BS in Information Technology, Data Analytics and Artificial Intelligence
School of Business, Technology, and Health Care Administration
The Data Analytics and Artificial Intelligence specialization is designed to provide learners with the knowledge, skills and abilities necessary to support the work of data analytics in a variety of applications and settings. The curriculum addresses the range of process and workflow concepts and activities that make up the work of data analytics within distributed and cloud-based IT environments. Specific topics include data identification and collection, data cleansing, and quality measurement. These topics are applied to data mining and analytics projects involving data transformation, manipulation, analysis, and presentation. Learners examine fundamental theories and applications of artificial intelligence (AI), including evaluation of opportunities for AI. Learners are prepared to successfully solve IT problems using a variety of data analytics tools and techniques. Learners integrate an understanding of the role of data governance and management as factors that impact data analytics with data preparation, transformation, and manipulation to prepare datasets for business analysts as well as to create business solutions specific to the IT environment.
General Education Requirements
Choose 45 quarter credits with a minimum of 4 quarter credits from each category; see General Education Courses.
Required courses
Additional Program Requirements
Core courses
At least 51 quarter credits
| IT1006 | Information Technology Concepts and Practices | 6 |
| IT1170 | Goals and Ethics for the IT Professional | 6 |
| IT2180 | Operating System and Hardware Infrastructure | 6 |
| IT2230 | Introduction to Database Systems | 3 |
| IT2240 | Introduction to Programming | 3 |
| IT2280 | Network Technology and Architecture | 6 |
| IT3240 | Web Development and JavaScript | 6 |
| IT3249 | Software Architecture and User Experience Design | 6 |
| IT4803 | System Assurance Security | 6 |
| PM1000 | Project Management Principles | 3 |
Specialization courses
At least 30 quarter credits
| IT4345 | Data Modeling and Statistical Analysis | 6 |
| IT4535 | Introduction to Artificial Intelligence | 6 |
| IT4537 | Enterprise Data Storage and Data Management | 6 |
| IT4737 | Database Development | 6 |
| IT4738 | Tools and Techniques for Data Science with Python | 6 |
Elective courses
At least 42 quarter credits
Choose 42 quarter credits of additional undergraduate courses.
Capstone courses
At least 12 quarter credits
Taken during the learner’s final two quarters
| IT4997 | Information Technology Capstone 1 | 6 |
| IT4998 | Information Technology Capstone 2 | 6 |
Total
At least 180 quarter credits, including a minimum of 54 quarter credits from the 3000-level and above
Honors Pathway
Learners enrolled in the honors pathway complete the following general education courses.
Honors courses
At least 15 quarter credits
| PHI-H2005 | Honors Seminar: Critical Thinking for the Professional World | 3 |
| COM-H4005 | Communicating and Integrating Solutions in the Professional World | 6 |
| SOC-H3005 | Honors Professional Seminar | 6 |
These courses are applied toward the general education requirement and taken in addition to the remaining required courses.
Total
At least 180 quarter credits, including a minimum of 54 quarter credits from the 3000-level and above
One or more courses in this program may require a prerequisite(s). Refer to the course descriptions for details.
Learners who do not complete all program requirements within quarter credit/program point minimums will be required to accrue such additional quarter credits/program points as are associated with any additional or repeat coursework necessary for successful completion of program requirements.
Multiple Specializations available (must be within the same degree program)