130 List of Common Computer Science Classes

This page is for those who are interested in Computer Science and will like to know the classes they will take to become a Computer Scientist. Computer science, a multi-billion dollar industry is booming and qualified computer science professionals are in high demand.

Every institution offering Computer Science have their own curriculum. To know all Computer Science major classes means you will visit each of these institutions and take a look at their course outlines which is impossible.

What I have listed on this page are Computer Science classes you may attend and there is no guarantee that all the listed Computer Science classes will be available in the school you have chosen.

Nevertheless, you may likely attend 80% of Computer Science major classes listed here. Computer Science is the study of the theory, experimentation, and engineering that form the basis for the design and use of computer systems. It can also be defined as the study of automating algorithmic processes.

These are Computer Science Classes

  • Algorithmic Game Theory
  • Algorithms and Data Structures for Applications
  • Analysis of Algorithms
  • Applications of Parallel Computers
  • Applied Logic
  • Applied Machine Learning
  • Artificial Intelligence
  • Assembly Language Programming
  • Autonomous Mobile Robots
  • Bayesian Machine Learning
  • Blockchains, Cryptocurrencies, and Smart Contracts
  • Business Programming
  • C++ Programming
  • Category Theory for Computer Scientists
  • Certified Software Systems
  • Choices and Consequences in Computing
  • Cloud Computing
  • Compiler Construction
  • Compiling Techniques
  • Computation for Content Creation
  • Computational Genetics and Genomics
  • Computational Linguistics
  • Computational Mathematics for Computer Science
  • Computer Applications
  • Computer Architecture and Organization
  • Computer Centre Management
  • Computer Game Architecture
  • Computer Graphics and Vision
  • Computer Hardware
  • Computer Networks a Decade
  • Operating Systems
  • Computer Science Colloquium
  • Computer Simulations
  • Computer System Organization and Programming
  • Computer Vision
  • Computing in the Arts
  • Crowdsourcing and Human Computation
  • Cryptocurrencies and Smart Contracts
  • Cryptography
  • Data Science
  • Data Structures and Functional Programming
  • Data-Driven Web Applications
  • Data-Sparse Matrix Computations
  • Database Systems
  • Decision Theory
  • Deep Learning
  • Digital Computer Logic Design
  • Discrete Structures
  • Distributed Computing Principles
  • Distributed Consensus and Blockchains
  • Distributed Systems
  • Elementary Data Processing
  • Embedded Systems
  • Excursions in Computational Sustainability
  • Expert Systems
  • File Management
  • Formal Languages and Automata Theory
  • Formal Verification
  • Foundations of Artificial Intelligence
  • Foundations of Reinforcement Learning
  • Freshmen and Nontechnical Team Projects
  • Fundamental Programming Concepts
  • HCI and Design
  • Human Robot Interaction
  • Industrial Training
  • Inference and Decision Making
  • Information Management Systems
  • Information Theory & Computer Communication Systems
  • Interactive Computer Graphics
  • International Research Internship
  • Introduction to Cognitive Science
  • Introduction to Compilers
  • Introduction to Computational Complexity
  • Introduction to Computer Electronics
  • Introduction to Computer Game Architecture
  • Introduction to Computer Graphics
  • Introduction to Computer Networks
  • Introduction to Computer Science
  • Introduction to Computer Vision
  • Introduction to Computing Using MATLAB
  • Introduction to Computing Using Python
  • Introduction to Constructive Type Theory
  • Introduction to Cryptography
  • Introduction to Database Systems
  • Introduction to Kleene Algebra
  • Introduction to Machine Learning
  • Introduction to Operating System
  • Introduction to Reinforcement Learning
  • Introduction to Theory of Computing
  • Introductory Design and Programming for the Web
  • Language and Information
  • Language-Based Security
  • Logics of Programs Machine Learning for Data Science
  • Mathematical Foundations for the Information Age
  • Matrix Computations
  • Microcomputers and Microprocessors
  • Natural Language Processing
  • Network Programming Languages
  • Networked and Distributed Systems
  • Networks IIMarket Design
  • Numerical Analysis and Differential Equations
  • Numerical Methods for Data Science
  • Object-Oriented Programming and Data Structures
  • Open-Source Software Engineering
  • Operating Systems
  • Optimization Methods
  • Privacy in the Digital Age
  • Programming Languages and Logics
  • Programming and Algorithms
  • Reasoning about Knowledge
  • Reasoning about Uncertainty
  • Recognizing and Modeling the World
  • Runtime Verification
  • Scientific Programming
  • Security Protocols and Privacy
  • Security and Privacy Technologies
  • Selected Topics in Computer Science
  • Signal Processing
  • Software Engineering
  • Software Testing
  • Startup Systems Design and Engineering
  • Structured Programming
  • Survey of Programming Languages
  • System Security
  • Systems Analysis
  • Systems Principles
  • Systems Programming
  • Systems Software and Formal Methods
  • Teaching Experience in Computer Science
  • The Great Instruction Set Architectures
  • The Structure of Information Networks
  • Theoretical Foundations of Machine Learning
    Theory of Computation
  • UNIX Tools and Scripting
  • Urban Analytics
  • Virtual and Augmented Reality

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