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Online Courses in Machine Learning

There are countless different providers of free machine learning online courses. In this overview, we show you how you can take machine learning classes online and become a machine learning expert.

Online Courses in Machine Learning
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Machine Learning Engineer is one of the most exciting emerging jobs.

It is well paid and perfectly suitable for newcomers.

We discuss Machine Learning (ML) as a science and show you where to find the appropriate online courses to kick-start your career in ML. 

(Do you want to know more about new emerging digitization jobs? Here we discuss three jobs of the future and a list of online courses for qualifying.)





Keep reading to find out:

1. What Machine Learning is

2. Why Machine Learning is important today 

3. How you can learn more about Machine Learning using online courses




What is Machine Learning? 

The answer probably depends on whom you ask. A simple definition of Machine Learning could sound like this: Machine Learning is the science of getting machines to learn on their own without being explicitly programmed. 

Machine Learning (ML) is part of Artificial Intelligence (AI). Whereas AI is the broad science of making machines mimick human intelligence, ML trains machines how to learn. 

ML Engineers use programming language and big data tools to write programs that enable machines to learn without being explicitly programmed. 

ML is important for anyone who needs to deal with large data sets. Among the industries that benefit from ML are:

  • Health care: Machine Learning helps medical staff to analyze complex medical data. It also enables wearable devices to assess a patient's health. 
  • Transportation: Recognizing traffic patterns is vital for making routes more efficient and forecasting traffic problems. 
  • Banking and finance: ML helps banks and financial service providers to analyze large sets of data to spot investment opportunities and to detect fraud.  

Machine Learning Engineers are highly paid experts. The average total pay for a Machine Learning Engineer in the United States is $ 165,000 (as of October 2019). In addition, ML is particularly suitable for lateral entrants. These factors make ML a highly attractive career. 

In summary:

  • Machine Learning is the science of making machines learn independently
  • Machine Learning is part of AI
  • Machine Learning Engineers use mathematics, statistics and programming languages
Online Courses in Machine Learning
Picture: geralt/Pixabay

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.

Beginner:

  • 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.


Tech vlogger Siraj Raval shares his 3-months-guide to help you go from an absolute beginner to proficient. 



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:

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. 

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.

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. 

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

Intermediate:

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.  

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

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. 

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:

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. 

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. 

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!