Stanford University - Programming, Probability, and Theory

These are full 6 to 10 week courses taught by some of the brightest professors in the world on campus at Stanford University. These classes contain the core curriculum on video, with supplemental info such as textbooks, quizzes, and knowledge bases on pdf files.

Cryptography
Cryptography is an indispensable tool for protecting information in computer systems. This course explains the inner workings of cryptographic primitives and how to correctly use them. Students will learn how to reason about the security of cryptographic constructions and how to apply this knowledge to real-world applications. The course begins with a detailed discussion of how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic. We will examine many deployed protocols and analyze mistakes in existing systems. The second half of the course discusses public-key techniques that let two or more parties generate a shared secret key. We will cover the relevant number theory and discuss public-key encryption and basic key-exchange. Throughout the course students will be exposed to many exciting open problems in the field. The course will include written homeworks and programming labs. 34 videos plus 7 pdfs

Design and Analysis of Algorithms
Introduction to fundamental techniques for designing and analyzing algorithms, including asymptotic analysis; divide-and-conquer algorithms and recurrences; greedy algorithms; data structures; dynamic programming; graph algorithms; and randomized algorithms. 173 videos plus over 30 pdfs

Discrete Probability
Introduction to discrete probability, including probability mass functions, and standard distributions such as the Bernoulli, Binomial, Poisson distributions. 5 videos

Game Theory
Popularized by movies such as "A Beautiful Mind", game theory is the mathematical modeling of strategic interaction among rational (and irrational) agents. Beyond what we call 'games' in common language, such as chess, poker, soccer, etc., it includes the modeling of conflict among nations, political campaigns, competition among firms, and trading behavior in markets such as the NYSE. How could you begin to model eBay, Google keyword auctions, and peer to peer file-sharing networks, without accounting for the incentives of the people using them? The course will provide the basics: representing games and strategies, the extensive form (which computer scientists call game trees), Bayesian games (modeling things like auctions), repeated and stochastic games, and more. We'll include a variety of examples including classic games and real-world applications. 16 videos plus 15 pdfs

Machine Learning
Introduction to applied machine learning. In this course, you'll learn about machine learning techniques such as linear regression, logistic regression, naive Bayes, SVMs, clustering, and more. In addition, you'll also learn the practical, hands-on, skills and techniques needed to get learning techniques to work well in practice. 30 videos plus links to online course material

Model Thinking
We live in a complex world with diverse people, firms, and governments whose behaviors aggregate to produce novel, unexpected phenomena. We see political uprisings, market crashes, and a never ending array of social trends. How do we make sense of it? Models. In this class, you will learn how to think with models and use them to make sense of the complex world around us. 68 videos plus slides and pdfs

Unsupervised Feature Learning and Deep Learning
Machine learning algorithms that learn feature representations from unlabeled data, including sparse coding, autoencoders, RBMs, DBNs.

Natural Language Processing
This course covers a broad range of topics in natural language processing, including word and sentence tokenization, text classification and sentiment analysis, spelling correction, information extraction, parsing, and meaning extraction. In this class, you will learn fundamental algorithms and mathematical models for processing natural language, and how these can be used to solve practical problems. 35 videos plus pdfs