Computer Science, Bachelor of Science with a Concentration in Artificial Intelligence in Data Science (B.S.)
Program Objectives
The mission of the Bachelor of Science in Computer Science program is to provide students with an education that will prepare them to develop a career in the fields of computer science or computer forensics.
Program Requirements
CIP Code: 11.0101
Major
Code | Title | Hours |
---|---|---|
University Graduation Requirements | ||
General Education | 36 | |
Student Success Seminar | ||
SCO 100 | Student Success Seminar | 1 |
Upper division courses (42 hrs. distributed throughout Major/Supporting/Gen Ed/Free Electives categories) | ||
Major Requirements | ||
Core Courses | ||
CSC 185 | Discrete Structures I 1 | 3 |
CSC 190 | Object- Oriented Programming I 1 | 3 |
CSC 191 | Object-Oriented Programming II | 3 |
CSC 195 | Discrete Structures II | 3 |
CSC 308 | Mobile App Development for Apple iOS | 3 |
CSC 310 | Data Structures | 3 |
CSC 313 | Database Systems | 3 |
CSC 338 | Fundamentals of Cybersecurity | 3 |
CSC 340 | Ethics & Software Engineering | 3 |
CSC 499 | CS Career Preparation | 1 |
Concentrations | ||
Students must select one of the following Concentrations: | ||
Computer Science (General) | ||
Computer Technology | ||
Interactive Multimedia | ||
Artificial Intelligence in Data Science | 54 | |
Free Electives | ||
Choose from 1 hour of free electives | 1 | |
Total Hours | 120 |
- 1
Students without a 25 ACT or 590 SAT will be advised to take CSC 170 Intro to Game Programming as preparation for CSC 185 Discrete Structures I and CSC 190 Object- Oriented Programming I.
Concentration
Code | Title | Hours |
---|---|---|
Concentration Courses | ||
CSC 311 | Algorithms I | 3 |
CSC 320 | Algorithms II | 3 |
CSC 545 | Theory of Database Systems | 3 |
CSC 546 | Artificial Intelligence | 3 |
CSC 581 | Machine Learning | 3 |
CSC 582 | Big Data | 3 |
CSC 583 | Data Visualization | 3 |
Choose from one hour of the following: | 1 | |
Innovative Problem Solving | ||
Independent Work | ||
Senior Seminar | ||
Supporting Course Requirements | ||
Calculus I (Element 2) G | ||
MAT 244 | Calculus II | 4 |
STA 270 | Applied Statistics | 4 |
STA 340 | Applied Regression Analysis | 3 |
STA 375 | Sampling Methods | 3 |
STA 380 | Nonparametric Statistics | 3 |
STA 575 | Statistical Methods Using SAS | 3 |
STA 580 | R and Introductory Data Mining | 3 |
STA 585 | Experimental Design | 3 |
Choose from one of the following sequences: | 6 | |
Applied Engineering Mgt: | ||
Introduction to Quality | ||
Choose from one of the following: | ||
Process Control and Auditing | ||
Reliability and Sampling | ||
Six Sigma Quality | ||
Biology: | ||
Genetics 1 | ||
Bioinformatics: Principles and Applications | ||
Economics: | ||
Fundamentals of Microeconomics | ||
Fundamentals of Macroeconomics (Element 5B) G | ||
Insurance: | ||
INS 370 | ||
Choose from one of the following: | ||
INS 372 | ||
INS 374 | ||
INS 378 | ||
Statistics: | ||
Mathematical Statistics I | ||
Mathematical Statistics II | ||
Computer Science: | ||
Digital Storage Device Forensics | ||
Choose from one of the following: | ||
Internet Forensics | ||
Network Forensic and Investigation | ||
Personal Electronic Device Forensics | ||
Geography: | ||
Geographic Information Systems 2 | ||
Advanced GIS | ||
Homeland Security: | ||
Choose from two of the following: | ||
Intelligence Process | ||
Counterintelligence | ||
Intelligence Analysis | ||
Total Hours | 54 |
- G
Course also satisfies a General Education element. Hours are included within the 36 hr. General Education requirement above.
- 1
BIO 315 Genetics has a prerequisite of BIO 111 Cell and Molecular Biology or BIO 112 Ecology and Evolution.
- 2
GEO 353 Geographic Information Systems has a prerequisite of one course from: AGR 216 Principles of Soils Laboratory, GEO 100 Regions and Nations of the World, GEO 210 Introduction to Physical Geography, GEO 220 , GLY 102 Earth Science for Elementary Teachers, GLY 107 Gold and Diamonds, or GLY 108 Earthquakes and Volcanoes.