# Hacker Courses > The online courses programmers keep recommending, ranked from 3,371 public Hacker News comments, 2006 to October 2026: 1,376 courses with a page each. Each course is scored from who recommended it, how strongly, in how many separate threads and for how many years (one vote per person; replies piling onto one thread are damped). Every course page quotes the comments behind its ranking and links each one to Hacker News. The catalog, rankings and summaries are CC BY 4.0; please cite and link the course page. Not affiliated with Y Combinator or Hacker News. ## Courses by topic - [Machine Learning & AI](https://hackercourses.com/topic/machine-learning-and-ai/): 172 courses. Top: Machine Learning (Andrew Ng), Practical Deep Learning for Coders, CS231n: Convolutional Neural Networks for Visual Recognition, Deep Learning Specialization (Andrew Ng), Neural Networks for Machine Learning (Geoffrey Hinton) - [Algorithms & Data Structures](https://hackercourses.com/topic/algorithms-and-data-structures/): 78 courses. Top: Algorithms, Part I, CS61A: Structure and Interpretation of Computer Programs, 6.006 Introduction to Algorithms, Introduction to Computer Science and Programming in Python, Algorithms: Design and Analysis, Part 1 - [CS Fundamentals & Systems](https://hackercourses.com/topic/cs-fundamentals-and-systems/): 166 courses. Top: The Elements of Computing Systems (Nand2Tetris), CS50: Introduction to Computer Science, Human Behavioral Biology (Robert Sapolsky), 6.824 Distributed Systems, 15-213 Introduction to Computer Systems - [Mathematics](https://hackercourses.com/topic/mathematics/): 178 courses. Top: 18.06 Linear Algebra (Gilbert Strang), Stat 110: Probability, The Theoretical Minimum (Leonard Susskind), 6.042J Mathematics for Computer Science, Essence of Linear Algebra - [Programming Languages](https://hackercourses.com/topic/programming-languages/): 124 courses. Top: 6.001 Structure and Interpretation of Computer Programs, Functional Programming Principles in Scala, Programming Languages (Dan Grossman), Design of Computer Programs, Compilers - [Web & Mobile Development](https://hackercourses.com/topic/web-and-mobile-development/): 131 courses. Top: CS193P Developing Applications for iOS using SwiftUI, CS253 Web Development, Web Development, CSS for JavaScript Developers, The Web Developer Bootcamp - [Databases & Data Engineering](https://hackercourses.com/topic/databases-and-data-engineering/): 30 courses. Top: 15-445/645 Intro to Database Systems, Introduction to Databases, 15-721 Advanced Database Systems, Intro to Database Systems, Databases: 5 SQL (Stanford) - [Security & Cryptography](https://hackercourses.com/topic/security-and-cryptography/): 25 courses. Top: Cryptography I, Applied Cryptography, CS255 Introduction to Cryptography (Dan Boneh), Modern Binary Exploitation, Securing Digital Democracy - [Science & Engineering](https://hackercourses.com/topic/science-and-engineering/): 150 courses. Top: Introduction to Biology - The Secret of Life, The Feynman Lectures on Physics, Underactuated Robotics, For the Love of Physics (Walter Lewin), 6.002 Circuits and Electronics - [Business, Finance & Economics](https://hackercourses.com/topic/business-finance-and-economics/): 91 courses. Top: Economics of Money and Banking, Financial Markets, Behavioral Economics (Dan Ariely), How to Start a Startup, Startup Engineering - [Design & Creative](https://hackercourses.com/topic/design-and-creative/): 31 courses. Top: Pixar in a Box, Writing Science Fiction and Fantasy (Brandon Sanderson), How to Draw, Introduction to Human-Computer Interaction, Songwriting - [Humanities & Social Science](https://hackercourses.com/topic/humanities-and-social-science/): 154 courses. Top: Justice (Michael Sandel), How to Listen to and Understand Great Music, Personality and its Transformations (Jordan Peterson), A Brief History of Humankind, The Peloponnesian War - [General Learning](https://hackercourses.com/topic/general-learning/): 46 courses. Top: Learning How to Learn: Powerful mental tools to help you master tough subjects, Model Thinking, The Science of Well-Being, How to Speak, The Art of Doing Science and Engineering (Richard Hamming) ## Top 30 overall - [Machine Learning (Andrew Ng)](https://hackercourses.com/course/machine-learning-andrew-ng/): Coursera; 240 recommenders, 2009–2026. Andrew Ng's introductory machine learning course on Coursera, covering supervised and unsupervised learning, linear and logistic regression, neural networks, and practical advice on applying ML. It originated as the… - [6.001 Structure and Interpretation of Computer Programs](https://hackercourses.com/course/6-001-structure-and-interpretation-of-computer-programs/): MIT OpenCourseWare; 88 recommenders, 2007–2026. MIT's introductory course on Structure and Interpretation of Computer Programs, built around the SICP textbook and Abelson and Sussman lectures, teaching abstraction, recursion, interpreters and functional-style… - [The Elements of Computing Systems (Nand2Tetris)](https://hackercourses.com/course/the-elements-of-computing-systems-nand2tetris/): nand2tetris.org; 87 recommenders, 2010–2026. The Elements of Computing Systems (Nand2Tetris) is a project-based course in which you build a working computer from NAND gates upward: logic gates, a CPU, memory, an assembler, a virtual machine, a high-level language… - [Practical Deep Learning for Coders](https://hackercourses.com/course/practical-deep-learning-for-coders/): fast.ai; 112 recommenders, 2017–2026. A free, top-down, hands-on deep learning course by Jeremy Howard and Rachel Thomas at fast.ai that teaches practitioners to build working models with PyTorch and Jupyter notebooks, with relatively little emphasis on… - [18.06 Linear Algebra (Gilbert Strang)](https://hackercourses.com/course/18-06-linear-algebra-gilbert-strang/): MIT OpenCourseWare; 78 recommenders, 2009–2026. MIT's undergraduate introductory linear algebra course taught by Gilbert Strang, covering matrices, vector spaces, eigenvalues, and the singular value decomposition, with video lectures, syllabus, and problem sets… - [CS50: Introduction to Computer Science](https://hackercourses.com/course/cs50-introduction-to-computer-science/): Harvard University; 72 recommenders, 2012–2026. CS50 is Harvard's introductory computer science course, covering programming fundamentals in C, Python, and web technologies along with algorithms, data structures, and problem-solving. It is offered free through… - [Learning How to Learn: Powerful mental tools to help you master tough subjects](https://hackercourses.com/course/learning-how-to-learn-powerful-mental-tools-to-help-you-master-tough-s/): Coursera; 60 recommenders, 2014–2025. A short Coursera course by Barbara Oakley (with Terrence Sejnowski) on the cognitive science of learning, covering topics such as chunking, memory, procrastination, and focused versus diffused modes of thinking. It is… - [Cryptography I](https://hackercourses.com/course/cryptography-i/): Coursera; 41 recommenders, 2012–2025. An introductory Coursera course by Dan Boneh (Stanford) covering the fundamentals and math of cryptography, including practical exercises such as breaking flawed constructions. It is the first of a two-part sequence… - [Functional Programming Principles in Scala](https://hackercourses.com/course/functional-programming-principles-in-scala/): Coursera; 42 recommenders, 2012–2026. Martin Odersky's introductory MOOC on functional programming using Scala, covering recursion, higher-order functions, immutable data, pattern matching, and collections. It is based largely on SICP-style exercises and… - [CS193P Developing Applications for iOS using SwiftUI](https://hackercourses.com/course/cs193p-developing-applications-for-ios-using-swiftui/): Stanford University; 39 recommenders, 2009–2025. CS193P is Stanford's iOS application development course, taught by Paul Hegarty, with free lecture videos and assignments covering Objective-C, Cocoa Touch, and later SwiftUI. Commenters describe it as a structured… - [Algorithms, Part I](https://hackercourses.com/course/algorithms-part-i/): Coursera; 38 recommenders, 2012–2025. Algorithms, Part I is Robert Sedgewick's introductory Princeton course on Coursera, covering fundamental data structures and algorithms such as union-find, stacks, queues, sorting, and searching, with Java programming… - [CS61A: Structure and Interpretation of Computer Programs](https://hackercourses.com/course/cs61a-structure-and-interpretation-of-computer-programs/): UC Berkeley; 31 recommenders, 2008–2026. CS 61A is UC Berkeley's introductory computer science course built around the textbook Structure and Interpretation of Computer Programs (SICP), covering programming abstraction, recursion, interpreters, and related… - [CS231n: Convolutional Neural Networks for Visual Recognition](https://hackercourses.com/course/cs231n-convolutional-neural-networks-for-visual-recognition/): Stanford University; 39 recommenders, 2015–2024. Stanford's CS231n covers convolutional neural networks and deep learning for visual recognition, including backpropagation, training networks, CNNs, and related architectures, with course notes, assignments, and… - [6.006 Introduction to Algorithms](https://hackercourses.com/course/6-006-introduction-to-algorithms/): MIT OpenCourseWare; 27 recommenders, 2009–2024. MIT's undergraduate introduction to algorithms and data structures, covering asymptotic analysis, sorting, hashing, graph search, and dynamic programming, with lecture videos and materials on MIT OpenCourseWare. It… - [Programming Languages (Dan Grossman)](https://hackercourses.com/course/programming-languages-dan-grossman/): Coursera; 30 recommenders, 2013–2023. A Coursera course by Dan Grossman (University of Washington) that teaches programming language fundamentals through Standard ML, Racket, and Ruby, covering functional programming, recursion, types, pattern matching… - [Deep Learning Specialization (Andrew Ng)](https://hackercourses.com/course/deep-learning-specialization-andrew-ng/): Coursera; 31 recommenders, 2017–2025. A five-course Coursera specialization by Andrew Ng, offered through deeplearning.ai, covering neural networks, hyperparameter tuning and project structure, convolutional networks, and sequence models. It builds from… - [Introduction to Computer Science and Programming in Python](https://hackercourses.com/course/introduction-to-computer-science-and-programming-in-python/): MIT OpenCourseWare; 25 recommenders, 2010–2025. MIT's introductory computer science course taught in Python, covering core programming and computational problem-solving with lecture videos, problem sets, and the course textbook. It is offered free through MIT… - [Human Behavioral Biology (Robert Sapolsky)](https://hackercourses.com/course/human-behavioral-biology-robert-sapolsky/): Stanford University; 26 recommenders, 2015–2026. Robert Sapolsky's Stanford course on human behavioral biology, taught as a lecture series that explains behavior across levels from genes and brain chemistry to evolution and culture. The lectures are freely available… - [Neural Networks for Machine Learning (Geoffrey Hinton)](https://hackercourses.com/course/neural-networks-for-machine-learning-geoffrey-hinton/): Coursera; 25 recommenders, 2012–2025. Geoffrey Hinton's Coursera course on neural networks for machine learning, covering feedforward and recurrent networks, backpropagation, and deep learning fundamentals from one of the field's pioneers. It is a… - [CS229 Machine Learning](https://hackercourses.com/course/cs229-machine-learning/): Stanford University; 20 recommenders, 2007–2023. Stanford's graduate-level machine learning course taught by Andrew Ng, covering the theory and math behind common learning algorithms, with lecture videos and course notes available online. It assumes a strong… - [Learning From Data](https://hackercourses.com/course/learning-from-data/): Caltech; 20 recommenders, 2012–2025. Yaser Abu-Mostafa's Caltech course on the theoretical foundations of machine learning, covering generalization, VC dimension, regularization, validation, and linear and nonlinear models. Available as free video… - [15-445/645 Intro to Database Systems](https://hackercourses.com/course/15-445-645-intro-to-database-systems/): Carnegie Mellon University; 17 recommenders, 2017–2025. CMU's introductory database systems course covering how DBMSs are designed and built: data models, storage, indexing, concurrency control, recovery, and query processing. Lectures are published free on YouTube, and… - [Introduction to Databases](https://hackercourses.com/course/introduction-to-databases/): Stanford University; 16 recommenders, 2011–2023. An introductory Stanford course by Jennifer Widom covering relational databases, relational theory and algebra, and SQL, with lectures and problem sets. It has run as a Stanford MOOC in several sessions, with… - [6.824 Distributed Systems](https://hackercourses.com/course/6-824-distributed-systems/): MIT OpenCourseWare; 16 recommenders, 2013–2025. MIT's graduate-level distributed systems course, with published lecture notes, assigned readings of classic papers, and Go labs that build pieces such as MapReduce, Raft consensus, and a sharded key-value store… - [Algorithms: Design and Analysis, Part 1](https://hackercourses.com/course/algorithms-design-and-analysis-part-1/): Coursera; 17 recommenders, 2012–2022. Stanford's introductory algorithms course taught by Tim Roughgarden covering asymptotic analysis, divide and conquer, sorting, and graph algorithms, with programming assignments checked against data sets. It was… - [Stat 110: Probability](https://hackercourses.com/course/stat-110-probability/): Harvard University; 18 recommenders, 2013–2025. Harvard's introductory probability course taught by Joe Blitzstein, covering probability basics and problem solving, with video lectures, problem sets, and a companion textbook. Lectures and materials are freely… - [CS188 Introduction to Artificial Intelligence](https://hackercourses.com/course/cs188-introduction-to-artificial-intelligence/): UC Berkeley; 18 recommenders, 2011–2018. CS188 is UC Berkeley's introductory artificial intelligence course, covering classical AI such as search, game playing, and probabilistic reasoning, with later material on machine learning. Its assignments are built… - [The Theoretical Minimum (Leonard Susskind)](https://hackercourses.com/course/the-theoretical-minimum-leonard-susskind/): YouTube; 16 recommenders, 2009–2024. A Stanford continuing-education lecture series by physicist Leonard Susskind, with companion books, covering classical mechanics, quantum mechanics, special and general relativity, and related topics at roughly… - [Probabilistic Graphical Models](https://hackercourses.com/course/probabilistic-graphical-models/): Coursera; 15 recommenders, 2012–2025. An advanced Coursera course by Daphne Koller on probabilistic graphical models, covering Bayesian networks, Markov networks, inference, and learning. It is based on the Koller and Friedman textbook and is noted for… - [15-213 Introduction to Computer Systems](https://hackercourses.com/course/15-213-introduction-to-computer-systems/): Carnegie Mellon University; 12 recommenders, 2009–2024. Carnegie Mellon's undergraduate introduction to computer systems, covering how programs run at the level of machine code, memory, linking, and the operating system, built around labs such as the bomb lab and malloc… ## Optional - [Every course, one record each](https://hackercourses.com/llms-full.txt): rank, links, topic, level, cost, format, years and summaries for all courses - [About and ranking method](https://hackercourses.com/about/) - [Source code and pipeline](https://github.com/dciconi/hackercourses)