClassFinder)

Credit Hours:

3

Instructor:

Saeed K. Rahimi

This course covers the technical concepts of managing vast amount of unstructured, semi-structured and structured data, collectively called "Big Data". Due to the sheer volume of Big Data, traditional approaches to managing databases does not work well for Big data and does not perform as expected. A distributed architecture for both the file system and the operating system is needed. Some of the techniques used in managing Big Data have the origins in the research and the developments that have been going on for decades in the area of parallel processing and distributed database management systems. This course focuses on why big data sets must be distributed and the issues that distribution introduces. The basic concepts on which distributed data sets are handled are discussed first. Once a foundation is defined, software tools that we use to work with big data sets are studied to provide an in-depth analysis of the concepts introduced. Specifically, we will study the issues distributed data design, data fragmentation, data replication, distributed fault tolerance/recovery. We will also study the use of Hadoop, Pig, Hive, and HBase in dealing big data sets and use real life examples of how these open source software are used. Prerequisite: SEIS 630 (Database Management Systems and Design) or override is required. Familiarity with Java is strongly recommended. Prerequisite: SEIS 630.

Schedule Details

Location Time Day(s)
SEIS 741 - 01 Embedded Microprocessor Design M - - - - - - 1745 - 2100 OSS LL18

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS LL18

Course Registration Number:

42481 (View in ClassFinder)

Credit Hours:

3

Instructor:

John M. Kruse

This course will introduce the concepts of embedded processor design. An overview of the most popular embedded processors such as the ARM, Analog Devices (ARM7 Cortex, Blackfin, and Sharc) TI (MSP430, 55x, ect), Microchip (PIC), Freescale (RS08, Power Core, M Core, etc), Atmel (AVR), NXP (ARM9, 8051, etc) will be covered. the strengths and weakness of each family of processors and where they are used will also be covered. The use of assemblers and simulators, accelerometers, A/D, D/A converters, signal synthesizers and serial communication interfaces will be covered in detail. The students will have lab time with ARM circuit Boards. Blackfin circuit boards are also availalbe for the student to use. An introduction to Digital Signal Processing in the time domain will be presented from a firmware engineers perspective, (time domain with no calculus). Prerequisite: SEIS 610

Schedule Details

Location Time Day(s)
SEIS 744 - 01 Internet of Things M - - - - - - 1745 - 2100 OSS 313

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 313

Course Registration Number:

41851 (View in ClassFinder)

Credit Hours:

3

Instructor:

Daniel R. Yarmoluk

This course is designed for students to be exposed to technologies and best practices that help them understand high level concepts and the supporting technologies that make up the Internet of Things. Additionally, students will use their hands to build a prototype of a real product and put it into practice to collect and analyze data. This will give them the foundation to further explore creating their own product in the future or join an existing IoT focused company. Most importantly, at the end of the course students will be able to understand the broad concepts and speak intelligently on how the Internet of Things will have an impact on our lives today and in the future. Prerequisite: SEIS 601 or SEIS 603.

Schedule Details

Location Time Day(s)
SEIS 751 - 01 Web App. Design & Dev. - T - - - - - 1745 - 2100 OSS 328

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 328

Course Registration Number:

40114 (View in ClassFinder)

Credit Hours:

3

Instructor:

Marius N. Tegomoh

This course introduces the fundamentals of web application design, and development using open standards. Students will learn how to create interactive database- driven media rich web applications. Students will learn both the technical and design aspects of creating effective web applications using a variety of technologies and development tools (mostly open source tools where appropriate). The course culminates in a term project that brings together elements of design and technology into a functioning web application. This is an introductory course and no prior knowledge or experience of web design or web development is required. Prerequisite: SEIS 610.

Schedule Details

Location Time Day(s)
SEIS 763 - 01 Machine Learning See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

41539 (View in ClassFinder)

Credit Hours:

3

Instructor:

Manjeet Rege

Machine Learning builds computational systems that learn from and adapt to the data presented to them. It has become one of the essential pillars in information technology today and provides a basis for several applications we use daily in diverse domains such as engineering, medicine, finance, and commerce. This course covers widely used supervised and unsupervised machine learning algorithms used in industry in technical depth, discussing both the theoretical underpinnings of machine learning techniques and providing hands-on experience in implementing them. Additionally, students will also learn to evaluate effectiveness and avoid common pitfalls in applying machine learning to a given problem. Prerequisite: Minimum grade of C- in SEIS 631

Schedule Details

Location Time Day(s)
OSS 3280900-160015 Sep '18
OSS 3280900-160029 Sep '18
OSS 3280900-160013 Oct '18
OSS 3280900-160027 Oct '18
OSS 3280900-160010 Nov '18
OSS 3280900-160001 Dec '18
OSS 3280900-160015 Dec '18
SEIS 763 - 02 Machine Learning - - - R - - - 1745 - 2100 OSS 325

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 325

Course Registration Number:

42485 (View in ClassFinder)

Credit Hours:

3

Instructor:

Manjeet Rege

Machine Learning builds computational systems that learn from and adapt to the data presented to them. It has become one of the essential pillars in information technology today and provides a basis for several applications we use daily in diverse domains such as engineering, medicine, finance, and commerce. This course covers widely used supervised and unsupervised machine learning algorithms used in industry in technical depth, discussing both the theoretical underpinnings of machine learning techniques and providing hands-on experience in implementing them. Additionally, students will also learn to evaluate effectiveness and avoid common pitfalls in applying machine learning to a given problem. Prerequisite: Minimum grade of C- in SEIS 631

Schedule Details

Location Time Day(s)
SEIS 764 - 01 Artificial Intelligence - - W - - - - 1745 - 2100 OSS 328

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 328

Course Registration Number:

43124 (View in ClassFinder)

Credit Hours:

Instructor:

Chih Lai

Artificial Intelligence has made significant strides in recent times and has become ubiquitous in the modern world, impacting our lives in different ways. By harnessing the power of deep neural networks, it is now possible to build real-world intelligent applications that outperform human precision in certain tasks. This course provides a broad coverage of AI techniques with a focus on industry application. Major topics covered in this course include: (1) how deep neural networks learn their intelligence, (2) self-learning from raw data, (3) common training problems and solutions, (4) transferring learning from existing AI systems, (5) training AI systems for machine visions with high accuracy, and (6) training time-series AI systems for recognizing sequential patterns. Students will have hands-on exercises for building efficient AI systems. Prerequisite: SEIS 763

Schedule Details

Location Time Day(s)
SEIS 764 - 02 Artificial Intelligence M - - - - - - 1745 - 2100 OSS 328

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 328

Course Registration Number:

43125 (View in ClassFinder)

Credit Hours:

Instructor:

Chih Lai

Artificial Intelligence has made significant strides in recent times and has become ubiquitous in the modern world, impacting our lives in different ways. By harnessing the power of deep neural networks, it is now possible to build real-world intelligent applications that outperform human precision in certain tasks. This course provides a broad coverage of AI techniques with a focus on industry application. Major topics covered in this course include: (1) how deep neural networks learn their intelligence, (2) self-learning from raw data, (3) common training problems and solutions, (4) transferring learning from existing AI systems, (5) training AI systems for machine visions with high accuracy, and (6) training time-series AI systems for recognizing sequential patterns. Students will have hands-on exercises for building efficient AI systems. Prerequisite: SEIS 763

Schedule Details

Location Time Day(s)
SEIS 776 - 01 Project I - - - - - - - -

Days of Week:

- - - - - - -

Time of Day:

-

Location:

Course Registration Number:

40115 (View in ClassFinder)

Credit Hours:

3

Instructor:

Bhabani Misra

Available to Software Engineering, Software Management and Information Technology students. These students may choose to register for SEIS776-777 and complete a research or software development project under the supervision of a full-time GPS faculty member. Students cannot receive credit for SEIS776 without completing SEIS777. Prerequisite: SEIS 627 and permission of the department.

Schedule Details

Location Time Day(s)
SEIS 777 - 01 Project II - - - - - - - -

Days of Week:

- - - - - - -

Time of Day:

-

Location:

Course Registration Number:

40116 (View in ClassFinder)

Credit Hours:

3

Instructor:

Bhabani Misra

Available to Software Engineering, Software Management and Information Technology students. These students may choose to register for SEIS776-777 and complete a research or software development project under the supervision of a full-time GPS faculty member. Students cannot receive credit for SEIS776 without completing SEIS777. Prerequisite: SEIS 627 and permission of the department.

Schedule Details

Location Time Day(s)

J-Term 2019 Courses

Course - Section Title Days Time Location

Spring 2019 Courses

Course - Section Title Days Time Location
SEIS 601 - 01 Found. of Software Dev-Java - - W - - - - 1745 - 2100 OSS 325

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 325

Course Registration Number:

21432 (View in ClassFinder)

Credit Hours:

Instructor:

Michael A. Dorin

The primary objective of this course is to provide the experienced programmer with knowledge of and experience with fundamental data structures and algorithms used in software design and development. The secondary objective is to give a fast-paced introduction to the Java programming language. Students will write multiple programs in Java, both to become familiar with Java and to apply data structure concepts. Prerequisite: none

Schedule Details

Location Time Day(s)
SEIS 602 - 01 Intermediate Software Dev - - W - - - - 1745 - 2100 OSS 431

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 431

Course Registration Number:

21434 (View in ClassFinder)

Credit Hours:

3

Instructor:

Syed H. Naqvi

This is an introductory software development course, with focus on intermediate-level fundamental and foundational concepts. These concepts include abstract data types such as lists, stacks, queues, and trees/graphs, as well as some of their associated algorithms such as insertion, deletion, searching, sorting, and traversals. Canonical implementations as well as framework supplied implementation alternatives (such as the JDK or other framework alternatives) will be explored and used. To apply the lecture concepts, we will implement software using the Java programming language and explore some of the tools used by software developers. There are many types of tools to be considered, such as integrated development environments (IDEs e.g. eclipse), tools for managing software build, configuration, and version control (e.g. Ant/Maven, Git), tools for testing and debugging (e.g. JUnit, LogBack/Log4J/SLF4J) and other tools used by developers to understand the code they are working with (e.g. GrepCode). In addition, we will discuss intermediate concepts, issues, and techniques including an introduction to concurrency issues, and development practices such as refactoring, logging, and debugging. Prerequisite: SEIS 601 or an equivalent understanding of Foundational Software Development concepts and the ability to use and understand the Java programming language is required.

Schedule Details

Location Time Day(s)
SEIS 603 - 01 Found. Software Dev-Python - T - - - - - 1745 - 2100 TMH 254

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

TMH 254

Course Registration Number:

21435 (View in ClassFinder)

Credit Hours:

3

Instructor:

Eric V. Level

This is an introductory software development course, with focus on fundamental and foundational concepts. These concepts include general problem solving and algorithm creation techniques, data types, constants, variables and expressions, Boolean, control flow, and object-oriented concepts. Applying these concepts, we implement programs using the Python language. We will examine its use as both an interpreted and a compiled language, working with data types such as numbers, strings, lists, dictionaries, and sets. Students will learn how to apply Python in managing data. No previous programming experience in Python or any other programming language is required.

Schedule Details

Location Time Day(s)
SEIS 603 - 02 Found. Software Dev-Python M - - - - - - 1745 - 2100 OSS 428

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 428

Course Registration Number:

21436 (View in ClassFinder)

Credit Hours:

3

Instructor:

Damodar Chetty

This is an introductory software development course, with focus on fundamental and foundational concepts. These concepts include general problem solving and algorithm creation techniques, data types, constants, variables and expressions, Boolean, control flow, and object-oriented concepts. Applying these concepts, we implement programs using the Python language. We will examine its use as both an interpreted and a compiled language, working with data types such as numbers, strings, lists, dictionaries, and sets. Students will learn how to apply Python in managing data. No previous programming experience in Python or any other programming language is required.

Schedule Details

Location Time Day(s)
SEIS 603 - 03 Found. Software Dev-Python - - - R - - - 1745 - 2100 JRC 301

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

JRC 301

Course Registration Number:

21437 (View in ClassFinder)

Credit Hours:

3

Instructor:

Eric V. Level

This is an introductory software development course, with focus on fundamental and foundational concepts. These concepts include general problem solving and algorithm creation techniques, data types, constants, variables and expressions, Boolean, control flow, and object-oriented concepts. Applying these concepts, we implement programs using the Python language. We will examine its use as both an interpreted and a compiled language, working with data types such as numbers, strings, lists, dictionaries, and sets. Students will learn how to apply Python in managing data. No previous programming experience in Python or any other programming language is required.

Schedule Details

Location Time Day(s)
SEIS 605 - 01 Technical Communications - T - - - - - 1745 - 2100 OSS 329

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 329

Course Registration Number:

21438 (View in ClassFinder)

Credit Hours:

3

Instructor:

Kirk T. Livingston

Teaches the fundamentals of written and oral communication as practiced by IT professionals. The course emphasizes product descriptions, instructions, informative and persuasive oral presentations, the role of graphics, and teamwork on projects. In addition, the course introduces managerial strategies and tactics, such as planning and evaluation, which are critical for meeting an intended audience's needs. Recently, the scope of this course was expanded to include communication issues related to business analysis and project management. After completing this course, students will be more confident about their ability to communicate effectively in the workplace. For MS Software students, this course must be completed before exceeding 12 credits in Software Engineering, Software Management, and Information Technology.

Schedule Details

Location Time Day(s)
SEIS 605 - 02 Technical Communications - - - R - - - 1745 - 2100 OSS 329

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 329

Course Registration Number:

21439 (View in ClassFinder)

Credit Hours:

3

Instructor:

Dorian G. Harvey

Teaches the fundamentals of written and oral communication as practiced by IT professionals. The course emphasizes product descriptions, instructions, informative and persuasive oral presentations, the role of graphics, and teamwork on projects. In addition, the course introduces managerial strategies and tactics, such as planning and evaluation, which are critical for meeting an intended audience's needs. Recently, the scope of this course was expanded to include communication issues related to business analysis and project management. After completing this course, students will be more confident about their ability to communicate effectively in the workplace. For MS Software students, this course must be completed before exceeding 12 credits in Software Engineering, Software Management, and Information Technology.

Schedule Details

Location Time Day(s)
SEIS 610 - 01 Software Engineering - T - - - - - 1745 - 2100 OSS 313

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 313

Course Registration Number:

21440 (View in ClassFinder)

Credit Hours:

Instructor:

Michael A. Dorin

This is a survey course covering software engineering concepts, techniques, and methodologies. Topics covered include software engineering; software process and its difficulties; software life-cycle models; software metrics; project planning including cost estimation; design methodologies including structured design, and object-oriented design; software testing; and software maintenance. A brief review of data structures is included. Prerequisite: SEIS 601 or SEIS 603. SEIS 610 can be taken concurrently with SEIS 601 or SEIS 603.

Schedule Details

Location Time Day(s)
SEIS 610 - 02 Software Engineering - - - R - - - 1745 - 2100 TMH 254

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

TMH 254

Course Registration Number:

21441 (View in ClassFinder)

Credit Hours:

Instructor:

Michael A. Dorin

This is a survey course covering software engineering concepts, techniques, and methodologies. Topics covered include software engineering; software process and its difficulties; software life-cycle models; software metrics; project planning including cost estimation; design methodologies including structured design, and object-oriented design; software testing; and software maintenance. A brief review of data structures is included. Prerequisite: SEIS 601 or SEIS 603. SEIS 610 can be taken concurrently with SEIS 601 or SEIS 603.

Schedule Details

Location Time Day(s)
SEIS 610 - 03 Software Engineering See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

21442 (View in ClassFinder)

Credit Hours:

Instructor:

Michael A. Dorin

This is a survey course covering software engineering concepts, techniques, and methodologies. Topics covered include software engineering; software process and its difficulties; software life-cycle models; software metrics; project planning including cost estimation; design methodologies including structured design, and object-oriented design; software testing; and software maintenance. A brief review of data structures is included. Prerequisite: SEIS 601 or SEIS 603. SEIS 610 can be taken concurrently with SEIS 601 or SEIS 603.

Schedule Details

Location Time Day(s)
OSS 3130900-160009 Feb '19
OSS 3130900-160023 Feb '19
OSS 3130900-160009 Mar '19
OSS 3130900-160023 Mar '19
OSS 3130900-160006 Apr '19
OSS 3130900-160027 Apr '19
OSS 3130900-160011 May '19
SEIS 627 - 01 Software Planning & Testing - - - R - - - 1745 - 2100 OSS 325

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 325

Course Registration Number:

22347 (View in ClassFinder)

Credit Hours:

3

Instructor:

Aric B. Aune

This course presents a software planning and quality perspective that guides the selection of tools and application of techniques needed for the successful completion of software development projects. A successful software project must manage many different, yet integrated activities. These activities include software development lifecycle tasks such as requirements gathering, software design, and code implementation. Many other activities also need to be planned and managed, such as project scope, schedule, and cost. In any successful software project, when issues arise (e.g. the requirements change, a defect in the software is discovered, scheduled activities do not go as planned, etc.) they need to be prioritized and appropriately addressed. To minimize the impact of software quality issues, software testing and quality improvement activities need to be planned, executed and coordinated. The purpose of this course is to learn the foundational concepts and practices needed to produce software that is completed on time, within budget, and with the necessary scope and quality required. While software development activities are covered in other courses, this course will focus more on the software planning and testing activities. Project management topics covered include: integration management, scope management, time management, cost management, and quality management from a software planning perspective. Software testing and quality topics covered include: testing terms and concepts, lower-level testing (e.g. unit and integration testing), higher-level testing (e.g. system and acceptance testing), and test automation. Agile Project and Product Management using Scrum will be introduced as an approach for directing these activities and laying the foundation for continuous process improvement and quality assurance. Prerequisite: SEIS 610 AND SEIS 601/603

Schedule Details

Location Time Day(s)
SEIS 627 - 03 Software Planning & Testing M - - - - - - 1745 - 2100 OSS 333

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

22349 (View in ClassFinder)

Credit Hours:

3

Instructor:

Frank S. Haug

This course presents a software planning and quality perspective that guides the selection of tools and application of techniques needed for the successful completion of software development projects. A successful software project must manage many different, yet integrated activities. These activities include software development lifecycle tasks such as requirements gathering, software design, and code implementation. Many other activities also need to be planned and managed, such as project scope, schedule, and cost. In any successful software project, when issues arise (e.g. the requirements change, a defect in the software is discovered, scheduled activities do not go as planned, etc.) they need to be prioritized and appropriately addressed. To minimize the impact of software quality issues, software testing and quality improvement activities need to be planned, executed and coordinated. The purpose of this course is to learn the foundational concepts and practices needed to produce software that is completed on time, within budget, and with the necessary scope and quality required. While software development activities are covered in other courses, this course will focus more on the software planning and testing activities. Project management topics covered include: integration management, scope management, time management, cost management, and quality management from a software planning perspective. Software testing and quality topics covered include: testing terms and concepts, lower-level testing (e.g. unit and integration testing), higher-level testing (e.g. system and acceptance testing), and test automation. Agile Project and Product Management using Scrum will be introduced as an approach for directing these activities and laying the foundation for continuous process improvement and quality assurance. Prerequisite: SEIS 610 AND SEIS 601/603

Schedule Details

Location Time Day(s)
SEIS 630 - 01 Database Mgmt Systems & Design M - - - - - - 1745 - 2100 OSS 328

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 328

Course Registration Number:

21447 (View in ClassFinder)

Credit Hours:

3

Instructor:

Saeed K. Rahimi

This course focuses on database management system concepts , database design, and implementation. Conceptual data modeling using Entity Relationships (ER) is used to capture the requirements of a database design. Relational model concepts are introduced and mapping from ER to relational model is discussed. Logical database design (Normalization) and indexing strategies are also discussed to aide system performance. Relational Algebra and Structured Query Language (SQL) are used to work with a database. From a system perspective, the course focuses on query optimization and execution strategies, concurrency control, locking, deadlocks and database back up and recovery concepts. Database security and authorization are also discussed. Students will use Oracle and/or SQL Server to design a database and complete an application using SQL as their project. Prerequisite: SEIS 610. SEIS 630 may be taken concurrently with SEIS610.

Schedule Details

Location Time Day(s)
SEIS 630 - 02 Database Mgmt Systems & Design - - - R - - - 1745 - 2100 OSS 328

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 328

Course Registration Number:

21448 (View in ClassFinder)

Credit Hours:

Instructor:

Jordan B. Barlow

This course focuses on database management system concepts , database design, and implementation. Conceptual data modeling using Entity Relationships (ER) is used to capture the requirements of a database design. Relational model concepts are introduced and mapping from ER to relational model is discussed. Logical database design (Normalization) and indexing strategies are also discussed to aide system performance. Relational Algebra and Structured Query Language (SQL) are used to work with a database. From a system perspective, the course focuses on query optimization and execution strategies, concurrency control, locking, deadlocks and database back up and recovery concepts. Database security and authorization are also discussed. Students will use Oracle and/or SQL Server to design a database and complete an application using SQL as their project. Prerequisite: SEIS 610. SEIS 630 may be taken concurrently with SEIS610.

Schedule Details

Location Time Day(s)
SEIS 630 - 03 Database Mgmt Systems & Design See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

21449 (View in ClassFinder)

Credit Hours:

Instructor:

Jordan B. Barlow

This course focuses on database management system concepts , database design, and implementation. Conceptual data modeling using Entity Relationships (ER) is used to capture the requirements of a database design. Relational model concepts are introduced and mapping from ER to relational model is discussed. Logical database design (Normalization) and indexing strategies are also discussed to aide system performance. Relational Algebra and Structured Query Language (SQL) are used to work with a database. From a system perspective, the course focuses on query optimization and execution strategies, concurrency control, locking, deadlocks and database back up and recovery concepts. Database security and authorization are also discussed. Students will use Oracle and/or SQL Server to design a database and complete an application using SQL as their project. Prerequisite: SEIS 610. SEIS 630 may be taken concurrently with SEIS610.

Schedule Details

Location Time Day(s)
OSS 3280900-160016 Feb '19
OSS 3280900-160002 Mar '19
OSS 3280900-160016 Mar '19
OSS 3280900-160030 Mar '19
OSS 3280900-160013 Apr '19
OSS 3280900-160004 May '19
OSS 3280900-160018 May '19
SEIS 631 - 01 Foundations of Data Analysis - - W - - - - 1745 - 2100 TMH 253

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

TMH 253

Course Registration Number:

21450 (View in ClassFinder)

Credit Hours:

Instructor:

Kristine Kubisiak

This course provides a broad introduction to the subject of data analysis by introducing common techniques that are essential for analyzing and deriving meaningful information from datasets. In particular, the course will focus on relevant methods for performing data collection, representation, transformation, and data-driven decision making. Students will also develop proficiency in the widely used R language which will be used throughout the course to reinforce the topics covered. Prerequisite: SEIS 601 or SEIS 603 (may be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 631 - 02 Foundations of Data Analysis - - - R - - - 1745 - 2100 TMH 253

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

TMH 253

Course Registration Number:

21451 (View in ClassFinder)

Credit Hours:

Instructor:

Anne A. Eaton

This course provides a broad introduction to the subject of data analysis by introducing common techniques that are essential for analyzing and deriving meaningful information from datasets. In particular, the course will focus on relevant methods for performing data collection, representation, transformation, and data-driven decision making. Students will also develop proficiency in the widely used R language which will be used throughout the course to reinforce the topics covered. Prerequisite: SEIS 601 or SEIS 603 (may be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 631 - 03 Foundations of Data Analysis - T - - - - - 1745 - 2100 BIN LL02

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

BIN LL02

Course Registration Number:

21512 (View in ClassFinder)

Credit Hours:

Instructor:

Aran W. Glancy

This course provides a broad introduction to the subject of data analysis by introducing common techniques that are essential for analyzing and deriving meaningful information from datasets. In particular, the course will focus on relevant methods for performing data collection, representation, transformation, and data-driven decision making. Students will also develop proficiency in the widely used R language which will be used throughout the course to reinforce the topics covered. Prerequisite: SEIS 601 or SEIS 603 (may be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 632 - 01 Data Analytics & Visualization - T - - - - - 1745 - 2100 OSS 325

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 325

Course Registration Number:

21452 (View in ClassFinder)

Credit Hours:

Instructor:

Ebrahim F. Kazemzadeh

The course provides an introduction to concepts and techniques used in field of data analytics and visualization. Data analytics is defined to be the science of examining raw data with the purpose of discovering knowledge by analyzing current and historical facts. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery, and best practices for creating effective data visualizations. Through practical application of the above topics, students will also develop proficiency in using analytics tools.

Schedule Details

Location Time Day(s)
SEIS 632 - 02 Data Analytics & Visualization - - W - - - - 1745 - 2100 OSS 333

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

21453 (View in ClassFinder)

Credit Hours:

Instructor:

Ebrahim F. Kazemzadeh

The course provides an introduction to concepts and techniques used in field of data analytics and visualization. Data analytics is defined to be the science of examining raw data with the purpose of discovering knowledge by analyzing current and historical facts. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery, and best practices for creating effective data visualizations. Through practical application of the above topics, students will also develop proficiency in using analytics tools.

Schedule Details

Location Time Day(s)
SEIS 632 - 03 Data Analytics & Visualization - T - - - - - 1745 - 2100 TMH 253

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

TMH 253

Course Registration Number:

21454 (View in ClassFinder)

Credit Hours:

Instructor:

Manjeet Rege

The course provides an introduction to concepts and techniques used in field of data analytics and visualization. Data analytics is defined to be the science of examining raw data with the purpose of discovering knowledge by analyzing current and historical facts. Insights discovered from the data are then communicated using data visualization. Topics covered in the course include predictive analytics, pattern discovery, and best practices for creating effective data visualizations. Through practical application of the above topics, students will also develop proficiency in using analytics tools.

Schedule Details

Location Time Day(s)
SEIS 635 - 01 Software Analysis and Design See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

21455 (View in ClassFinder)

Credit Hours:

Instructor:

Eric V. Level

This course covers basic object-oriented techniques for specifying, designing, and implementing software systems. Iterative development methodologies are emphasized. The Unified Modeling Language (UML) is used as a notational system for capturing the development process artifacts. Students will gain experience with a software tool for creating UML diagrams. Other topics include use cases, class discovery and domain modeling, responsibility-driven design, basic design patterns, software class design, converting designs to code, object-oriented testing, packaging, deployment, along with intermediate Java topics relevant to system implementation. This course also introduces ideas in functional and parallel programming. Students will work on an object-oriented team project, apply concepts and techniques to describe and create a working software system. Prerequisite: SEIS 602 and SEIS 610.

Schedule Details

Location Time Day(s)
OSS 3260900-160016 Feb '19
OSS 3260900-160002 Mar '19
OSS 3260900-160016 Mar '19
OSS 3260900-160030 Mar '19
OSS 3260900-160013 Apr '19
OSS 3260900-160004 May '19
OSS 3260900-160018 May '19
SEIS 636 - 01 Requirements Analysis See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

21456 (View in ClassFinder)

Credit Hours:

Instructor:

Jan M. Gardner

The objective of this course is to introduce the business analyst roles and responsibilities and knowledge areas such as enterprise analysis, requirements planning and measurement, requirements elicitation, requirements communication, requirements analysis and documentation, solution assessment and validation, business analysis fundamentals including tools and techniques. Prerequisite: SEIS 610. SEIS 636 may be taken concurrently with SEIS 610.

Schedule Details

Location Time Day(s)
OSS 3290900-160016 Feb '19
OSS 3290900-160002 Mar '19
OSS 3290900-160016 Mar '19
OSS 3290900-160030 Mar '19
OSS 3290900-160013 Apr '19
OSS 3290900-160027 Apr '19
OSS 3290900-160011 May '19
SEIS 662 - 01 Enterprise Resource Planning M - - - - - - 1745 - 2100 JRC 301

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

JRC 301

Course Registration Number:

21458 (View in ClassFinder)

Credit Hours:

Instructor:

William H. Gamble

This course will provide a practical overview of Enterprise Resource Planning, connecting the academic and even marketing elements with real-world, case-based issues as encountered by business and other organizations. ERP has become a critical strategic consideration for many companies, and the course will look at best-practice implementations at leading companies internationally. Course will examine best practice usage of ERP in a global distributed computing environment. In addition, it will look into trends relating to critical issues such as Cloud and Big Data. Professionals currently working in the IT organizations or future IT professionals will benefit from this course. Prerequisite: Minimum grade of C- in SEIS 610

Schedule Details

Location Time Day(s)
SEIS 663 - 01 IT Security and Networking - T - - - - - 1745 - 2100 OWS 250

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OWS 250

Course Registration Number:

21459 (View in ClassFinder)

Credit Hours:

Instructor:

Melinda J. Mattox

This course will provide the foundation of information technology security, including authentication, authorization, access management, physical security, network security (firewalls, intrusion detection), application security (software and database), security regulations, and disaster recovery. We will explore social engineering and other human factors and the impact to security. There will be an emphasis on local area networking (LAN) and Internet architecture and protocols, including TCP/IP and the OSI layers. We study protocol details, the way they relate and interact with each other, and how they are applied in real systems. Prerequisite: SEIS610

Schedule Details

Location Time Day(s)
SEIS 663 - 02 IT Security and Networking - - - R - - - 1745 - 2100 OWS 250

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OWS 250

Course Registration Number:

21460 (View in ClassFinder)

Credit Hours:

Instructor:

Theodore M. Wallerstedt

This course will provide the foundation of information technology security, including authentication, authorization, access management, physical security, network security (firewalls, intrusion detection), application security (software and database), security regulations, and disaster recovery. We will explore social engineering and other human factors and the impact to security. There will be an emphasis on local area networking (LAN) and Internet architecture and protocols, including TCP/IP and the OSI layers. We study protocol details, the way they relate and interact with each other, and how they are applied in real systems. Prerequisite: SEIS610

Schedule Details

Location Time Day(s)
SEIS 664 - 01 Information Tech. Delivery - - - - F - - 1745 - 2100 OSS 428

Days of Week:

- - - - F - -

Time of Day:

1745 - 2100

Location:

OSS 428

Course Registration Number:

21461 (View in ClassFinder)

Credit Hours:

Instructor:

Charles T. Betz

This survey course covers IT delivery, operations, and management in both theory and practice, including Business and consumer needs for IT value, IT infrastructure, cloud, continuous integration/delivery, IT product and service management, work and task management, operations management, organization and culture, project management, process management, change and incident management, IT governance, risk, security, and compliance business continuity, enterprise information and e-records management, enterprise IT architecture and portfolio management, IT management frameworks including ITIL, COBIT, and IT4IT, Agile and Lean influences including Kanban, Scrum, and DevOps, Continuous improvement and IT. Prerequisite: SEIS 610

Schedule Details

Location Time Day(s)
SEIS 665 - 01 Dev Ops & Cloud Infrastructure M - - - - - - 1745 - 2100 OSS 326

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 326

Course Registration Number:

21462 (View in ClassFinder)

Credit Hours:

Instructor:

Chi-Lung Chiang

This course covers the engineering and design of IT infrastructure, focusing on cloud-scale distributed systems and modern DevOps practices. IT infrastructure deployment practices are rapidly changing as organizations build "Infrastructure as code" and adopt cloud computing platforms. We will examine the theory behind these modern practices and the real-world implementation challenges faced by IT organizations. While the lessons will cover a number of theoretical concepts, we will primarily learn by doing. Students will gain hands-on experience with several widely-adopted IT platforms including Github, AWS, and Docker. Prerequisite: SEIS 610

Schedule Details

Location Time Day(s)
SEIS 665 - 02 Dev Ops & Cloud Infrastructure - T - - - - - 1745 - 2100 OSS 326

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 326

Course Registration Number:

22350 (View in ClassFinder)

Credit Hours:

Instructor:

Chi-Lung Chiang

This course covers the engineering and design of IT infrastructure, focusing on cloud-scale distributed systems and modern DevOps practices. IT infrastructure deployment practices are rapidly changing as organizations build "Infrastructure as code" and adopt cloud computing platforms. We will examine the theory behind these modern practices and the real-world implementation challenges faced by IT organizations. While the lessons will cover a number of theoretical concepts, we will primarily learn by doing. Students will gain hands-on experience with several widely-adopted IT platforms including Github, AWS, and Docker. Prerequisite: SEIS 610

Schedule Details

Location Time Day(s)
SEIS 665 - 03 Dev Ops & Cloud Infrastructure - - - R - - - 1745 - 2100 OSS 326

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 326

Course Registration Number:

22351 (View in ClassFinder)

Credit Hours:

Instructor:

Chi-Lung Chiang

This course covers the engineering and design of IT infrastructure, focusing on cloud-scale distributed systems and modern DevOps practices. IT infrastructure deployment practices are rapidly changing as organizations build "Infrastructure as code" and adopt cloud computing platforms. We will examine the theory behind these modern practices and the real-world implementation challenges faced by IT organizations. While the lessons will cover a number of theoretical concepts, we will primarily learn by doing. Students will gain hands-on experience with several widely-adopted IT platforms including Github, AWS, and Docker. Prerequisite: SEIS 610

Schedule Details

Location Time Day(s)
SEIS 721 - 01 Advanced Computer Security - T - - - - - 1745 - 2100 OWS LL54

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OWS LL54

Course Registration Number:

22352 (View in ClassFinder)

Credit Hours:

Instructor:

Bradley S. Rubin

This course is the next step beyond the prerequisite course, Computer Security. Given the security concepts and building blocks developed in the former course, this course both explores these previous topics in greater depth and covers additional topics. Topics will include advanced cryptography, single sign on leveraging directories,wireless network security, firewalls, VPNs, and intrusion detection and prevention systems, and other security technologies. There is significant coverage of application security issues (buffer overrun, SQL injection, cross-site scripting, etc.) as well. In addition, this course utilizes a computer security lab for hands-on exercises that reinforce the material and covers weekly current events in computer security. Prerequisites: SEIS 663 and SEIS 720.

Schedule Details

Location Time Day(s)
SEIS 732 - 01 Data Warehouse & Bus Intel - T - - - - - 1745 - 2100 OSS 328

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 328

Course Registration Number:

21464 (View in ClassFinder)

Credit Hours:

Instructor:

Frank S. Haug

In order to build and maintain a successful data warehouse, it is important to understand all of its components and how they fit together. This course will cover data warehouse and data mart lifecycle phases while focusing on infrastructure, design, and management issues. The course project will provide an opportunity to for hands-on experience with some of the available tools and technologies. Topics include: differences between data warehouses and traditional database systems (OLTP), multidimensional analysis and design, building data warehouses using "cube" vs. RDBMS (Star schema, etc.), planning for data warehouses, extraction transformation and loading (ETL), online analytical processing (OLAP), data mining, quality and cleansing, common pitfalls to avoid when designing, implementing and maintaining data warehouse environments, and the impact of new technologies (data webhouse, clickstream, XML). Prerequisite: SEIS630

Schedule Details

Location Time Day(s)
SEIS 732 - 02 Data Warehouse & Bus Intel - - W - - - - 1745 - 2100 OSS 328

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OSS 328

Course Registration Number:

21465 (View in ClassFinder)

Credit Hours:

Instructor:

Frank S. Haug

In order to build and maintain a successful data warehouse, it is important to understand all of its components and how they fit together. This course will cover data warehouse and data mart lifecycle phases while focusing on infrastructure, design, and management issues. The course project will provide an opportunity to for hands-on experience with some of the available tools and technologies. Topics include: differences between data warehouses and traditional database systems (OLTP), multidimensional analysis and design, building data warehouses using "cube" vs. RDBMS (Star schema, etc.), planning for data warehouses, extraction transformation and loading (ETL), online analytical processing (OLAP), data mining, quality and cleansing, common pitfalls to avoid when designing, implementing and maintaining data warehouse environments, and the impact of new technologies (data webhouse, clickstream, XML). Prerequisite: SEIS630

Schedule Details

Location Time Day(s)
SEIS 733 - 01 Database Administratn Concepts - - - - F - - 1745 - 2100 OSS 333

Days of Week:

- - - - F - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

21466 (View in ClassFinder)

Credit Hours:

Instructor:

Bradford C. Armitage

Database Administrators (DBA's) have to perform multiple functions within an organization. This class focuses on the issues that database administrators have to deal with in their everyday professional life. Responsibilities of a DBA are broken down by functions and each function is studied. These include: database system planning, database system installation and upgrading, database design (conceptual, logical, and physical), normalization (de-normalization), database loading and unloading, database change management, data availability, database security and access management, performance management (query processing, indexing, physical space planning, etc.), system performance, data integrity, data and storage management, data migration, data movement and distribution, database connectivity, fault tolerance (back ups and recovery) and disaster recovery planning. Students will use SQL Server and Oracle to design, implement and administer their database using these two commercial products. Although the course uses examples of these two two product functions, it is not a SQL Server or Oracle DBA certifcation course. Prerequisite: SEIS 630

Schedule Details

Location Time Day(s)
SEIS 736 - 01 Big Data Architecture - - - R - - - 1745 - 2100 OSS 333

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

21472 (View in ClassFinder)

Credit Hours:

Instructor:

Bradley S. Rubin

This course covers emerging big data architectures, predominately Hadoop and related technologies that deal with large amounts of unstructured and semi-structured data. Topics include operating system, architecture, security, big data structure and storage. The primary applications discussed in this class focus on information retrieval, specifically text processing techniques and algorithms, such as parsing, stemming, compression, and string searching. Information retrieval is also a great case study for broader issues in building systems that scale and perform, so we discuss associated issues in data structures, algorithms, computational complexity, and measurement. Prerequisite: (SEIS 601 or SEIS 603) and SEIS 630 (can be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 736 - 02 Big Data Architecture - - - - - S - 0900 - 1215 OSS 333

Days of Week:

- - - - - S -

Time of Day:

0900 - 1215

Location:

OSS 333

Course Registration Number:

21469 (View in ClassFinder)

Credit Hours:

Instructor:

Bradley S. Rubin

This course covers emerging big data architectures, predominately Hadoop and related technologies that deal with large amounts of unstructured and semi-structured data. Topics include operating system, architecture, security, big data structure and storage. The primary applications discussed in this class focus on information retrieval, specifically text processing techniques and algorithms, such as parsing, stemming, compression, and string searching. Information retrieval is also a great case study for broader issues in building systems that scale and perform, so we discuss associated issues in data structures, algorithms, computational complexity, and measurement. Prerequisite: (SEIS 601 or SEIS 603) and SEIS 630 (can be taken concurrently).

Schedule Details

Location Time Day(s)
SEIS 737 - 01 Big Data Management M - - - - - - 1745 - 2100 OSS 325

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 325

Course Registration Number:

21473 (View in ClassFinder)

Credit Hours:

Instructor:

Chakravarthy Sankaraiah

This course covers the technical concepts of managing vast amount of unstructured, semi-structured and structured data, collectively called "Big Data". Due to the sheer volume of Big Data, traditional approaches to managing databases does not work well for Big data and does not perform as expected. A distributed architecture for both the file system and the operating system is needed. Some of the techniques used in managing Big Data have the origins in the research and the developments that have been going on for decades in the area of parallel processing and distributed database management systems. This course focuses on why big data sets must be distributed and the issues that distribution introduces. The basic concepts on which distributed data sets are handled are discussed first. Once a foundation is defined, software tools that we use to work with big data sets are studied to provide an in-depth analysis of the concepts introduced. Specifically, we will study the issues distributed data design, data fragmentation, data replication, distributed fault tolerance/recovery. We will also study the use of Hadoop, Pig, Hive, and HBase in dealing big data sets and use real life examples of how these open source software are used. Prerequisite: SEIS 630 (Database Management Systems and Design) or override is required. Familiarity with Java is strongly recommended. Prerequisite: SEIS 630.

Schedule Details

Location Time Day(s)
SEIS 737 - 02 Big Data Management - T - - - - - 1745 - 2100 OSS 333

Days of Week:

- T - - - - -

Time of Day:

1745 - 2100

Location:

OSS 333

Course Registration Number:

21474 (View in ClassFinder)

Credit Hours:

Instructor:

Asher Chaudhry

This course covers the technical concepts of managing vast amount of unstructured, semi-structured and structured data, collectively called "Big Data". Due to the sheer volume of Big Data, traditional approaches to managing databases does not work well for Big data and does not perform as expected. A distributed architecture for both the file system and the operating system is needed. Some of the techniques used in managing Big Data have the origins in the research and the developments that have been going on for decades in the area of parallel processing and distributed database management systems. This course focuses on why big data sets must be distributed and the issues that distribution introduces. The basic concepts on which distributed data sets are handled are discussed first. Once a foundation is defined, software tools that we use to work with big data sets are studied to provide an in-depth analysis of the concepts introduced. Specifically, we will study the issues distributed data design, data fragmentation, data replication, distributed fault tolerance/recovery. We will also study the use of Hadoop, Pig, Hive, and HBase in dealing big data sets and use real life examples of how these open source software are used. Prerequisite: SEIS 630 (Database Management Systems and Design) or override is required. Familiarity with Java is strongly recommended. Prerequisite: SEIS 630.

Schedule Details

Location Time Day(s)
SEIS 742 - 01 Advanced Microprocessor M - - - - - - 1745 - 2100 OSS 313

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

OSS 313

Course Registration Number:

22353 (View in ClassFinder)

Credit Hours:

Instructor:

John M. Kruse

This course covers the architecture of the most recently developed microprocessors such as the Blackfin processor from Analog Devices along with state of the art development tools. The student will learn advanced embedded design through several biomedical applications. Exposure to industrial and robotic applications will also be covered. The class has an emphasis on biomedical firmware applications. The students will design and code a biomedical project using the Blackfin processor BF533 circuit boards. Complex peripherals such as MEM's gyroscopes, Sigma Delta Converters and smart sensors will be covered and how to implement them into systems. The project provides hands-on experience in designing and developing microprocessor-based systems using the Blackfin BF533 microprocessor and its state of the art development tools. This processor was jointly developed by Intel and Analog Devices and is the most advanced and efficient fixed point architecture available today. Prerequisite: SEIS741.

Schedule Details

Location Time Day(s)
SEIS 744 - 01 Internet of Things M - - - - - - 1745 - 2100 TMH 254

Days of Week:

M - - - - - -

Time of Day:

1745 - 2100

Location:

TMH 254

Course Registration Number:

21477 (View in ClassFinder)

Credit Hours:

Instructor:

Daniel R. Yarmoluk

This course is designed for students to be exposed to technologies and best practices that help them understand high level concepts and the supporting technologies that make up the Internet of Things. Additionally, students will use their hands to build a prototype of a real product and put it into practice to collect and analyze data. This will give them the foundation to further explore creating their own product in the future or join an existing IoT focused company. Most importantly, at the end of the course students will be able to understand the broad concepts and speak intelligently on how the Internet of Things will have an impact on our lives today and in the future. Prerequisite: SEIS 601 or SEIS 603.

Schedule Details

Location Time Day(s)
SEIS 763 - 01 Machine Learning - - W - - - - 1745 - 2100 OWS 250

Days of Week:

- - W - - - -

Time of Day:

1745 - 2100

Location:

OWS 250

Course Registration Number:

21478 (View in ClassFinder)

Credit Hours:

Instructor:

Manjeet Rege

Machine Learning builds computational systems that learn from and adapt to the data presented to them. It has become one of the essential pillars in information technology today and provides a basis for several applications we use daily in diverse domains such as engineering, medicine, finance, and commerce. This course covers widely used supervised and unsupervised machine learning algorithms used in industry in technical depth, discussing both the theoretical underpinnings of machine learning techniques and providing hands-on experience in implementing them. Additionally, students will also learn to evaluate effectiveness and avoid common pitfalls in applying machine learning to a given problem. Prerequisite: Minimum grade of C- in SEIS 631

Schedule Details

Location Time Day(s)
SEIS 763 - 02 Machine Learning See Details * *

Days of Week:

See Details

Time of Day:

*

Location:

*

Course Registration Number:

21479 (View in ClassFinder)

Credit Hours:

Instructor:

Manjeet Rege

Machine Learning builds computational systems that learn from and adapt to the data presented to them. It has become one of the essential pillars in information technology today and provides a basis for several applications we use daily in diverse domains such as engineering, medicine, finance, and commerce. This course covers widely used supervised and unsupervised machine learning algorithms used in industry in technical depth, discussing both the theoretical underpinnings of machine learning techniques and providing hands-on experience in implementing them. Additionally, students will also learn to evaluate effectiveness and avoid common pitfalls in applying machine learning to a given problem. Prerequisite: Minimum grade of C- in SEIS 631

Schedule Details

Location Time Day(s)
OSS 3280900-160009 Feb '19
OSS 3280900-160023 Feb '19
OSS 3280900-160009 Mar '19
OSS 3280900-160023 Mar '19
OSS 3280900-160006 Apr '19
OSS 3280900-160027 Apr '19
OSS 3280900-160011 May '19
SEIS 764 - 01 Artificial Intelligence - - - R - - - 1745 - 2100 BIN LL02

Days of Week:

- - - R - - -

Time of Day:

1745 - 2100

Location:

BIN LL02

Course Registration Number:

22354 (View in ClassFinder)

Credit Hours:

3

Instructor:

Cort M. Lunke

Artificial Intelligence has made significant strides in recent times and has become ubiquitous in the modern world, impacting our lives in different ways. By harnessing the power of deep neural networks, it is now possible to build real-world intelligent applications that outperform human precision in certain tasks. This course provides a broad coverage of AI techniques with a focus on industry application. Major topics covered in this course include: (1) how deep neural networks learn their intelligence, (2) self-learning from raw data, (3) common training problems and solutions, (4) transferring learning from existing AI systems, (5) training AI systems for machine visions with high accuracy, and (6) training time-series AI systems for recognizing sequential patterns. Students will have hands-on exercises for building efficient AI systems. Prerequisite: SEIS 763

Schedule Details

Location Time Day(s)