Machine learning is a division of AI (Artificial Intelligence) devoted to designing algorithms to learn from data. It has various applications, including business analytics, health informatics, financial predictions, & self-driving cars. Nowadays, machine learning skills are extensively in demand. Most open developer positions on Microsoft’s & Amazon’s career pages require “Machine Learning.” Therefore, the Best Machine Learning Courses can help you to build a career in that field.
If you know about machine learning, you can build a career as Machine Learning Engineer, Natural Language Processing (NLP) Scientist, Data Scientist, or Business Intelligence Developer.
Best Machine Learning Courses
1. Machine Learning by Coursera
This is one of the Best Machine Learning Courses around. This beginner’s course is produced & taught by Mr. Andrew Ng, an experienced Stanford professor, co-founder of Google Brain, co-founder of Coursera, & the VP of Baidu’s AI team.
The course uses the open-source programming language Octave rather than Python or R for the assignments. This might be an impasse for some, but Octave is a simple way to learn the basics of ML (Machine Learning) if you are a total beginner.
In general, the course is very well-rounded & intuitively discussed. The math necessary to understand every algorithm is fully explained, with some calculus details & a revision of Linear Algebra. The course is rather all-inclusive, but some knowledge of Linear Algebra can be helpful.
Provider: Prof. Andrew Ng, Stanford.
Cost: Free to check, $79 for Certificate.
2. Machine Learning Foundations: A Case Study Approach by University of Washington
Many machine learning courses like to deal with the subject from a rather conceptual perspective. They devote lots of time to establishing mathematical foundations & consigning more substantial aspects of the discipline to instances & exercises. This course takes a reverse approach.
As the name suggests, the course approaches machine learning through real-life case studies, each with a precise context & objective. These case studies help to establish machine learning concepts in reality.
Rather than learning how to do regressions only, you will learn how to predict prices with regressions. That doesn’t state that the course polishes over the speculative details. It just approaches the subject more practically.
Provider: University of Washington.
Cost: Free enrollment, $79 for Certificate.
3. Deep Learning Specialization by Coursera
Also created & taught by Professor Andrew Ng, this specialization is a more advanced course for anyone keen to learn about neural networks & Deep Learning, & their ways of solving the problem.
The assignments & lectures in every course use the Python programming language & the TensorFlow library for neural networks. This is obviously an excellent choice after Ng’s Machine Learning course since you will get a similar lecture style, but now Python will be used for machine learning.
Provider: Andrew Ng.
Cost: Free to check, $49 per month for Certificate.
4. Machine Learning Crash Course by Google AI
This course is a product of Google AI Education, an entirely free platform comprising articles, videos, and interactive content. Though free, it is still considered one of the Top Machine Learning Courses Online.
The Machine Learning Crash Course contains the topics required to solve ML (Machine Learning) problems as quickly as possible. Like the earlier course, Python is the programming language of preference, & TensorFlow is introduced here. Every main part of the prospectus comes with an interactive & useful Jupyter notebook hosted on Google Colab.
Video tutorials & articles are concise & simple, so you can quickly move through the course at your speed.
Provider: Google AI.
Cost: Free.
5. Machine Learning with Python by Coursera
This is another beginner course that focuses exclusively on the most basic machine learning algorithms. The instructor, slides, & details of the algorithms merge very well to provide you with an intuitive feeling of the basics.
This course uses Python programming & is rather deals lightly with the mathematics behind the algorithms. With every module, you can note in an interactive Jupyter notebook in your browser to work on the new ideas you just learned. Each notebook strengthens your knowledge & gives you solid instructions if you want to use an algorithm on real data.
Provider: IBM.
Price: Free to check, $39 per month for Certificate.
6. Machine Learning by edX
This is a higher course with the highest math requirement among any other course available. You must have a firm knowledge of Linear Algebra, Calculus, Probability, & programming. The course offers exciting programming assignments in either Python or Octave language, but this course doesn’t teach any of them.
One of the noteworthy dissimilarities with this course is the exposure to the probabilistic approach to machine learning. If you are eager to read some books, such as Machine Learning: A Probabilistic Perspective by Kevin P. Murphy, one of the most suggested data science books, then this course would be a remarkable match.
Provider: University of Columbia.
Cost: Free to check, $300 for Certificate.
7. Introduction to Machine Learning for Coders by Fast.ai
Fast.ai created this remarkable, free machine learning course for people with earlier Python programming experience.
It’s astonishing how much time & effort the creators of Fast.ai have dedicated to this & other courses on their site. The course is founded on = the University of San Diego’s Data Science program, so you will find that the lectures given here are similar to the MIT OpenCourseWare.
The course offers videos, homework assignments, all-embracing notes, & a discussion board. Regrettably, you won’t find graded assignments, quizzes, or certification of completion, so if you need them, consider other alternatives.
A major part of the course content is applied, so you can learn how to use the ML models besides launching them on cloud providers like AWS (Amazon Web Services).
Provider: Fast.ai
Cost: Free.
How To Choose Best Machine Learning Course?
Before finalizing one of the Best Machine Learning Courses for you, consider the following points:
Syllabus Covered: Try to know the syllabus before enrolling to ensure you will learn the vital & required aspects, not the surplus ones.
Course Highlights & services: Furthermore, put some thoughts on course highlights to find out the topics they cover most & other amenities, like placement assistance, mock interviews, & practical projects.
Skills Required: Thinks about the skills required for the course & if you have them.
Course Duration: You must determine the duration of every course.
Course Fees: Know course fees to determine whether they meet your budget.
FAQ
Q: What career can I make after learning machine learning?
A: You can build a career in business analytics, health informatics, financial predictions & much more.
Q: Is there any free Best Machine Learning Courses?
A: As discussed in the article, Introduction to Machine Learning for Coders by Fast.ai & Machine Learning Crash Course by Google AI are free courses.
Q: Is there any use of machine learning in our daily lives?
A: The use of machine learning can be found in Face detection technology, self-driving cars, Smart assistants, cyber security & many more.