Starting to learn machine learning online can be overwhelming because there are many good online courses out there. I understood the situation, I was there too.
In this article, I will tell you more about the course that I recommend the most for any beginner in machine learning.
Machine learning specialization by Andrew NG is a popular course on Coursera and the first course I took that helped me understand the basics of math, statistics, and programming needed for machine learning.
What is Coursera?
Coursera is an online learning platform that provides guided on-demand courses on a wide range of topics. The platform collaborates with top universities and corporations such as Amazon Web Services, Google, and IBM to deliver courses.
How does Coursera work?
The platform contains courses, projects, and specializations. a specialization contains many individual courses.
More about Machine Learning Specialization by Andrew Ng:
This is one of the most popular courses on the platform in machine learning. The course is explained to beginners with no background in math or programming. The new 2022 version of the course uses Python language programming.
The course is taught by professor Andrew Ng from Standford. His way of teaching is easy to understand and follow.
This course begins by building the mathematical groundwork for machine learning. It covers linear algebra and univariate linear regression before going on to multivariate and logistic regression.
You will learn the following in the first course of the Machine Learning Specialization:
• Create machine learning models in Python using NumPy and scikit-learn.
• Construct and train supervised machine learning models for prediction and binary classification problems, such as linear regression and logistic regression.
DeepLearning.AI and Stanford Online collaborated to produce the Machine Learning Specialization, a core online curriculum. You will study the principles of machine learning and how to apply these approaches to construct real-world AI applications in this beginner-friendly class.
This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.
This three-course Specialization is an updated and enlarged version of Andrew’s groundbreaking Machine Learning course, which has received 4.9 out of 5 stars and has been studied by over 4.8 million students since its inception in 2012.
It covers supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.)
By the completion of this Specialization, you will have mastered fundamental principles and obtained the practical know-how to apply machine learning to tough real-world situations swiftly and forcefully. The new Machine Learning Specialization is the ideal place to start whether you want to get into AI or establish a career in machine learning.
How does the course work?
There are 3 ways to take this course on Coursera:
1- You can pay the price of the course to watch all the videos and take the certification at the end of the specialization if you passed all the assignments.
2- Or, you can apply for financial aid that takes up to 15 days to be reviewed. Once accepted, you can take the course and get the certification after passing the assignments.
3- If you are only interested in taking the course without the certification or doing the assignments, you can audit the course. The third method will let you watch all the videos of the specialization.
Features of the course:
This course, like other Coursera courses, has:
Certificate of completion
Course forums to answer your questions
Lecture control speed
Offline videos
Video subtitles
Assignments
If you have taken this course or another machine learning course that you recommend, make sure to mention it in the comments.
Hey there! I am the creator of AI Decoder.
I am a data scientist by training and a Ph.D. student in AI. In this blog, I try to explain the knowledge I learn in simple words and help someone somewhere.