Coursera Deep Learning

Expert in Data Science, Machine Learning and AI. Become an IBM-approved Expert in Data Science, Machine Learning and Artificial Intelligence.

Break into the NLP space. Master cutting-edge NLP techniques through four hands-on courses!

Launch your career as an AI engineer. Learn how to provide business insights from big data using machine learning and deep learning techniques.

Welcome to the Reinforcement Learning course. Here you will find out about: - foundations of RL methods: value/policy iteration, q-learning, policy gradient, etc. –- with math & batteries included - using deep neural networks for RL tasks –- also known as "the hype train"

Clouds, Distributed Systems, Networking. Learn about and build distributed and networked systems for clouds and big data.

People apply Bayesian methods in many areas: from game development to drug discovery. They give superpowers to many machine learning algorithms: handling missing data, extracting much more information from small datasets. Bayesian methods also allow us to estimate uncertainty in predictions, which is a desirable feature for fields like medicine.

Kick-start Your Career with Artifical Intelligence.

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial.

Get Ahead with Key Business Technologies. Gain Foundational Understanding of Key Technologies Driving Modern Businesses.

AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone–especially your non-technical colleagues–to take.