Quick Answer

A computer science degree requires approximately 120 credit hours, with core courses in programming (usually starting with Java, Python, or C++), data structures, algorithms, discrete mathematics, computer architecture, operating systems, and software engineering. Math requirements typically include Calculus I and II, linear algebra, probability and statistics, and discrete math. Most programs assume no prior coding experience, but the learning curve in the first two semesters is steep.

The real question behind this search: can I do this if I have never written code before? The answer is yes — most CS programs are designed to teach you from scratch. But the gap between "designed to teach you from scratch" and "easy for beginners" is enormous. The first two semesters will demand more hours than almost any other major because you are simultaneously learning a new way of thinking (computational logic) and the syntax to express it.

The National Center for Education Statistics shows that computer science is one of the fastest-growing bachelor's degree categories, with awards increasing substantially year over year1. The programs are producing more graduates than ever, which means employers can be selective. A CS degree alone no longer guarantees a top-tier job — your projects, internships, and specific skills within the degree matter more than ever.

For the broader career and ROI analysis, see the computer science degree overview. This page covers exactly what the program requires.

Expert Tip

The single most important habit for CS students is writing code every day outside of assignments. The students who excel are the ones who treat programming like a language — daily practice builds fluency that cramming before deadlines never achieves. Build small personal projects, contribute to open source, or solve problems on coding challenge platforms. The difference between a B student and an A student in CS is often practice volume, not natural ability.

Core Coursework: What Every CS Major Takes

CS curricula follow a progression from fundamentals to systems to applications. The ACM/IEEE Computing Curricula guidelines shape most programs, creating a relatively consistent core across universities.

Foundational courses (first two years):

  • Introduction to Computer Science / Programming I — your first programming language (Java, Python, or C++ depending on the school). Variables, control structures, functions, and basic object-oriented programming.
  • Programming II / Data Structures — arrays, linked lists, stacks, queues, trees, hash tables, and graphs. How to organize and access data efficiently. This course is the gateway to everything else.
  • Discrete Mathematics — logic, proofs, sets, relations, functions, combinatorics, and graph theory. The mathematical foundation of computer science, distinct from calculus.
  • Calculus I and II — limits, derivatives, integrals, and series. Required as mathematics prerequisites even though you may not use calculus directly in most CS courses.
  • Linear Algebra — vectors, matrices, transformations, and eigenvalues. Essential for machine learning, graphics, and scientific computing.
  • Probability and Statistics — statistical reasoning, probability distributions, and data analysis. Increasingly critical given the rise of data science.
120
Credit hours for a standard CS bachelor's degree, with roughly 40-50 in CS courses and 15-20 in mathematics
[1]

Upper-level courses (junior and senior years):

  • Algorithms — algorithm design, analysis, complexity theory (Big-O notation), sorting, searching, dynamic programming, and graph algorithms. Often considered the most theoretically challenging CS course.
  • Computer Architecture/Organization — how computers work at the hardware level. CPU design, memory hierarchy, assembly language, and instruction sets.
  • Operating Systems — process management, memory management, file systems, and concurrency. You learn how software manages hardware resources.
  • Software Engineering — software development lifecycle, version control, testing, agile methodologies, and team-based development. The course most directly connected to industry practices.
  • Databases — relational database design, SQL, normalization, and increasingly NoSQL and distributed databases.
  • Computer Networks — TCP/IP, protocols, network architecture, and security fundamentals.
  • Theory of Computation — formal languages, automata, Turing machines, and computability. The most abstract and mathematical course in the major.
  • Senior Project/Capstone — a substantial team or individual project demonstrating your ability to design, implement, and present a complete software system.

BA vs BS: Which Track Is Right for You?

BS in Computer Science — the standard professional track. More math and science requirements, including physics and additional calculus. This is what most employers and graduate programs expect.

BA in Computer Science — fewer math and science requirements, more room for liberal arts breadth. Good for students who want to combine CS with a non-technical field (design, linguistics, business, music). Some top companies do not distinguish between BA and BS, but research-focused graduate programs prefer the BS.

The BS is the safer choice if you are uncertain about your career direction. The BA makes sense if you have a specific interdisciplinary goal (CS + design for UX, CS + linguistics for NLP, CS + business for product management).

Important

If you are choosing between a BA and BS, check the specific course requirements at your school. At some universities the difference is only 2-3 courses. At others, the BS requires substantially more math and science (physics, Calculus III, differential equations) that the BA does not. The gap varies widely by institution, so compare the actual degree audits rather than assuming.

Common Concentrations and Specializations

Artificial intelligence/machine learning — neural networks, natural language processing, computer vision, and statistical learning. The hottest area in CS and the one most dependent on strong math skills (linear algebra, probability, optimization).

Software engineering — large-scale system design, development methodologies, testing, and DevOps. The most directly career-connected concentration.

Cybersecurity — network security, cryptography, vulnerability analysis, and ethical hacking. Growing demand with dedicated career paths in government and private sector.

Data science — statistical analysis, machine learning, data visualization, and big data systems. Often bridges CS and statistics departments.

Systems and networks — operating systems, distributed computing, cloud infrastructure, and network architecture.

Human-computer interaction (HCI) — user interface design, usability research, and interaction design. Bridges CS and design.

Game development — graphics programming, game engines, and interactive media. Niche but well-defined career path.

Prerequisites and Admission Requirements

Most CS programs do not require prior programming experience for admission. However, some competitive programs at top universities have started requiring AP Computer Science or equivalent coursework.

Math placement is the critical factor. If you enter college ready for Calculus I, you are on track. If you need pre-calculus, your CS sequence may be delayed because some foundational CS courses require concurrent calculus enrollment.

Admission to the CS major at many large universities is now competitive — separate from university admission. This is a recent change driven by surging enrollment. Requirements may include:

  • Minimum GPA in prerequisite CS courses (often 2.7 to 3.0 in intro programming and data structures)
  • Minimum GPA in prerequisite math courses
  • Limited spots based on departmental capacity
  • Application during sophomore year

This competitive admission process is a major change from a decade ago and catches many students off guard. Research your specific school's policy before assuming you can declare CS whenever you want.

Did You Know

The Bureau of Labor Statistics projects that software developer positions will grow about 17% between 2023 and 2033, which is much faster than average for all occupations2. However, the entry-level market has become more competitive as CS enrollment has surged. The students getting the best job offers are those with internship experience, strong personal projects, and specific technical skills beyond the standard curriculum.

Skills You'll Build (and What Employers Actually Value)

Problem decomposition — breaking complex problems into manageable pieces. This is the core intellectual skill of CS and the one that transfers most broadly to other domains.

Programming proficiency — fluency in at least one or two languages, with the ability to learn new languages quickly. Employers care less about which languages you know and more about your ability to write clean, efficient, well-documented code.

System design — understanding how components interact to form complete systems. This skill develops gradually through architecture, operating systems, and capstone projects.

Debugging and testing — finding and fixing errors systematically. The ability to diagnose problems is valued as highly as the ability to write new code.

Collaboration through code — version control (Git), code review, pair programming, and team development practices. Modern software development is almost entirely collaborative.

What Nobody Tells You About CS Requirements

The first two courses are the hardest adjustment period. Introduction to CS and Data Structures represent the steepest learning curve because you are building a new mental framework for problem-solving while simultaneously learning syntax. The drop/fail rate in these courses is high at most universities. If you survive them, the upper-level courses are actually more interesting and often feel more manageable because you have the foundational thinking in place.

The math matters more than you think. Many CS students resent the math requirements, but linear algebra shows up directly in machine learning and graphics, probability underpins AI and security, and discrete math is the theoretical foundation for algorithms and data structures. Students who treat math as a checkbox to clear end up limited in what CS subfields they can pursue.

Office hours are not optional. CS professors and teaching assistants hold office hours for a reason — programming assignments generate specific, technical questions that are difficult to resolve alone. Students who use office hours consistently perform better than those who struggle in isolation.

Imposter syndrome is universal, not a sign you do not belong. Nearly every CS student feels underprepared at some point, especially when classmates seem to grasp concepts faster. The students who "get it" faster often had prior programming experience that the curriculum does not assume. If you are learning to code for the first time, you are exactly the student the program was designed for.

Side projects and internships separate job candidates more than GPA. A CS graduate with a 3.0 GPA, two internships, and an active GitHub portfolio gets more interviews than a 3.8 GPA student with no projects. Start building things outside of class by your sophomore year.

If you are comparing technical majors, see engineering degree requirements for a hardware-oriented alternative and math degree requirements for the pure mathematics path. CS overlaps with both but focuses specifically on software and computation.

FAQ

Do I need to know how to code before starting a CS degree?

No. Most programs start with an introductory course that assumes zero programming experience. However, students who have some exposure (AP Computer Science, self-taught coding, or online courses) have an easier transition in the first semester. If you want to prepare, learn the basics of Python through a free online course before your first semester.

How much math does a computer science degree require?

Typically Calculus I and II, linear algebra, discrete mathematics, and probability/statistics — approximately 15-20 credit hours of math. Some programs also require Calculus III or differential equations. The math is essential, not decorative. Linear algebra is used directly in AI and graphics, discrete math underpins algorithms, and probability is central to data science and machine learning.

Is computer science harder than engineering?

They are different types of difficulty. CS is more abstract and mathematical in its upper-level theory courses. Engineering (particularly mechanical and electrical) involves more physics and physical design. Both require strong problem-solving skills and significant time commitments. CS students spend more time debugging code; engineering students spend more time in physical labs and design studios.

Can I get a CS job without a CS degree?

It is possible through coding bootcamps and self-study, but a degree remains the most reliable path, especially for roles at established companies and for career advancement. The Bureau of Labor Statistics reports that most software development positions require at least a bachelor's degree2. The degree provides theoretical depth (algorithms, systems, architecture) that bootcamps typically skip.

How long does a CS degree take?

Four years is standard (120 credit hours). Students who enter needing pre-calculus or who fail a prerequisite course may need an additional semester. Students who pursue a double major or minor often take 4.5 to 5 years. Summer internships (which are critical for career outcomes) do not typically delay graduation since they replace summer courses, not required semester coursework.

What programming language should I learn first?

Your program will choose for you — most start with Python, Java, or C++. Python is the most beginner-friendly and increasingly the default choice. Java provides a strong foundation in object-oriented programming. C++ is less common as a first language but teaches memory management that Python and Java abstract away. The specific language matters less than learning to think computationally.

More on this degree:

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Footnotes

  1. National Center for Education Statistics. (2024). Digest of Education Statistics: Table 322.10 — Bachelor's degrees conferred by postsecondary institutions, by field of study. NCES. https://nces.ed.gov/programs/digest/d23/tables/dt23_322.10.asp ↩

  2. U.S. Bureau of Labor Statistics. (2025). Occupational Outlook Handbook: Software Developers, Quality Assurance Analysts, and Testers. BLS. https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm ↩ ↩2

  3. U.S. Bureau of Labor Statistics. (2025). Occupational Outlook Handbook: Computer and Information Technology Occupations. BLS. https://www.bls.gov/ooh/computer-and-information-technology/home.htm ↩