17 online computer science classes from MIT you can enroll in for free

This course is part one of an introduction to computational thinking, programming, and computer and data science. Without any prior experience in computer science or programming, you should be able to exit both with an understanding of how to think computationally and write programs to tackle problems.

The class focuses on breadth rather than depth. You'll learn about Python, simple algorithms, testing and debugging, data structures, and get an informal introduction to algorithm complexity.

This course should take nine weeks to complete.

This is part one of a three-part series on digital systems. It's based on a course offered by the MIT Department of Electrical Engineering and Computer Science and covers topics like digital encoding of information, principles of digital signaling, combinational and sequential logic, implementation in CMOS, and more.

Using your browser for design entry and simulation, you'll get to design and debug circuits at both the transistor- and gate-level, culminating in the creation of a 32-bit arithmetic and logic unit.

It'll take ten weeks to complete.

This course covers topics like the design of a processor instruction set architecture, how to translate high-level programs into sequences of computer instructions, the design of the datapath and control logic for a 32-bit processor, and the role of caches in the memory hierarchy.

It takes ten weeks to complete.

This interactive course teaches students how to turn a processor into an entire computer system. You'll learn virtualization as a way to share a single processor, along with basic organization of a simple time-shared operating system, appropriate techniques for parallel processing, and how to use pipelining to increase a processor's throughput.

This course should take ten weeks to complete.

This course teaches students the techniques foundational to the design of microchips used in smartphones, self-driving cars, computers, and the internet.

It should take students five weeks to complete.

Slightly beyond the Level 1 class, this course teaches students how to speed up digital circuits and build amplifiers in the design of microchips used in smartphones, self-driving cars, computers, and the internet.

It'll take students 5 weeks to complete.

Students will learn about cool applications, op-amps and filters in the design of microchips used in smartphones, self-driving cars, computers, and the internet.

It should take students seven weeks to complete.

This introductory synthetic biology course brings together computer science, engineering, design, biotechnology, genetic engineering, and biology. Students will learn how to engineer biological systems and program organisms to perform novel tasks.

It'll take students 15 weeks to complete.

In Paradox and Infinity, you will be introduced to highlights from the intersection of philosophy and mathematics. You'll learn about infinity, time travel and free will, and computability and Gödel's Theorem.

It'll take students 12 weeks to complete.

This course is part one of two courses focused on writing good software with modern engineering techniques.

Students learn how to write programs that are safe from bugs, easy to understand, and ready for change. They'll learn about Java programming, software testing, code specifications, and abstract data types.

It takes 12 weeks to complete.

This is the second course on writing good software. It digs deeper into what makes a good code "good" and teaches students how to create code that is safe from bugs, easy to understand, and ready for change. Students will explore two paradigms for modern programming: grammars, parsing, and recursive datatypes; and concurrent programming with threads.

It should take students ten weeks to complete.

This course is designed as a focused view of the theory behind modern discrete-time signal processing systems and applications. Each topic includes a set of automatically-graded exercises for self-assessment, to help digest concepts, and to preview topics.

It should take students four weeks to complete.

Learn how to design health information and communication technology (ICT) solutions for the developing world in this course that focuses on leveraging IT to do just that. It especially highlights how to do so in resource-constrained settings. Students will learn about global health burdens, health informatics, design thinking, evaluation and monitoring, and the software development process.

It should take students 13 weeks to complete.

This is an in-depth introduction to the field of machine learning. Students will cover topics from linear models to deep learning and reinforcement learning through hands-on Python projects. It's also the last course in the MITx MicroMasters program in Statistics and Data Science.

It'll take students 15 weeks to complete.

This class is part of a three-course series that teaches students about quantum bits, quantum logic gates, quantum algorithms, and quantum communications. It will help build foundational knowledge to understand what quantum computers can do, how they work, and how you can contribute to discovering new things and solving problems.

It should take students five weeks to complete.

The second part of Quantum Information Science builds on the foundational introduction provided in the first course and explores simple quantum protocols and algorithms, including quantum teleportation and superdense coding, Deutsch-Jozsa and Simon's algorithms, Grover's quantum search algorithm, and Shor's quantum factoring algorithm.

It should take students five weeks to complete.

The third and final course in Quantum Information Science is an introduction to the theory and practice of quantum computation. It builds on the previous courses' foundational knowledge and the simple quantum protocols learned during the second course. Students will learn about formal models for quantum noise and quantum communication channels, simple quantum error-correction codes, including the quantum Hamming code, quantum key distribution protocol, and distributed quantum protocols and algorithms.

It should take seven weeks to complete.