Machine Learning

AI is not only for engineers. “AI for Everyone”, a non-technical course, will help you understand AI technologies and spot opportunities to apply AI to problems in your own organization. You will see examples of what today’s AI can – and cannot – do. Finally, you will understand how AI is impacting society and how to navigate through this technological change.

In this course, you'll build a movie recommendation system and learn the science behind one of the most popular and successful data science techniques.

This free, two-hour deep learning course provides an interactive introduction to practical deep learning methods. You will learn to use deep learning techniques in MATLAB® for image recognition.

In this free TensorFlow course, you will be able to learn the basic concepts of TensorFlow, the main functions, operations and the execution pipeline. Starting with a simple “Hello Word” example, throughout the course you will be able to see how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions.

The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods.

Through the preparation for HCIA-AI, you will systematically understand and grasp Python programming, essential mathematics knowledge in AI, basic programming methods using TensorFlow (a machine learning and Deep Learning platform framework), pre-knowledge and overview of Deep Learning, overview of Huawei cloud EI.

In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

This free, two-hour course provides an interactive introduction to practical machine learning methods for classification problems.

Learn what machine learning is all about in this beginner-friendly course. Through videos and labs, learn how to apply different machine learning techniques such as classification, clustering, neural networks, regression, and recommender systems.

Welcome to Recommendation Systems! We've designed this course to expand your knowledge of recommendation systems and explain different models used in recommendation, including matrix factorization and deep neural networks.