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 ¶¶Òõpro.
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.
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.
Year One | ||
---|---|---|
Fall | Credits | |
CSCI 10xx | Introduction to Computer Science †| 3 |
MATHÌý1660 | Discrete Mathematics | 3 |
University Core and/or General Electives | 9 | |
Ìý | Credits | 15 |
Spring | ||
CSCIÌý1300 | Introduction to Object-Oriented Programming | 4 |
MATHÌý1510 | Calculus I | 4 |
University Core and/or General Electives | 6 | |
Ìý | Credits | 14 |
Year Two | ||
Fall | ||
CSCIÌý2100 | Data Structures | 4 |
CSCIÌý2500 | Computer Organization and Systems | 3 |
MATHÌý1520 | Calculus II | 4 |
University Core and/or General Electives | 6 | |
Ìý | Credits | 17 |
Spring | ||
CSCIÌý2300 | Object-Oriented Software Design | 3 |
CSCIÌý2510 | Principles of Computing Systems | 3 |
MATHÌý3850 | Foundation of Statistics | 3 |
University Core and/or General Electives | 6 | |
Ìý | Credits | 15 |
Year Three | ||
Fall | ||
CSCIÌý3100 | Algorithms | 3 |
University Core and/or General Electives | 12 | |
Ìý | Credits | 15 |
Spring | ||
5000-level version of CSCI Systems Elective | 3 | |
PHILÌý3050X | Computer Ethics | 3 |
University Core and/or General Electives | 9 | |
Ìý | Credits | 15 |
Year Four | ||
Fall | ||
CSCIÌý4961 | Capstone Project I | 2 |
CSCIÌý5750 | Introduction to Machine Learning | 3 |
University Core and/or General Electives | 9 | |
Ìý | Credits | 14 |
Spring | ||
CSCIÌý4962 | Capstone Project II | 2 |
CSCIÌý5740 | Introduction to Artificial Intelligence | 3 |
University Core and/or General Electives | 9 | |
Ìý | Credits | 14 |
Year Five | ||
Fall | ||
CSCIÌý5030 | Principles of Software Development | 3 |
Artificial Intelligence Foundation selection | 3 | |
Artificial Intelligence Applications selection | 3 | |
Artificial Intelligence Elective | 3 | |
Ìý | Credits | 12 |
Spring | ||
CSCIÌý5961 | Artificial Intelligence Capstone Project | 3 |
Artificial Intelligence Foundations selection | 3 | |
Or | Ìý | |
Application Course | Ìý | |
CSCI 5xxx | General Elective a | 3 |
Ìý | Credits | 9 |
Ìý | Total Credits | 140 |
- a
Waiver replacement for CSCI 5050: Computing and Society
Introduction to Computer Science
Code | Title | Credits |
---|---|---|
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 |
SystemsÌý
Code | Title | Credits |
---|---|---|
CSCIÌý4500 | Advanced Operating Systems | |
CSCIÌý4530 | Computer Security | |
CSCIÌý4550 | Computer Networks | |
CSCIÌý4610 | Concurrent and Parallel Programming | |
CSCIÌý4620 | Distributed Computing |
Program Notes
CSCIÌý5050 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 CSCIÌý5990 Thesis Research (0-6 cr) as part of the elective requirements.
Internship with Industry
Students may apply at most three credits of CSCIÌý5910 Internship with Industry (1-3 cr)Ìýtoward 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).