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In the age of artificial intelligence, machine learning may sound old-fashioned, but it remains a valuable and frequently used skill. Machine learning is the use of algorithms in computer systems to “learn” from data, enabling those systems to perform autonomous tasks. Manufacturing, engineering, programming, data science, and more can all include machine learning.
The field is very different from artificial intelligence in terms of approach, methods, and underlying structures, and often makes headlines in physics and other scientific applications. To learn more about machine learning, you can take online courses from various companies or institutions.
Best Machine Learning Courses: Comparison Chart
Introduction to Machine Learning (Google): Best for Beginners
Google’s Introduction to Machine Learning course is a clear and low-commitment choice for beginners. This course is the first in a series of Google’s machine learning “foundations courses.” This makes it easy for you to explore as many topics as you want.
Price
This course is free.
period
This course only takes 20 minutes to complete.
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prerequisites
There are no prerequisites for this course.
Data Science – Machine Learning (Harvard on edX): Best for Data Scientists
Harvard University’s online courses have some of the brightest minds in education behind them, which contributed to our selection of “Data Science: Machine Learning”. This course is part of Harvard University’s larger online Data Science course. It is suitable for people with some professional experience in data science, putting machine learning into existing real-world jobs. The result of this course is a project that learners can use or present to current or future employers, i.e. a movie recommendation system that demonstrates mastery of predictive algorithms.
Price
Data Science: Machine Learning is free to audit. A certificate of completion and unlimited access to course materials is available for $149.
period
This course is self-paced and covers enough material to last approximately 8 weeks if you study 2 to 4 hours per week.
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prerequisites
It is recommended to take previous courses Professional Certificate in Data Science Before taking this course.
Cornell Machine Learning Certificate Program (Cornell University): Best for a Traditional College Education
While this certification includes self-paced elements, it also offers live discussions with peers and educators. Participants will receive feedback on their work. The course includes projects suitable for a resume or other real-world presentation. It covers the mathematics involved in machine learning – including linear algebra and probability distributions – as well as the computational aspects, including kernel machines and neural networks.
Price
The cost of this certification is $3,750.
period
This course requires 6-9 hours of study per week and can be completed in 3.5 months.
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prerequisites
Cornell University recommends that students taking this course have a “mathematical background, including familiarity with Python, probability theory, statistics, multivariate calculus, and linear algebra.” Some projects require the use of NumPy library and Jupyter Notebooks.
Stanford Machine Learning Specialization (Coursera): Best for building neural network applications
Andrew Ng is often called one of the best instructors in the field of artificial intelligence. As an adjunct professor at Stanford University and co-founder of Coursera, he has built a brand on conveying complex information in a practical, actionable way to people who want to advance in the tech field. The Machine Learning Specialization consists of three separate courses covering neural networks, deep reinforcement learning, and more.
Price
You can access this course with a Coursera Plus subscription for $59 per month.
period
Coursera estimates that this self-paced course will take 2 months, 10 hours per week.
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prerequisites
Coursera recommends that learners taking this course have a background in “basic coding (for loops, functions, if/else statements) and high school math (arithmetic, algebra).”
IBM Introduction to Machine Learning Specialization (Coursera): Best for aspiring data scientists
IBM instructors teach this machine learning course, which consists of four mini-courses:
- Exploratory Data Analysis for Machine Learning.
- Supervised Machine Learning: Regression.
- Supervised Machine Learning: Classification.
- Unsupervised machine learning.
This specialization includes hands-on exercises with SQL, regression, classification, and other useful tools and techniques in machine learning. By the end of the course, you will be able to design machine learning systems to gain insights from data sets that lack target or labeled variables. Upon completion of this specialization, learners will receive a professional certificate from IBM.
Price
You can get this Specialization content with a Coursera Plus subscription for $59 per month.
period
The specialization requires 10 hours per week over two months to complete.
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prerequisites
Learners pursuing this specialization should have some experience with coding, particularly Python, and be familiar with calculus, linear algebra, probability, and statistics.
method
In selecting these courses, we looked at some of the most reputable universities and online learning platforms in the tech community. We strive to offer beginner, intermediate, and advanced courses and certifications.
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