11+ Best Computer Science Courses Online (Top Picks Of 2024)

Well, when you buy courses using links on our website, we may earn a tiny commission — at no extra cost to you. None Whatsoever! This helps us keep curating helpful content 😊

Computer Science refers to the study of computer technology, which includes both hardware and software. Students can learn skills that are necessary across almost every industry in our tech-driven world in this diverse and exciting field.

A computer programmer must possess a number of hard skills, including an understanding of data structures, SQL, web development, cloud computing, OOPs languages, etc. 

There are many online computer science courses available to improve one’s skills and succeed in the field.

The following are the best online courses for beginners to learn the fundamentals of computer science. They are designed by experts and are considered reliable by thousands of students who have enrolled in these courses on platforms such as Udemy, Coursera, Udacity, Futurelearn, and edX.

11 Best Computer Science Courses

If you are in a bit of a hurry, then here is a quick overview of the top 11 computer science courses that you can refer to.

Sr. NoBest Computer Science CoursesPlatformRating
1.Introduction to Computer Science and Programming using PythonedX4.8/5
2.Computer Science 101: Master the Theory behind Programming Udemy4.8/5
3.Introduction to Computer Science and Programming Specialization Coursera4.7/5
4.Computer Science 101edX4.8/5
5.Intro to Theoretical Computer Science Udacity4.9/5
6.CS50’s Computer Science for Business Professionals edX4.6/5
7.Mathematical Thinking in Computer Science Coursera4.7/5
8.Problem-Solving by Computational ThinkingCoursera4.5/5
9.How Computers WorkCoursera4.6/5
10.Mathematics for Computer Science: Essential Skills FutureLearn4.7/5
11. Machine LearningCoursera4.8/5

1. Python Programming and Computer Science Introduction (edX)


The Python Programming and Computer Science Introduction course from MIT is my top pick for the best computer science course and is offered on edX.

This course gives students background information on the many applications of computation while putting more of an emphasis on breadth than depth.

Course indicates Python could be viewed as a positive or a negative depending on your objectives.

You will gain knowledge about what computers are, how they function, and their limitations in addition to a brief overview of computation and computer programming.

In addition, you’ll learn about functions and how they relate to abstraction, recursion, and other key ideas in computer science that are used in problem-solving.

You also get covered with a thorough understanding of the various ways that information can be represented in Python by the end of this course. 

You can complete this course without any prior knowledge, with the exception of high school maths.

Python Programming Course
Price$75 for verified track
Duration9 weeks (14-16 hours per week)
InstructorJohn Guttag, Ana Bell, Eric Grimson, 

Key Highlights:

  • Get to understand the notion of computation.
  • Solve the basic and simple algorithms.
  • Learn a python programming language.
  • Get covered with the informal introduction to algorithmic complexity.
  • Learn data structures, testing, and debugging.
  • Learn with graded assignments and exams.

2. Computer Science 101: Master the Theory behind Programming (Udemy)


This 10-hour course, which is among the best on Udemy for learning computer science for beginners, will instruct you in the fundamentals of computer science, data structures, and methodologies in a way that is entertaining and engaging.

Analyzing algorithms, clusters, and the way data is stored comes after learning the binary system. The course then progresses to nodes and their significance, linked lists, stacks implemented, different storing algorithms, trees, binary search trees, and much more.

With over 16,000 students already enrolled, this is one of the most liked computer science courses on Udemy. 

This course is specifically made to cover each subject in a variety of simple-to-understand ways.

Computer Science
LevelBeginner to Intermediate
Duration11 hours
InstructorKurt Anderson

Key Highlights:

  • Be able to compare a wide range of algorithms.
  • Learn the complete fundamentals of computer science theory.
  • Get covered with the different data structures and algorithms.
  • Understand the fundamental theories of algorithm analysis.
  • Learn the core sorting algorithms.

3. Introduction to Computer Science and Programming Specialization (Coursera)


This course is the most useful one for explaining the fundamentals of computer science and the mathematics underlying them.

It offers you a comprehensive review of both problem-solving and the widely applicable JavaScript language.

The course is composed of three parts: How Computers Work, Mathematics for Computer Science, and Introduction to Computer Programming.

JavaScript is used to create 2D interactive and graphical programs in the course’s introduction to computer programming.

The next step is to learn the basics of how computers operate and how to apply those principles to any software-based system. Finally, you will gain an understanding of the mathematics that computer science relies on.

In terms of social proof, more than 36% of those who took the course went on to launch a new career after finishing the specialization. and over 25% received a pay raise or a promotion.

Programming Specialization
InstitutionUniversity of London
Duration5 hours/ week (4 months)
InstructorDr. Edward Anstead, Dr. Simon Katan, Prof Macro Gillies, Dr. Matthew Yee-king

Key Highlights:

  • Create interactive browser-based programs with 2D graphics by learning the Javascript language.
  • Understand and develop mental models to describe the workings of a range of computer systems.
  • Learn the number bases thoroughly, practice mathematical operations, work with sequence data and series, and plot graphs.
  • Transform the numbers between number bases and perform arithmetic in number bases.

4. Computer Science 101 (edX)


This course, in contrast to the others, emphasizes the magic of computers by showing how they function by upholding a few fairly basic patterns.

You will learn to recognize these patterns through this course. You will undoubtedly gain an understanding of how computers operate and what their limitations are.

Additionally, this course introduces you to networking and other important CS topics. You will learn how to use concepts from programs, such as loops, variables, and interactions.

Additionally, it will cover interpreters, compilers, and both high-level and low-level languages.

You will comprehend the various components that make up a computer and the various kinds of networks by the end of this course. A wide range of other subjects, including databases, cybersecurity, analogue, spreadsheet applications, and digital data, will be briefly covered.

Computer Science
InstitutionStandford online
Price$199 for the verified track.Audit track – free
LevelBasic to intermediate
Duration6 weeks (4-6 hours per week)
InstructorNick Parlante

Key Highlights:

  • Learn all the basics of computers and coding.
  • Understand how the computer hardware works. (chips, CPU, memory, disk)
  • Get covered with the computer codes: loops and logic.
  • Learn how structured data works and how the software works.
  • Understand the difference between analogue and digital.
  • Get full-time support from the edX
  • Learn with graded assignments and exams.

5. Intro to Theoretical Computer Science (Udacity)


The two main areas of theoretical computer science are computability and complexity theory, which are the focus of this course. You will learn about a range of practical issues in this course, from telecommunications to finance.

You will comprehend what makes an issue difficult as well as the importance of comprehending these issues. This will prepare you to comprehend NP-completeness, why a problem is difficult to resolve and how to demonstrate it.

The course also covers how to approach a problem after demonstrating its difficulty.

You’ll be able to explain and apply these methods in real-world settings once this course is over. You will then proceed to challenge that, in theory. 

You must have a fundamental understanding of programming and algorithmic thinking in order to join this course. Otherwise, there is no prerequisite knowledge of theoretical computer science.

Intro to Theoretical Computer Science
Duration2 months approx
InstructorSebastian Wernicke, Sean Bennet, Sarah Norell

Key Highlights:

  • The course teaches you the basic concepts in theoretical computer science. 
  • Get training from industry experts with various interactive quizzes.
  • Get covered with a complete introduction to tough problems and their analysis.
  • Learn smart techniques that can solve problems that are theoretically impossible to solve.
  • Solve the most challenging algorithmic problems and apply the powerful tools to solve them in practice.

6. CS50’s Computer Science for Business Professionals (edX)


The introduction to computer science in CS50 is specially tailored for entrepreneurs, product managers, and industry leaders.

This particular course adopts a bottom-up methodology that emphasizes mastery of fundamental ideas and implementation specifics.

You will master the top-level concepts and related design choices through these video lessons.

Additionally, you will gain knowledge of computational thinking, computer languages, web development, internet technologies, and technology stacks.

You will know how to utilize programming languages, technology stacks, web development, and various internet technologies once you have finished the course.

Computer Science for Business Professionals
InstitutionHarvard education
Duration6 weeks (2-6 hours per week)
InstructorDavid J. Malan

Key Highlights:

  • Gain computational thinking.
  • Learn various programming languages.
  • Get covered with internet technologies.
  • Understand the technology stacks and web development.
  • Learn cloud computing to make technological decisions.

7. Mathematical Thinking in Computer Science (Coursera)


You will learn the critical mathematical thinking skills required in all areas of computer science in this course. Students learn about the crucial tools used in discrete mathematics, such as induction, recursion, logic, invariants, examples, and optimality, in the free online computer science course.

After that, you will use the tools you have learned about to respond to questions about programming. Additionally, you will learn several techniques for demonstrating both the existence of an object and its superiority over all competing projects.

You will practice difficult and seemingly illogical but logical aspects of mathematical logic as well as learn the fundamentals of it. This will make your code more readable and precise, and it will also make it easier for you to express your ideas clearly and concisely.

 Mathematical Thinking in Computer Science
InstitutionUC San Diego
Duration42 hours approx
InstructorAlexander S. Kulikov, Michel Levin

Key Highlights:

  • Learn to make convincing arguments and mathematical thinking to solve them.
  • Learn to understand the proofs and how to discover them on your own.
  • Understand the various techniques for showing that an object exists and that an object is optimal among all the other objects.
  • Learn with interactive videos and puzzles.
  • Learn how to define objects, prove ideas, and implement programs using the two potent techniques of recursion and induction.

8. Problem-Solving by Computational Thinking (Coursera)


You’ll discover the foundations of computational thinking in this course, as well as how computer scientists create and evaluate algorithms and use Python to implement solutions on a computer.

You will meet people in this course who use computational thinking to tackle problems from a wide range of industries. You will interact with a special group of analytical thinkers and be pushed to think about how computational thinking can benefit society.

You will be able to create an algorithm and communicate it to the computer by creating a straightforward Python program by the end of the course.

You will learn a variety of skills, including computation, simple algorithms, Python programming, and problem-solving.

Computational Thinking
InstitutionUniversity of Pennsylvania
Duration18 hours approx
InstructorSusan Davidson

Key Highlights:

  • The course explains the complete pillars of Computational thinking.
  • Evaluate an algorithm and analyze how its performance gets affected by the size of the input.
  • Get covered with the basic operations of modern computers.
  • Understand the applied computational thinking using python.
  • Get introduced to python programming and its core features.

9. How Computers Work (Coursera)


This course covers a wide range of topics, including computing devices, abstract thought, modifiability, computer systems, and connectivity.

The first topic covered in the course is an abstraction, which is the practice of highlighting key details while omitting unnecessary ones. Computer science, both at the software and hardware levels, is one of many disciplines that heavily rely on abstraction.

Moving forward, you’ll discover how networks and communication protocols enable computers to communicate with one another over the Internet. Additionally, you’ll discover the various security risks that users and computers are exposed to as well as how to safeguard your personal information.

Finally, you’ll look at fundamental web development. Applying your newly acquired understanding of state, abstraction, and modularity, you’ll be able to comprehend websites’ operations with ease.

The course is totally suitable for someone who wants to lay a strong foundation for further study in computer science as it is for someone who is merely interested in computers and wants to explore some important CS topics but is not necessarily looking for a deep dive.

To sign up for this course, you don’t need any prior computer science knowledge.

How Computers Work
InstitutionUniversity of London
Duration10 hours approx
InstructorProf. Marco Gillies

Key Highlights:

  • Learn about the computer science concepts of state and modularity.
  • Understand how computers communicate with each other over networks.
  • Get covered with some of the security threats that the internet entails and how they can be avoided.
  • Apply the computer science concepts that you have learned in the course to understand how modern websites work.

10. Mathematics for Computer Science: Essential Skills (FutureLearn)


You’ll discover how to formalize and operate on “sets”, beginning with Venn diagrams and set theory. You’ll develop your reasoning ability about computations as well as data processing objects. You can visualize this kind of reasoning with the aid of a Venn diagram.

The next step is algebra and its methods. An introduction to algebra, which can be thought of as maths is done with variables rather than explicit numbers, will be given, along with information on how it is used in algorithms and scientific data processing. You will learn how to use algebra to resolve linear and basic arithmetic in this course.

Finally, you’ll discover vectors and why graphic programming relies so heavily on them. You’ll discover how matrices can be used to represent vectors.

Mathematics for Computer Science
InstitutionUniversity of Hull
PriceMonthly subscription of FutureLearn- $27.99
Duration3 weeks
InstructorLaura Broddle

Key Highlights:

  • Create and analyze Venn diagrams of set relations and operational processes.
  • Be able to identify elements, find the outcomes of intersections or unions, find subgroups and complements, and use set theory notation.
  • Use a variety of algebraic strategies to solve simultaneous, quadratic, and linear equations and inequalities.
  • Find the direction and magnitude of a vector, experiment with vector addition and subtraction, and multiply a vector by a scalar.
  • Find the inverse of a given matrix, if one exists, and perform the addition, multiplication, and transposition matrix operations.

11. Machine Learning (Coursera)


The machine learning course on Coursera is designed to teach learners the fundamentals of machine learning. This course is offered by Andrew Ng, a renowned computer scientist and artificial intelligence expert, and is one of the most popular courses on the platform.

It consists of video lectures, quizzes, and programming assignments that cover a wide range of machine-learning concepts. The course covers both supervised and unsupervised learning, as well as other important topics such as regularization, neural networks, and deep learning.

Learners are expected to complete several programming assignments using MATLAB or Octave, which help them to gain practical experience in implementing machine learning algorithms. 

Throughout the course, Andrew Ng provides clear explanations of complex concepts, making it easy for learners to understand and apply the concepts covered. 

Machine Learning
Duration32 hours
InstructorAndrew Ng, Eddy Shyu, Geoff Ladwig.

Key Highlights: 

  • Build machine learning modes in python.
  • Learn Numpy and sci-kit-learn.
  • Build and train supervised machine learning models.
  • Understand logistic regression for classification.
  • Get a complete overview of Gradient Descent.


Understanding the fundamentals of computer science will speed up your progress toward your goals if you want to learn programming to launch a career in technology.

Select one of the top online computer science courses from the list above to begin learning the fundamentals of computer science as swiftly as possible.

If you are not sure which course to choose from the above courses, then here is my suggestion:

  1. Python Programming and Computer Science Introduction – Best for beginners.
  2. Computer Science 101 – Best for intermediates
  3. Mathematics for Computer Science: Essential Skills – Best for mathematical approach.

I hope this article has helped you to understand the best computer science courses. Share your thoughts in the comment section below.

Alvin Parker

Leave a Comment