Showing 1–12 of 18 results
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.
deeplearning.ai Beginner 6 hours
In this course, you'll define clustering for ML applications, prepare data for clustering, define similarity for your dataset, compare manual and supervised similarity measures, use the k-means algorithm to cluster data, evaluate the quality of your clustering result.
Google Advanced, Intermediate 4 hours
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.
IBM Advanced 10 hours, Self-paced
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.
Reaktor, University of Helsinki Beginner 6 weeks
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.
Huawei Beginner, Intermediate 5 hours
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.
Stanford University Beginner, Intermediate 13 weeks
This Machine Learning with Python course dives into the basics of Machine Learning using Python, an approachable and well-known programming language. You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each.
IBM Intermediate 15 hours
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.
IBM Intermediate 12 hours