Online Courses in Machine Learning

Free Machine Learning Online Courses

Below, you find free of charge courses in machine learning for various difficulty levels. However, depending on your prior knowledge, any machine learning online course can be "too easy" or "too hard" for you. We therefore recommend that you check out the videos yourself. The basic version of the courses is available without any cost. (Optional) certificates can be purchased.

• Machine Learning by Stanford University is one of the most famous introductory courses on Machine Learning. The course is taught by Prof. Andrew Ng (AI expert at Google, Coursera co-founder). Course participation is free (optional certificates are available for a fee). The necessary algebra basics are covered by the program.
• In the ML course from Munich University, the foundations of Machine Learning can be studied as well. The course is delivered as a video lecture. Slides are shown together with the lessons.  
• This lecture series by the ETH Zurich presents the theory of fundamental machine learning concepts (e.g. Bayesian theory of optimal decisions, maximum likelihood and Bayesian parameter inference, classification with discriminant functions, ensemble methods, regression, non parametric density estimation, dimension reduction etc.)
• Introduction to Artificial Intelligence (AI) gives a high-level overview of AI and shows how ML provides the foundation of AI. 

Intermediate: 

• This free ML course by Duke University gives an introduction to machine learning models (logistic regression, convolutional neural networks, natural language precessing etc.). Some Python programming and basic math skills are required.
• Microsoft teaches Deep Learning  (via edX). Here participants gain an intuitive understanding of the key concepts of ML. 
• Another Microsoft course explores the essential mathematical foundations of ML and AI.
• The free Machine Learning online course by Udacity covers Supervised, Unsupervised and Reinforcement Learning. 

Advanced:

• Applied AI with Deep Learning teaches deep learning for applications such as natural language processing, computer vision etc. This Machine Learning MOOC by IBM is designed for students with prior experience in programming and mathematics. 
• The Machine Learning course by Columbia University explores classification and regression, clustering methods, sequential models, matrix factorization, topic modeling and model selection. 
• The MOOC Machine Learning: Classification by the University of Washington teaches students how to create classifiers for a variety of tasks. Among the techniques taught are boosted decision trees, kernelized support vector machines, and logistic regression.   
• Participants of the Machine Learning MOOC Marketing Analytics by Columbia University learn how to develop quantitative models that help marketers forecast how customers will buy goods and services.

Fee-based Online Courses in Machine Learning

These paid course series are usually made up of 4-6 individual online courses. The programs last between 2 months and 1,5 years.

They comprehensively prepare you for a career start in ML. After successful completion, you can receive certificates recognized by employers in the field.

(To learn more about certificates and nanodegrees and how companies value them click here.)

Beginner:

• Mathematics for Machine Learning and Data Science

This series of online courses from the renowned Imperial College London is designed to give students the prerequisite mathematical knowledge to take more advanced classes in Machine Learning and Data Science. The program covers linear algebra, multivariate calculus, and principle component analysis. 

• Microsoft Professional Certificate in Data Science Fundamentals 

This course series gives an introduction to the fundamentals of Data Science for beginners. Among the topics covered are working with data using the programming languages R and Python, creating and validating machine learning models with Azure, and applying statistical methods to data.

• Data Science (Harvard)

This online program by Harvard University explains key data science essentials by real-world examples. One module focuses purely on Machine Learning. The ML module lasts 15-20 hours per week, for 8 weeks. In the Machine Learning module you will build a movie recommendation system. 

• Foundations of Data Science (UC Berkeley)

The course covers Python, statistics, and machine learning concepts. 

Intermediate:

• Mathematics for Machine Learning Specialization

The Machine Learning MOOC by the renowned Imperial College London covers the mathematics needed for Machine Learning and Data Science (Linear Algebra, Principle Component Analysis, Multivariate Calculus). The online program was designed for intermediate learners who wish to polish their maths skills for ML and Data Science.  

• Machine Learning A-Z: Hands-On Python & R in Data Science 

This course sequence teaches how to create ML algorithms in Python and R. 

• Machine Learning Specialization (Coursera)

This specialization from Coursera teaches students how to analyze large data sets, build apps that make predictions from data, and create systems and adapt and develop over time. 

• Deep Learning: Recurrent Neural Networks in Python

This course provides an introduction to GRU, LSTM, and more modern deep learning, machine learning, and data science skills. Most work is done in Numpy, Matplotlip, and Theano. 

Advanced:

• Advanced Machine Learning Specialization

This online course series by Coursera covers deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. You need a basic understanding of machine learning concepts as a prerequisite. 

• IBM AI Enterprise Workflow Specialization

The series of six courses prepares you to take the IBM AI Enterprise Workflow V1 Data Science Specialist certificate. The IBM AI Enterprise Workflow enables you to build AI solutions. 

• Self-Driving Car Engineer Nanodegree (Udacity)

The comprehensive course series is taught by Sebastian Thrun, one of the great minds behind autonomous vehicles. The machine learning online classes prepare students for a career in the area of self-driving cars. Prior knowledge of statistics and Python is a must. 

• Machine Learning Engineer Nanodegree (Udacity):

This nanodegree program from Udacity explains the technical details of machine learning. The lecturer, Prof. Sebastian Thrun, is also a co-founder of Udacity. The program lasts about 6 months. 

How to Search for the Best Online Courses in Machine Learning?

There are, of course, many other Machine Learning MOOCs and video lectures.

Use the search field at the top of the Edukatico website to find online courses in your chosen subject. Use the filter to refine your search criteria.  

You receive more results if you search for related concepts. For example, instead of typing "machine learning" into the search field use alternative search terms such as "supervised/unsupervised reinforcement", "deep learning" or "multivariable calculus". 

Edukatico Is Your Search Portal for Online Courses

Browse thousands of online courses from various providers in 22 subject areas in our directory (MOOCs, online lectures, and other online courses). 

Just test a free MOOC yourself. And register for our Course Manager to efficiently organize your online courses. And also subscribe to our newsletter here, and follow us on Facebook and Twitter!