Computer Science, Bachelor of Science with a Concentration in Artificial Intelligence in Data Science (B.S.)
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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.