Is Machine Learning by Andrew Ng is worth it? Review | Coursera

Machine Learning by Andrew Ng is the most sought Massive Open Online Courses (MOOC) for data science on Coursera. The average rating of 4.9 out of 5, given by 148,147 learners speaks this course popularity.

Machine Learning by Andrew Ng Review

Planning to take Machine Learning by Andrew Ng Professional Certificate Course? Still have queries about the Course details, Financial AID, Reviews, then you were in the right place. In this post, we will be covering all your queries.

We have gathered all the information to check this until the post’s end for Cost, Reviews, Testimonials.

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About Machine Learning by Andrew Ng course

Course Details
Additional Details

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you’ll learn about not only the theoretical underpinnings of learning but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you’ll learn about some of Silicon Valley’s best practices in innovation as it pertains to machine learning and AI.

This course provides a broad introduction to machine learning, data mining, and statistical pattern recognition.

Topics covered in Machine Learning by Andrew Ng :

(i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).

(ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).

(iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications so that you’ll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.

Additional Details

Completion CertificateYes
Content TypeAssignment, Ebook, On-demand video, Other downloadable Content, Practical Projects, Slides
Course DurationSelf Paced
Course LanguageEnglish
Cousre AccessTill course completion
Personal Career CoachNo
SubtitlesFrench, Chinese (Simplified), Russian, English, Hebrew, Spanish, Hindi, Japanese
Technical Mentor SupportNo
Andrew NG Machine Learning videos

This is the best course I have ever taken. Andrew is a very good teacher and he makes even the most difficult things understandable. A big thank you for spending so many hours creating this course.



  • This course will cover Linear and Logistic Regression, Vectorisation, Regularisation, Neural Networks, Feedforward and Back Propagation (this is very good), Cost Functions, Network Initialisation, SVMs, Dimensionality Reduction, Supervised/Unsupervised Learning, Principal Component Analysis (PCA), K-Means Clustering, Anomaly Detection, Recommender Systems and much more.
  • Logistic Regression
  • Artificial Neural Network
  • Machine Learning (ML) Algorithms
  • Machine Learning

Course Pricing

Purchase Course ·  60$

Commit to earning a Certificate—it’s a trusted, shareable way to showcase your new skills.

Full Course, No Certificate

You will still have access to all course materials for this course.


Andrew NgInstructor 

CEO/Founder Landing AI; Co-founder, Coursera; Adjunct Professor, Stanford University; formerly Chief Scientist, Baidu and founding lead of Google Brain

Courses Content and material

This course covers the complete syllabus of the Machine Learning. The learner will get access to the course content in the form of lecture videos, PDF readings, lecture slides, assignments, and quiz.

There will be assignments in each course that will need to be completed to pass the course. In Coursera courses, the peer review assignment model is used in which fellow learners will evaluate each other assignment and give feedback.

The learner can also participate in the discussion forum where questions related to courses are being answered. The forum is very useful to clear doubts and get feedback from fellow learners.

Offered by

To get the certificate, learners will need to complete courses infc6g this module. The certificate is issued by the Stanford University

Machine learning by Andrew Ng Certificate

To get the certificate, learners will need to complete 11 weeks of course content. The certificate is issued by Stanford University.

The Coursera modules do not bear credits. However, some universities or organizations may consider a specialization course for credit. You will need to contact the university to confirm it.


Amazing skill of teaching and a very well structured course for people to start to learn to machine learning. The assignments are very good for understanding the practical side of machine learning.

Abdul Q


Machine learning by Andrew Ng

Editorial team



An excellent, all-round foundation to machine learning.
Covers a wide range of ML methods
Is not afraid to tackle the mathematics and Andrew Ng is excellent in teaching the intuitions
A significant portion of the course focuses on Neural Network fundamentals
Amazing coverage of how to actually apply methods and typical pitfalls of most ML engineers


Wish you the best in your journey and hope you emerge successful sooner than later ?


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