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

This program allows a student to complete, in an accelerated fashion, both the Bachelor of Arts in Computer Science and the Master of Science in Artificial Intelligence at Saint Louis University.

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

Computer Science, B.A.

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
FallCredits
CSCI 10xxIntroduction to Computer Science 3
MATH 1660 Discrete Mathematics 3
University Core and/or General Electives 9
 Credits15
Spring
CSCI 1300 Introduction to Object-Oriented Programming 4
MATH 1510 Calculus I 4
University Core and/or General Electives 6
 Credits14
Year Two
Fall
CSCI 2100 Data Structures 4
CSCI 2500 Computer Organization and Systems 3
MATH 1520 Calculus II 4
University Core and/or General Electives 6
 Credits17
Spring
CSCI 2300 Object-Oriented Software Design 3
CSCI 2510 Principles of Computing Systems 3
MATH 3850 Foundation of Statistics 3
University Core and/or General Electives 6
 Credits15
Year Three
Fall
CSCI 3100 Algorithms 3
University Core and/or General Electives 12
 Credits15
Spring
5000-level version of CSCI Systems Elective 3
PHIL 3050X Computer Ethics 3
University Core and/or General Electives 9
 Credits15
Year Four
Fall
CSCI 4961 Capstone Project I 2
Critical course:  CSCI 5750 Introduction to Machine Learning 3
University Core and/or General Electives 9
 Credits14
Spring
CSCI 4962 Capstone Project II 2
Critical course:  CSCI 5740 Introduction to Artificial Intelligence 3
University Core and/or General Electives 9
 Credits14
Year Five
Fall
CSCI 5030 Principles of Software Development 3
Artificial Intelligence Foundation selection 3
Artificial Intelligence Applications selection 3
Artificial Intelligence Elective 3
 Credits12
Spring
Critical course:  CSCI 5961 Artificial Intelligence Capstone Project 3
Artificial Intelligence Foundations selection 3
Or  
Application Course  
CSCI 5xxxGeneral Elective a 3
 Credits9
 Total Credits140
a

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 

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

Program Notes

CSCI 5050 Computing and Society (3 cr) requirement will be waived for students who took Computer Ethics as an
undergraduate; these hours would become an additional graduate elective.

Thesis Option

A master's thesis is optional. Students completing a thesis should take six credits of Thesis Research Thesis Research (CSCI 5990) as part of the elective requirements.

Internship with Industry

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

Closely Related Disciplines

With approval, students may include up to six credits of elective graduate coursework in closely related disciplines (e.g. mathematics and statistics, bioinformatics and computational biology, electrical and computer engineering).