Developing high quality distributed systems software is hard; developing high quality reusable distributed systems software is even harder. The principles, methods, and skills required to develop reusable software cannot be learned by generalities. Instead, developers must learn through experience how...

This post is part of our “Getting Started” series of free text tutorials on some of our most popular course topics.

Lectures from the NYU Course on Deep Learning (Spring 2014) This is a graduate course on deep learning, one of the hottest topics in machine learning and AI at the moment. In the last two or three years, Deep learning has revolutionized speech recognition and image recognition. Deep learning is...

This is an introductory course by Caltech Professor Yaser Abu-Mostafa on machine learning that covers the basic theory, algorithms, and applications. Machine learning (ML) enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML techniques...

The C++ Grandmaster Certification is an online course in which participants develop their own complete standalone C++ toolchain - including a preprocessor, compiler, assembler, linker, and standard library. The toolchain will produce executable applications for a target of (a) the Linux operating...

Modern theoretical methods used in study of molecular structure, bonding, and reactivity. Concepts and practical applications. Semiempirical, ab initio, and density functional calculations of molecular electronic structure. Theoretical determination of molecular structure and spectra; relationship to...

Natural language processing (NLP) is one of the most important technologies of the information age. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate most everything in language: web search, advertisement...

Haskell is a high-level, pure functional programming language with a strong static type system and elegant mathematical underpinnings, and is being increasingly used in industry by organizations such as Facebook, AT&T, and NASA. In the first 3/4 of the course, we will explore the joys of pure, lazy,...

Machine learning is a powerful set of techniques that allow computers to learn from data rather than having a human expert program a behavior by hand. Neural networks are a class of machine learning algorithm originally inspired by the brain, but which have recently have seen a lot of success at practical...

These are the videos I use to teach my Neural networks class at Université de Sherbrooke

Deep Reinforcement Learning

Advanced Topics 2015 (COMPM050/COMPGI13): Reinforcement Learning

Our 4-week advanced course considers how to design interactions between agents in order to achieve good social outcomes. The course -- which is free and open to the public -- considers three main topics: social choice theory (i.e., collective decision making), mechanism design, and auctions. More...

Advanced Topics in Machine Learning: COMPGI13 (kernel part)

We've built a collection of 48 exercises that demonstrate attacks on real-world crypto. This is a different way to learn about crypto than taking a class or reading a book. We give you problems to solve. They're derived from weaknesses in real-world systems and modern cryptographic constructions....

One of the best ways to learn how to program in a new language is by looking at lots and lots of example programs. The best thing to do is to copy and paste each program below into a text file and compile it. Then, try the experiments. By extending these example programs, you will gain familiarity with...

This course provides an overview of Enterprise Computing and in particular, the role of System z hardware and its primary operating system (z/OS) in an Enterprise Computing environment. The emphasis is on commercial computing. The introductory topic provides an overview of Enterprise Computing in...

A course taught in 2015 at Oxford University with the help of Brendan Shillingford. The course focuses on the exciting field of deep learning. By drawing inspiration from neuroscience and statistics, it introduces the basic background on neural networks, back propagation, Boltzmann machines, autoencoders...

Computer Vision has become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. Recent developments...

This class is an introduction to the practice of deep learning through the applied theme of building a self-driving car. It is open to beginners and is designed for those who are new to machine learning, but it can also benefit advanced researchers in the field looking for a practical overview of deep...