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

¶¶Òõpro'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.Ìý

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.Ìý

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.Ìý

Students who drop belowÌýthat GPA while in the accelerated program will be placed on a one-semester probationary period before beingÌýdismissed from the accelerated program.Ìý

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

Ìý

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

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
MATHÌý1510 Calculus I 4
University Core and/or General Electives 9
ÌýCredits16
Spring
CSCIÌý1300 Introduction to Object-Oriented Programming 4
MATHÌý1510 Calculus I 4
University Core and/or General Electives 6
ÌýCredits14
Year Two
Fall
CSCIÌý2100 Data Structures 4
CSCIÌý2500 Computer Organization and Systems 3
MATHÌý1660 Discrete Mathematics 3
Science I with lab 4
PHILÌý3050X Computer Ethics 3
ÌýCredits17
Spring
CSCIÌý2300 Object-Oriented Software Design 3
CSCIÌý2510 Principles of Computing Systems 3
STATÌý3850 Foundation of Statistics 3
Science II with lab 4
University Core and/or General Electives 3
ÌýCredits16
Year Three
Fall
CSCIÌý3100 Algorithms 3
Additional Mathematics/Statistics (2000+) 3
Science or engineering 3-4
University Core and/or General Electives 6
ÌýCredits15-16
Spring
CSCIÌý3200 Programming Languages 3
CSCIÌý3300 Software Engineering 3
5000-level version of CSCI Systems Elective 3
Additional Mathematics/Statistics (2000+) 3
University Core and/or General Electives 3
ÌýCredits15
Year Four
Fall
CSCIÌý4961 Capstone Project I 2
CSCIÌý5750 Introduction to Machine Learning 3
University Core and/or General Electives 9
ÌýCredits14
Spring
CSCIÌý4962 Capstone Project II 2
CSCIÌý5740 Introduction to Artificial Intelligence 3
University Core and/or General Electives 9
ÌýCredits14
Year Five
Fall
CSCIÌý5030 Principles of Software Development 3
Artificial Intelligence Foundations selection 3
Artificial Intelligence Applications selection 3
Artificial Intelligence Elective 3
ÌýCredits12
Spring
CSCIÌý5961 Artificial Intelligence Capstone Project 3
Artificial Intelligence Foundation 3
Or Ìý
Artificial Intelligence Application Course Ìý
CSCI 5xxxGeneral Elective a 3
ÌýCredits9
ÌýTotal Credits142-143
a

Waiver replacement for CSCI 5050: Computing and Society.

Introduction to Computer Science

CSCIÌý1010
Introduction to Computer Science: Principles
CSCIÌý1020
Introduction to Computer Science: Bioinformatics
CSCIÌý1025
Introduction to Computer Science: Cybersecurity
CSCIÌý1030
Introduction to Computer Science: Game Design
CSCIÌý1040
Introduction to Computer Science: Mobile Computing
CSCIÌý1050
Introduction to Computer Science: Multimedia
CSCIÌý1060
Introduction to Computer Science: Scientific Programming
CSCIÌý1070
Introduction to Computer Science: Taming Big Data
CSCIÌý1080
Introduction to Computer Science: World Wide Web
CSCIÌý1090
Introduction to Computer Science: Special Topics
With permission, a computing-intensive course from another discipline may be substituted. Examples of such courses include:
BMEÌý2000
Biomedical Engineering Computing
CVNGÌý1500
Civil Engineering Computing
STATÌý3850
Foundation of Statistics

Systems Courses

CSCIÌý4500
Advanced Operating Systems
CSCIÌý4530
Computer Security
CSCIÌý4550
Computer Networks
CSCIÌý4610
Concurrent and Parallel Programming
CSCIÌý4620
Distributed Computing

Program Notes

Thesis Option

A master's thesis is optional. Students completing a thesis should take six credits ofÌýThesis Research (CSCIÌý5990) 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 (CSCIÌý5910)Ìýtoward the degree requirements.