The Bachelor of Science in Computer Science (BS-CS) program provides students with in-depth knowledge and analytical skills associated with the design, development, testing and documentation of a range of operating systems; database management; and programming languages. With computers found in every aspect of today’s society, students completing the Bachelor of Science Degree are prepared for a range of options, including continued study in the field at the graduate level.

Students pursuing a Bachelor of Science degree in Computer Science must complete all required courses in their chosen major as outlined below.

Prerequisites

Students must pass the following prerequisites before they can begin taking courses in the major:

MATH 1201	College Algebra
MATH 1280	Introduction to Statistics
CS 1101	Programming Fundamentals
CS 1102	Programming 1
CS 1103	Programming 2
CS 1105	Digital Electronics & Computer Architecture
CS 2203	Databases 1
CS 2204	Communications and Networking
CS 2205	Web Programming 1 (proctored course)
CS 2301	Operating Systems 1 (proctored course)
CS 2401	Software Engineering 1
CS 3303	Data Structures (Proctored course)
CS 3305	Web Programming 2 (Proctored course)
CS 3306	Databases 2 (proctored course)
CS 3307	Operating Systems 2 (proctored course)
CS 4402	Comparative Programming Languages (proctored course)
CS 4407	Data Mining and Machine Learning (proctored course)
MATH 1302	Discrete Mathematics
MATH 1211	Calculus

Electives

CS 3304	Analysis of Algorithms
CS 3308	Information Retrieval
CS 4403	Software Engineering 2
CS 4404	Advanced Networking and Data Security
CS 4405	Mobile Applications
CS 4406	Computer Graphics
CS 4408	Artificial Intelligence

Other Electives:  Students pursuing an Associate of Science degree may choose additional elective courses beyond those specified in the General Education requirements, and/or select introductory courses in other majors, and/or take additional courses in a student’s major that may not be required for the degree.

Learning Pathway

The learning pathway for your program has been curated to create the best learning experience for each student. For the most effective way to learn, courses need to be taken in the right sequence; lower-level courses prepare students with the foundational knowledge they need for higher level courses.  This allows students to learn  in order to better achieve the program and institutional learning outcomes .

 

Each student’s learning pathway is customized based on the courses the student has already taken and the degree requirements at the time of enrollment. For this reason, your path may differ from another student’s path. However, here is an example of a sequence a student with no previous classes or transfer credits may take through the Bachelor of Science in Computer Science* program:

1. UNIV 1001 Online Education Strategies
2. CS 1101 Programming Fundamentals
3. ENGL 1102 English Composition 2
4. CS 1102 Programming 1
5. General Education – Social and Behavior Science Course
6. CS 1103 Programming 2
7. General Education – Social and Behavior Science Course
8. CS 1104 Computer Systems
9. General Education – Mathematical Sciences Course
10. CS 2203 Databases 1
11. General Education – Mathematical Sciences Course
12. CS 2204 Communications and Networking
13. General Education – Values and Ethical Reasoning Course
14. CS 2205 Web Programming 1
15. General Education – Natural Science and Technology Course
16. BUS 1105 – Business Communication
17. General Education – Humanities Course
18. CS 2301 Operating Systems 1
19. General Education – Civilization Studies, Culture, and Belief Course
20. CS 2401 Software Engineering 1
21. General Education – Humanities Course
22. CS 3303 Data Structures
23. General Elective Course
24. Major Elective Course
25. General Elective Course
26. CS 3305 Web Programming 2
27. MATH 1211 Calculus
28. CS 3306 Databases 2
29. MATH 1302 Discrete Mathematics
30. CS 3307 Operating Systems 2
31. Major Elective Course
32. Major Elective Course
33. Major Elective Course
34. CS 4402 Comparative Programming Languages
35. Major Elective Course
36. Major Elective Course
37. Major Elective Course
38. Major Elective Course
39. CS 4407 Data Mining and Machine Learning
40. Major Elective Course

*For the Associate Degree, courses 1-20 serve as the learning sequence.