Computer Science, B.S. to Artificial Intelligence, M.S. Accelerated Program

Saint Louis University's computer science B.S. to artificial intelligence M.S. accelerated program allows a student to complete both the Bachelor of Science in Computer Science and the Master of Science in Artificial Intelligence at SLU in a shorter time period than if the degrees were pursued independently.

For additional information, see the catalog entries for the following SLU programs:

Computer Science, B.S.

Artificial Intelligence, M.S.

Students who wish to apply to this accelerated program should have completed all 2000-level coursework required of the computer science bachelor's program and have completed at least 75 credits at the time of application. At the time of application, students must have a cumulative GPA of at least 3.00 and a GPA of at least 3.00 in their computer science coursework. 

Contact the graduate coordinator for more details.

Non-Course Requirements

All Science and Engineering B.A. and B.S. students must complete an exit interview/survey near the end of their bachelor's program. 

Continuation Standards

Students must maintain a cumulative GPA of at least 3.00 and a GPA of at least 3.00 in their computer science coursework. 

Students who drop below that GPA while in the accelerated program will be placed on a one-semester probationary period before being dismissed from the accelerated program. 

Only grades of B or better in the graduate courses taken while an undergraduate can be applied to the master's degree.


Roadmaps are recommended semester-by-semester plans of study for programs and assume full-time enrollment unless otherwise noted.  

Courses and milestones designated as critical (marked with !) must be completed in the semester listed to ensure a timely graduation. Transfer credit may change the roadmap.

This roadmap should not be used in the place of regular academic advising appointments. All students are encouraged to meet with their advisor/mentor each semester. Requirements, course availability and sequencing are subject to change.

Plan of Study Grid
Year One
CSCI 10xxIntroduction to Computer Science 3
MATH 1510 Calculus I 4
University Core and/or General Electives 9
CSCI 1300 Introduction to Object-Oriented Programming 4
MATH 1510 Calculus I 4
University Core and/or General Electives 6
Year Two
CSCI 2100 Data Structures 4
CSCI 2500 Computer Organization and Systems 3
MATH 1660 Discrete Mathematics 3
Science I with lab 4
PHIL 3050X Computer Ethics 3
CSCI 2300 Object-Oriented Software Design 3
CSCI 2510 Principles of Computing Systems 3
STAT 3850 Foundation of Statistics 3
Science II with lab 4
University Core and/or General Electives 3
Year Three
CSCI 3100 Algorithms 3
Additional Mathematics/Statistics (2000+) 3
Science or engineering 3-4
University Core and/or General Electives 6
CSCI 3200 Programming Languages 3
CSCI 3300 Software Engineering 3
5000-level version of CSCI Systems Elective 3
Additional Mathematics/Statistics (2000+) 3
University Core and/or General Electives 3
Year Four
CSCI 4961 Capstone Project I 2
Critical course:  CSCI 5750 Introduction to Machine Learning 3
University Core and/or General Electives 9
CSCI 4962 Capstone Project II 2
Critical course:  CSCI 5740 Introduction to Artificial Intelligence 3
University Core and/or General Electives 9
Year Five
CSCI 5030 Principles of Software Development 3
Artificial Intelligence Foundations selection 3
Artificial Intelligence Applications selection 3
Artificial Intelligence Elective 3
Critical course:  CSCI 5961 Artificial Intelligence Capstone Project 3
Artificial Intelligence Foundation 3
Artificial Intelligence Application Course  
CSCI 5xxxGeneral Elective a 3
 Total Credits142-143

Waiver replacement for CSCI 5050: Computing and Society.

Introduction to Computer Science

Introduction to Computer Science: Principles
Introduction to Computer Science: Bioinformatics
Introduction to Computer Science: Cybersecurity
Introduction to Computer Science: Game Design
Introduction to Computer Science: Mobile Computing
Introduction to Computer Science: Multimedia
Introduction to Computer Science: Scientific Programming
Introduction to Computer Science: Taming Big Data
Introduction to Computer Science: World Wide Web
Introduction to Computer Science: Special Topics
With permission, a computing-intensive course from another discipline may be substituted. Examples of such courses include:
Biomedical Engineering Computing
Civil Engineering Computing
Foundation of Statistics

Systems Courses

Advanced Operating Systems
Computer Security
Computer Networks
Concurrent and Parallel Programming
Distributed Computing

Program Notes

Thesis Option

A master's thesis is optional. Students completing a thesis should take six credits of Thesis Research (CSCI 5990) in lieu of the AI capstone project and either a foundations or applications selection.

Internship with Industry

Students may apply at most three credits of Internship with Industry (CSCI 5910) toward the degree requirements.