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 programs:
Admission Requirements
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.
Program Requirements
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.
Students can take up to 15 credits of graduate coursework that will count for both the B.S. and M.S. Courses and credits included are below.
| Undergraduate Program Requirement | Met by Graduate Course |
|---|---|
| 3-credit Systems Elective at the 3000-level | Systems Elective at the 5000-level |
| CS AI/ML requirement | CSCI 5750 |
| CS Elective at the 3000-level or above | CSCI 5740 |
| 6 credits of University Electives | 6 credits of AI Electives |
This roadmap is just one example of a semester-by-semester plan of study for this program. There are other plans students can and do take. The plan of study for each particular student is established in consultation with each student’s academic advisor; this roadmap does not replace academic advising appointments.
Roadmap notes:
- This Roadmap assumes full-time enrollment unless otherwise noted.
- Courses/Milestones marked with an “!” are critical and must be completed in the semester listed in the Roadmap to ensure a timely graduation.
- Course availability and sequencing are subject to change.
| Year One | ||
|---|---|---|
| Fall | Credits | |
| CSCI 10xx | Introduction to Computer Science | 3 |
| MATH 1510 | Calculus I | 4 |
| University Core and/or General Electives | 9 | |
| Credits | 16 | |
| Spring | ||
| CSCI 1300 | Introduction to Object-Oriented Programming | 4 |
| MATH 1510 | Calculus I | 4 |
| University Core and/or General Electives | 6 | |
| Credits | 14 | |
| Year Two | ||
| Fall | ||
| 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 |
| Credits | 17 | |
| Spring | ||
| 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 | |
| Credits | 16 | |
| Year Three | ||
| Fall | ||
| CSCI 3100 | Algorithms | 3 |
| Additional Mathematics/Statistics (2000+) | 3 | |
| Science or engineering | 3-4 | |
| University Core and/or General Electives | 6 | |
| Credits | 15-16 | |
| Spring | ||
| 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 | |
| Credits | 15 | |
| Year Four | ||
| Fall | ||
| CSCI 4961 | Capstone Project I | 2 |
| CSCI 5750 | Introduction to Machine Learning | 3 |
| University Core and/or General Electives | 6 | |
| Graduate AI Elective | 3 | |
| Credits | 14 | |
| Spring | ||
| CSCI 4962 | Capstone Project II | 2 |
| CSCI 5740 | Introduction to Artificial Intelligence | 3 |
| University Core and/or General Electives | 6 | |
| Graduate AI Elective | 3 | |
| Credits | 14 | |
| Year Five | ||
| Fall | ||
| CSCI 5030 | Principles of Software Development | 3 |
| Artificial Intelligence Principles course | 3 | |
| Artificial Intelligence Applications course | 3 | |
| Credits | 9 | |
| Spring | ||
| CSCI 5961 | Artificial Intelligence Capstone Project | 3 |
| CSCI 5xxx | General Elective a | 3 |
| Credits | 6 | |
| Total Credits | 136-137 | |
- a
Waiver replacement for CSCI 5050: Computing and Society.
Introduction to Computer Science
| Code | Title | Credits |
|---|---|---|
CSCI 1010 | Introduction to Computer Science: Principles | |
CSCI 1020 | Introduction to Computer Science: Bioinformatics | |
CSCI 1025 | Introduction to Computer Science: Cybersecurity | |
CSCI 1030 | Introduction to Computer Science: Game Design | |
CSCI 1040 | Introduction to Computer Science: Mobile Computing | |
CSCI 1050 | Introduction to Computer Science: Multimedia | |
CSCI 1060 | Introduction to Computer Science: Scientific Programming | |
CSCI 1070 | Introduction to Computer Science: Taming Big Data | |
CSCI 1080 | Introduction to Computer Science: World Wide Web | |
CSCI 1090 | Introduction to Computer Science: Special Topics | |
| With permission, a computing-intensive course from another discipline may be substituted as long as it is not already fulfilling another requirement. Examples of such courses include: | ||
BME 2000 | Biomedical Engineering Computing | |
CVNG 1500 | Civil Engineering Computing | |
STAT 3850 | Foundation of Statistics | |
Systems Courses
| Code | Title | Credits |
|---|---|---|
CSCI 4500 | Operating Systems | |
CSCI 4530 | Computer Security | |
CSCI 4550 | Computer Networks | |
CSCI 4610 | Concurrent and Parallel Programming | |
CSCI 4620 | 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.
Students at Saint Louis University-Madrid can complete the first three or four years of their accelerated program in Madrid and then finish their M.S. at SLU-St. Louis.
Depending on the format of their M.S., students will transition before their fourth or fifth year of study. Options are listed below.
Option A: 3+2 Pathway (Thesis)
- Years 1-3: Students complete foundational coursework in Madrid.
- Years 4-5: Final year of B.S. and M.S. coursework/research completed in St. Louis. Students begin capstone research work in St. Louis in year four, which transitions into a formal M.S. thesis project and completion in year five.
Option B: 4+1 Research-Linked Pathway (Thesis)
- Years 1-4: Full B.S. completion in Madrid, including a senior capstone research project initiated under the guidance of Madrid faculty, in collaboration with St. Louis faculty. Students also complete the first 15 credits of M.S.-level coursework (5xxx level; potentially through online courses when available from STL campus).
- Year 5: Students matriculate fully into the M.S. program to continue and complete their research thesis and the remaining 15 credits of M.S. coursework in St. Louis.
Option C: 4+1 Coursework-Based Pathway (Nonthesis)
- Years 1-4: Students complete B.S. in Madrid and the first 15 credits of their M.S. coursework (5xxx level; potentially through online courses when available from STL campus).
- Year 5: Remaining 15 credits of M.S. coursework is completed in St. Louis.
For more information about computer science programs, please call 314-977-6667 or email cs@slu.edu.