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.
About this Course
Learner Career Outcomes
Approx. 56 hours to complete
Learner Career Outcomes
Approx. 56 hours to complete
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.
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TOP REVIEWS FROM MACHINE LEARNING
It's a good introduction - not too complicated and covers a wide range of topics. The programming exercises are well put together and significantly help understanding. The free Matlab license is nice.
Everything is taught from basics, which makes this course very accessible- still requires effort, however will leave you with real confidence and understanding of subjects covered. Great teacher too..
Very nicely explained the mathematical topics, even for people like me with some phobia regarding large formulas. Useful hands-on experience with MATLAB coding, which I would have had to learn anyway.
this course is very basic. does not explain the concepts in details. Course instructor is very nice.\n\nLooking forward for a course in depth of machine learning and related algorithms from Andrew ng.
Andrew Ng is a great teacher.\n\nHe inspired me to begin this new chapter in my life. I couldn't have done it without you\n\nand also He made me a better and more thoughtful person.\n\nThank You! Sir.
Great explanation of each topic. However i felt the course is little outdated and it would have been better if it has topics related to python/R algorithm class libraries and algorithm implementation.
This course is amazing and covers most of the ML algorithms. I really liked that this course has emphasized math behind each technique which helps to choose the best algorithm while solving a problem.
Very well structured and delivered course. Progressive introduction of concepts and intuitive description by Andrew really give a sense of understanding even for the more complex area of the training.
This is course just awesome. You get everything you wanted from this course. It covers on all topics in detail, helps in getting confidence in learning all the techiques and ideas in machine learning.
Very helpful and easy to learn. The quiz and programming assignments are well designed and very useful. Thank Prof. Andrew Ng and coursera and the ones who share their problems and ideas in the forum.
Amazing course for people looking to understand few important aspects of machine learning in terms of linear algebra and how the algorithms work! Definitely will help me in my future modelling efforts
Enjoyed following the course (videos) and reading notes, resources, discussions as well as doing assignments using GNU Octave (visualizing the results). Well organized. A big thanks to the whole team.
The content is super useful but i think this course need to be recorded again because some materials has more easier ways to illustrate even by Prof Andrew which has illustrate it in deep learning .ai
Amazing course. It gets deep into the content and now I feel I know at least the basics of Machine Learning. This is definitely going to help me on my job! Thanks Andrew and the mentors of the course!
Sub title should be corrected. Since I'm not that good in English but I know when there're mis-traslated or wrong sub title. If you fix this problems , I thin it helps many students a lot. Thanks!!!!!
An amazing skills of teaching and very well structured course for people start to learn to the machine learning. The assignments are very good for understanding the practical side of machine learning.
One of the best course at Coursera, the content are very well versed, assignments and quiz are quite challenging and good, Andrew is one of the best guide we could have in our side.\n\nThanks Coursera
Excellent starting course on machine learning. Beats any of the so called programming books on ML. Highly recommend this as a starting point for anyone wishing to be a ML programmer or data scientist.
Everything is great about this course. Dr. Ng dumbs is it down with the complex math involved. He explained everything clearly, slowly and softly. Now I can say I know something about Machine Learning
Great teaching style , Presentation is lucid, Assignments are at right difficulty level for the beginners to get an under the hood understanding without getting bogged down by the superfluous details.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
Is financial aid available?
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