Bachelors in Computer Science

4 Years On Campus Bachelors Program

University of Minnesota Twin Cities

Program Overview

The University of Minnesota offers two distinct undergraduate pathways in Computer Science, allowing students to choose a program that aligns with their academic goals and interests:

  • Bachelor of Science (B.S.) in Computer Science
    Offered through the College of Science and Engineering, this program emphasizes technical depth, mathematical rigor, and engineering principles—ideal for students aiming for technically intensive roles or graduate study in computer science.

  • Bachelor of Arts (B.A.) in Computer Science
    Administered by the College of Liberal Arts, this program combines core computer science coursework with the flexibility of a liberal arts education, making it a great option for students interested in interdisciplinary studies or combining computer science with other fields.

 

Core Curriculum (Common to Both Degrees)

Both the B.S. and B.A. programs share a foundational set of computer science courses, including:

  • CSCI 1133: Introduction to Computing and Programming Concepts

  • CSCI 1933: Introduction to Algorithms and Data Structures

  • CSCI 2011: Discrete Structures

  • CSCI 2021: Machine Architecture and Organization

  • CSCI 2033: Computational Linear Algebra

  • CSCI 2041: Advanced Programming Principles

  • CSCI 3081W: Program Design and Development

 

Program-Specific Requirements

B.S. in Computer Science (CSE)

  • Lab Science Courses: Includes Physics I and one additional approved lab science course.

  • Upper-Division Math Course: Advanced coursework to strengthen analytical and quantitative skills.

  • Technical Electives: 23 credits of upper-division electives, including at least 11 credits in computer science; the rest may come from approved technical areas outside of CSCI.

B.A. in Computer Science (CLA)

  • Second Language Proficiency: Completion of four semesters of a second language or equivalent demonstrated proficiency.

  • Upper-Division CSCI Electives: At least 8 credits from advanced (4000–5000 level) CSCI courses.

  • CLA Additional Requirements: 18 credits of upper-division courses outside of computer science. One of these, STAT 3021 (a statistics course), counts toward the requirement.

Both degree paths offer students flexibility, strong academic support, and career readiness. Whether you’re aiming to build advanced technical expertise or pursue a broader interdisciplinary approach, the University of Minnesota has a pathway to match your aspirations.

 

Experiential Learning (Research, Projects, Internships etc.)

The University of Minnesota emphasizes hands-on learning through various avenues:​

  • Undergraduate Research: Students have opportunities to engage in research projects, collaborating with faculty on cutting-edge topics.​

  • Internships and Co-ops: The university's strong ties with industry partners facilitate internships and cooperative education experiences, providing practical exposure and professional development.​

  • Student Organizations: Active participation in computing clubs and organizations fosters collaboration, networking, and leadership skills.​

Progression & Future Opportunities

Graduates from both the B.S. and B.A. programs are well-prepared for diverse career paths in technology, research, and academia. The comprehensive curriculum and emphasis on both theoretical and practical skills ensure that students are equipped to tackle complex challenges in the field.​

By integrating a rigorous curriculum with experiential learning opportunities, the University of Minnesota Twin Cities' Computer Science programs aim to develop well-rounded professionals capable of adapting to the rapidly evolving tech landscape.​

Program Key Stats

$41,238
$ 55
Aug Intake : RD 1st Jan EA/ED 1st Nov


77 %
No
Yes

Eligibility Criteria

ABB - AAB
3.0 - 3
32 - 36
80 - 85

1310 - 1480
27 - 31
6.5
79

Additional Information & Requirements

Career Options

  • Career Pathway:   Software Engineering: Developer
  • Full-Stack Engineer
  • Mobile App Developer
  •   AI & Data Science: Machine Learning Engineer
  • Data Scientist
  • AI Researcher
  •   Cybersecurity & Cloud: Cybersecurity Analyst
  • Cloud Engineer
  • Ethical Hacker
  •   Finance & Business Tech: Quantitative Analyst
  • Fintech Developer
  • Blockchain Specialist
  •   Product & Management: Product Manager
  • Technical Program Manager
  •   Entrepreneurship: Startups and innovation
  •   Further Studies: MS or PhD in AI
  • cybersecurity
  • or data science for research roles
  • MBA for leadership and management positions
  •   Long-Term Growth: Engineering: Software Engineer → Tech Lead → CTO
  •   Data & AI: Data Scientist → Head of AI
  • Management: Product Manager → VP of Engineering

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