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:
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:
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.
Intermediate:
Advanced:
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.
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!