University of South Carolina

How this program compares

Benchmark this program against our national recognition pages and use the key guides below to evaluate ROI, admissions difficulty, and outcomes.

Admission Snapshot

Typical admitted student: The bulletin describes competitive admission, normally expecting a BS in CS, CE, or a related field with coursework in algorithms, data structures, systems, discrete math, and calculus; conditional admission may require completing missing prerequisites as part of the degree. February 1 and October 1 material deadlines have been used for fall/summer and spring starts—confirm annually.

About This Program

Columbia’s MSCS is a traditional computer science master’s with explicit thesis and non-thesis rails; AI specialization is not a separate diploma title but emerges through choice of electives, certificates, and faculty research in artificial intelligence.

Career Outcomes

Thesis or non-thesis MSCS with rigorous core CS and electives suitable for AI/ML depth through graduate CSCE coursework and related research institutes.

• 1. Software Engineer
• 2. Machine Learning Engineer
• 3. Systems / Infrastructure Engineer
• 4. PhD-bound researcher

What You'll Learn

• Satisfy a graduate CS core in architecture, languages, algorithms, and professional seminar expectations.
• Deepen in ML/AI topics via CSCE electives numbered appropriately for the chosen option.
• Complete either thesis research with public defense or a non-thesis exam pathway per bulletin rules.
• Collaborate with AI-focused research centers if admitted to related labs.

Curriculum Highlights

The University of South Carolina academic bulletin for the M.S. in Computer Science specifies 30 credit hours beyond the bachelor’s, with 10 hours of core courses (computer architecture, compiler construction, analysis of algorithms, and a computing seminar) and 20 hours of electives (up to six hours of non-CSCE courses; limits apply to certain independent-study courses). Students choose thesis or non-thesis options: thesis students may apply six thesis credits toward electives with additional 700-level CSCE credit and defense requirements; non-thesis students complete at least 15 hours of 700-level CSCE coursework and pass a written comprehensive exam. Artificial intelligence and machine learning topics are typically pursued within electives and research groups such as the AI Institute hub linked from the department.

Top Employers

Graduates recruit across Southeast technology, finance, and federal contractor employers; see departmental placement resources for audited statistics.

Admissions

The bulletin describes competitive admission, normally expecting a BS in CS, CE, or a related field with coursework in algorithms, data structures, systems, discrete math, and calculus; conditional admission may require completing missing prerequisites as part of the degree. February 1 and October 1 material deadlines have been used for fall/summer and spring starts—confirm annually.

Application Materials

• Statement of purpose: Typically required
• Letters of recommendation: At least two cited in bulletin
• Resume: Confirm
• Transcripts: Official transcripts required
• English proficiency for international applicants per Graduate School

Academic Requirements

• Degree Required: Bachelor's (CS/CE-related typical)
• GRE/GMAT: Verify department policy each cycle
• TOEFL/IELTS: Per Graduate School requirements