The machine learning (ML) and artificial intelligence (AI) industries are booming right now. According to a report published by Fortune Business Insights, the global ML industry is expected to grow at a compound annual growth rate of 36.2%, reaching a market capitalization of $225.91 billion by 2023. ML includes healthcare, retail, automotive, manufacturing, and agriculture.
If you’re looking to get into ML, or if you already understand the basic concepts and want to expand your skill set, you’re in the right place. We’ve compiled a list of the best free and paid online courses that you can start today and complete at your own pace. The courses listed range from beginner to advanced levels.
Browse the courses below to find your next course. After choosing the right program, you need to register for a specific platform, free or paid. Make sure you have a good internet connection as internet is a prerequisite for all online courses. We recommend using CenturyLink Internet. It’s fast and affordable, so you can complete the course without interruption. Here is a list of the courses we have selected for you.
Introduction to Machine Learning for Programmers – Fast.ai
This course is intended for programmers who already have Python programming experience. Course content is based on the University of San Diego’s Data Science program, and lectures are delivered in the classroom with other students, similar to MIT OpenCourseware. The only drawback is that it only uses the open source library “fastai” to teach ML.
The course is highly interactive and applied, giving you hands-on experience in developing new projects. You’ll also learn how to incorporate your project into action with videos, assignments, notes, and discussion boards. The best part about this course is that it’s free. It doesn’t give you a certificate of completion, but it’s great if you’re just trying to learn ML.
Machine Learning – Coursera
This is one of the most popular online ML courses you can find on the internet. The course is taught by Andrew Ng, Stanford University professor and co-founder of Google Brain and Coursera. He’s a very talented person with deep machine learning expertise that you can benefit from. It’s important to note that this program uses Octave as the programming language, not Python or R. This is great if you want to diversify your skills.
The course is easy to follow because everything is explained in detail, including math and calculus procedures. Additionally, course audits are free, but you will need to pay if a certificate is required upon completion.
Deep Learning Specialization – Coursera
After completing a Machine Learning course on Coursera, you can move on to the next core that explores neural networks and deep learning in more detail. This course is brought to you by Andrew Ng and his deeplearning.ai and is free to take. However, if you want a certificate, you’ll need to purchase a Coursera monthly subscription. It is up to you to complete the course over a month or not, but you will have to pay a monthly fee unless you have completed the course.
Machine Learning Crash Course – Google AI
Google AI Education is a completely free platform with dozens of useful resources anyone can use to learn machine learning and artificial intelligence. As this is a crash course, it primarily focuses on the topics you need to learn to solve machine learning problems using Python. Another nice feature of this course is that it gives you an interactive Jupyter notebook where you can save your notes in Google Colab.
This course is especially useful if you want to cover all the fundamentals of machine learning but don’t want to pay the subscription fee. Please note that you will not receive a certificate even if you complete the course.
Machine Learning with Python – Coursera
Brought to you by IBM, this is an introductory machine learning course that uses the Python programming language. Calculations are also taken down a notch and you won’t encounter overly complex calculations. Begin with an introduction to machine learning and progress to regression, classification, clustering, and recommender systems. Finally, we need to build the final project. This can also be featured in your portfolio.
Since it is a course for beginners, I will carefully explain each step. The instructor will explain the process and the pros and cons of each algorithm at the start. This course is free to attend, but a monthly fee is required to receive a certificate of completion.
Conclusion
These are some of the courses you can start today to sharpen your machine learning skills. Please note that most free courses do not provide a certificate of completion and often you will have to pay an additional fee to obtain one. However, if it doesn’t matter and you’re just focused on learning the concepts, you can do it for free most of the time.
source of information
https://www.learndatasci.com/best-machine-learning-courses/
