Data Science & Artificial Intelligence, BS
Department & Program Chair: Chris Bopp, Ph.D.
Faculty
C. Bopp, Ph.D.
A. Foerst, Ph.D.
B. Kellogg, M.S.
The Data Science & Artificial Intelligence major prepares students for positions in data analytics and in the design, implementation, and management of AI systems. These technical data roles can be found across a broad range of sectors such as healthcare, business, and other interdisciplinary fields. This program emphasizes practical applications, ethical data practices, and strong analytical and computational skills. It also provides a solid foundation for advanced study at the graduate level.
The department follows the ACM (Association for Computing Machinery) guidelines for undergraduate education.
The department maintains three computer labs to support the curriculum. The Software Development Laboratory supports the first three courses in the major sequence and several upper-division courses. The Network/Systems Administration lab supports a variety of introductory and advanced networking and server management courses. The Cybersecurity Lab offers workstations for conducting advanced security assessments. Finally, a virtual lab environment allows students to gain hands-on experience with virtual servers, giving them the ability to configure and deploy new services.
Together, the department faculty has published numerous articles and textbooks. With the addition of practicing professionals, the program faculty provides breadth and depth in the foundational - as well as emerging areas - of computing. Students often participate in research projects with faculty supervision, occasionally co-authoring papers with faculty members.
| Code | Title | Credits |
|---|---|---|
| Data Science | ||
| Data Science courses: | 17 | |
| INTRO TO DATA & DATA ANALYTICS | ||
| PREDICITIVE MODELING IN AI | ||
| PRESCRIPTIVE AI | ||
| DATA SCIENCE CASE STUDIES | ||
| DATA SCIENCE TOOLKIT and DATA SCIENCE TOOLKIT LAB | ||
or DSAI-201R | DATA SCIENCE II | |
| EMERGING TRENDS IN DATA SCIENCE and EMERGING TRENDS IN DATA SCIENCE LAB | ||
or DSAI-301R | AI & MACHINE LEARNING | |
| Computer Science courses: | 24 | |
| INTRODUCTION TO PROGRAMMING IN PYTHON and INTRO TO PROGRAMMING IN PYTHON LAB | ||
| DATABASE AND BIG DATA and DATABASE AND BIG DATA LAB | ||
| USER EXPERIENCE DESIGN and USER EXPERIENCE DESIGN LAB | ||
| MACHINE LEARNING and MACHINE LEARNING LAB | ||
| SENIOR COMPREHENSIVE PROJECT I | ||
| SENIOR COMPREHENSIVE PROJECT II | ||
| Mathematics courses: | 12 | |
| CALCULUS I | ||
| DISCRETE MATHEMATICS I | ||
| DISCRETE MATHEMATICS II | ||
| LINEAR ALGEBRA | ||
| DS Electives from below options: | 9-10 | |
| CALCULUS II | ||
| CALCULUS III | ||
| INTRODUCTION TO INFORMATION SECURITY | ||
| COMPUTERS, SOCIETY & ETHICS | ||
| WEB DEVELOPMENT and WEB DEVELOPMENT LAB | ||
| STATISTICAL APPS FOR BUSINESS | ||
| ECONOMETRICS FOR FINANCE | ||
| Data Science Subject Electives 1 | 9 | |
| General Education Requirements | 37 | |
| Foreign Language 2 | 3 | |
| General Electives (enough to reach 120 credits) | 9 | |
| Total Credits | 120-121 | |
- 1
Students must propose their own three course sequence, and it must be approved by their advisor.
- 2
The foreign language must be at the level of 202 or higher. Students not prepared to begin at this level will need to take additional courses in language.
| First Year | |||
|---|---|---|---|
| Fall | Credits | Spring | Credits |
| DSAI-107 | 3 | MATH-207 | 3 |
| CS-130 & CSL-130 | 4 | ENG-102 | 3 |
| ENG-101 | 3 | THFS-101 | 3 |
| BONA-101 | 3 | CS-243 & CSL-2431 | 4 |
| Foreign Language Requirement | 3 | Foreign Language Requirement | 3 |
| 16 | 16 | ||
| Second Year | |||
| Fall | Credits | Spring | Credits |
| MATH-151 | 4 | MATH-241 | 3 |
| MATH-208 | 3 | CS-257 & CSL-257 | 4 |
| PHIL-104 | 3 | DSAI-301 & DSL-3013 | 4 |
| DSAI-201 & DSL-2012 | 4 | History Distribution Course | 3 |
| DS Subject Elective | 3 | ||
| 14 | 17 | ||
| Third Year | |||
| Fall | Credits | Spring | Credits |
| CS-258 & CSL-258 | 4 | DSAI-351 | 3 |
| DS Subject Elective | 3 | DSAI-341R | 4 |
| Natural Science Distribution | 4 | DS Subject Elective | 3 |
| DS Elective Course | 3 | Literature Distribution Course | 3 |
| Theology Distribution | 3 | ||
| 14 | 16 | ||
| Fourth Year | |||
| Fall | Credits | Spring | Credits |
| CS-401 | 2 | CS-402 | 1 |
| DS-401 | 2 | DS Elective Courses | 6 |
| DSAI-342R | 4 | Social Science Distribution | 3 |
| General Electives | 6 | General Electives | 3 |
| Philosophy Distribution | 3 | ||
| 17 | 13 | ||
| Total Credits 123 | |||
Changes in the sequence of the program listed above may be desirable. These must be made in consultation with the student’s academic adviser.