Finding the Best Machine Learning Online Courses in 2020

Machine learning is a branch of computer science and artificial intelligence that automates analytical model building. It is based on the belief that systems can learn from data, identify patterns and make decisions with minimal human intervention. As models are exposed to new data, they are able to independently adapt, learning from previous computations and creating reliable and repeatable results.

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University of California, Berkeley

Machine Learning Online Course

Understand the impact of machine learning, and aptly communicate its integration. Learn to analyze the models, techniques, and ethical ramifications of ML applications.Learn More

London School of Economics

Machine Learning: Practical Applications

Engage with real-world problems as you apply machine learning models to data sets in R, interpret the predictions, and evaluate these predictions.Learn More

What Is a Machine Learning Course?

Machine learning courses offer everything from the fundamentals of machine learning to advanced practices and statistical modeling. There are machine learning online courses for most people who are interested, from beginners to experts. Many machine learning courses are available online for free, meaning there’s little barrier to learning more about this valuable field.

Online machine learning courses

Below are some machine learning courses available online. Machine learning fundamentals courses offer an introduction to machine learning and its basic principles, such as data mining and statistical pattern recognition. Courses will likely include theoretical and practical instruction, so you can learn some basics of implementing machine learning techniques.

While machine learning is often used by data scientists, it can also help many professionals and businesses. Courses for machine learning in business provide an understanding the advantages, limitations and scope of machine learning from a management perspective. Machine learning can be used in business to streamline decision-making, analyze data and reduce errors when processing large amounts of data.

Deep learning courses are advanced and teach students how to run supervised, semi-supervised and unsupervised learning.

Much like how humans process information and then communicate through a biological neural network, deep learning algorithms can process huge amounts of data, then take those datasets and find essential meanings. Deep learning allows the user to develop broader and more in-depth solutions, as opposed to task-specific solutions like in traditional machine learning.

Course	Focus	Topics
LSE Machine Learning: Practical Applications Sponsored	Machine Learning Fundamentals	Regression Classification Tree-based methods and ensemble learning Introduction to neural networks
Machine Learning Crash Course by Google	Machine Learning Fundamentals	Training test sets and validation Machine learning engineering such as static vs. dynamic training Case studies
Machine Learning A-Z™: Hands-On Python & R In Data Science	Machine Learning Fundamentals	Data preprocessing Linear regressions Support vector regressions (SVR) Natural language processing
UC Berkeley Machine Learning Sponsored	Machine Learning for Business	Solving business problems with machine learning Measuring and evaluating model performance Neural networks for business Justifying an organizational machine learning approach
Massachusetts Institute of Technology Machine Learning in Business	Machine Learning for Business	Implementing machine learning in a business Helping machines learn to use language Finding patterns in human transactions Machine learning challenges in the future
Artificial Intelligence & Machine Learning for Business	Machine Learning for Business	Industries disrupted by artificial intelligence and machine learning Applications of artificial intelligence and machine learning for business leaders
Machine Learning, Data Science and Deep Learning with Python	Deep Learning	Building ANNs with Tensorflow and Keras Linear regression, polynomial regression, and multivariate regression Apache Spark’s MLLib
Introduction to Deep Learning	Deep Learning	Intro to deep learning methods Image recognition Game playing Image generation

What Is the Difference Between Artificial Intelligence and Machine Learning?

The terms machine learning, artificial intelligence and deep learning are often thrown around interchangeably, but they are all distinct disciplines and techniques. Artificial intelligence is the science of training machines to perform human tasks, whereas machine learning is a subset of artificial intelligence that instructs a machine how to learn.

Artificial intelligence is the broadest term to describe advanced computer intelligence. According to the Brookings Institution, AI is thought to refer to machines that “respond to stimulation consistent with traditional responses” like humans, while taking into account humans’ ability for contemplation, judgment and intention.” An example would be
IBM’s Deep Blue, which beat chess grandmaster Garry Kasparov at the game in 1996. Deep Blue relied on rule-based artificial intelligence: If a player did X, the next move should be Y.

Machine learning is a subfield of artificial intelligence. According to O’reilly, the core principle is that machines take data and “learn” for themselves. Google DeepMind’s AlphaGo, which in 2016 beat Lee Sedol at Go, extrapolated the strategy of the game by studying a large dataset of expert moves. This was a form of machine learning.

How Can I Enhance My Career With a Machine Learning Course?

Machine learning is useful for businesses because it reduces work and room for error. There are a number of careers that deal with machine learning, including:

Machine learning engineers
Data scientist
Natural language processing scientists
Business intelligence developers
Human-centered machine learning designers

Many businesses can benefit from the analysis and interpretation of large amounts of data. Machine learning may provide valuable insights in your current business or open new career paths at other organizations.

LSE Machine Learning:Practical Applications

Online

LSE Machine Learning:Practical Applications Online Course

LENGTH: 8 Weeks

This online technical course from the LSE provides a practical approach to machine learning in modern business analytics. Throughout the course, you’ll analyze real-world problems as you apply machine learning models in R, interpret the predictions, and evaluate the results.

UC Berkeley Machine Learning