As of this article, it has had 2,632,122 users enroll in the course. That is just enrolled in, but unknown if they have finished. It is estimated that 1% — 15% of users who start complete the course.
Full Answer
In my opinion, no doubt Andrew Ng's Machine learning course is the best choice for learning the theoretical aspects of ML, but this course lacks too following features. Visual examples.
Andrew's Course marks your entry to the Machine Learning domain. It's an entry-level program that gives brief domain knowledge. Ng's classes give a good level of learning at a foundation level.
Now, Andrew Ng's lectures are pretty basic, and only gives you a basic idea about some basic knowledge and tools used in ML. IMO, you should go to YouTube and search for Nando de Frietas's lectures. There are two volumes of it: Basic and Advanced. Start with Basic one and build on the concepts and knowledge which you have already learnt.
Tracking down an appropriate course subsequent to completing Andrew Ng's AI course is more fundamental than just taking a course. Thus, to learn Data Science in the ideal manner, You can go to many other reputed courses on Learnbay, Data camp, Edureka, Udemy, etc., which are more useful than Andrew Ng's Course on machine learning.
Andrew Ng's Machine Learning course at Stanford was published in 2011. Andrew Ng's course is still rated as one of the best machine learning courses 8 years after it was published.
Is it worth paying for Andrew Ng's machine learning course on Coursera? Yes absolutely, it is worth every penny. It is one of the best ML courses designed which require no prerequisite knowledge.
I did it one hour a day, six days a week, and it took me six months. I did take good notes and sometimes I would go through the material twice to make sure I understood it.
Congratulations on completing Andrew Ng's Coursera class on Machine Learning! ... Machine Learning is an important part of learning Data Science so if you want to further continue with your studies then pursuing a course in Data Science will be a good idea.More items...
Machine learning course offered at Coursera is the watered down version of original CS 229 offered at Stanford university.
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It's no doubt that the Machine Learning certification offered by Stanford University via Coursera is a massive success. This is undoubtedly in-part thanks to the excellent ability of the course's creator Andrew Ng to simplify some of the more complex aspects of ML into intuitive and easy-to-learn concepts.
Do not forget that the course materials are completely free and you need to pay only for the certificate (standard Coursera fee — about 80 USD).
It is one of the best ML courses designed which require no prerequisite knowledge. Even if you have very little experience in mathematics, you would find it super easy because the course covers all the basic mathematics required. The course starts from scratch and touches most important of concepts of the ML.
1 Answer. NO! you cannot learn Machine learning in one month and even if you did cover the topic, then also it wouldn't be fruitful to you as you might not have grasped the subject's depth and because of lack of practice, you will not be technically strong.
Machine learning courses vary in a period from 6 months to 18 months. However, the curriculum varies with the type of degree or certification you opt for. You stand to gain sufficient knowledge on machine learning through 6-month courses which could give you access to entry-level positions at top firms.
Machine learning is a big business worldwide, and the salaries for machine learning engineers are well worth it. For example, some engineers earn upwards of $142,000, but there is still plenty of demand for deep learning engineers. There's never been a better time to get into machine learning.
Andrew Ng is the co-founder of Google Brain and Coursera, and an adjunct professor at Stanford University. He was also a former vice president and chief scientist at Baidu working on large scale artificial intelligence projects. Therefore, without a doubt, Andrew Ng is one of the most knowledgeable people in the world for teaching machine learning.
Since this is an introduction to machine learning course, very little mathematics and nearly zero statistics background is required. However, people familiar with probability/statistics, vector calculus, and linear algebra will find it a lot easier to understand the formulas and the mathematical derivations. Furthermore, a couple videos are provided between the course for reviewing some basic concepts of linear algebra and manipulations of matrices which would be used in the programming exercises.
On August 15 2011, Stanford professor Andrew Ng uploaded an intro video to YouTube for his free online Machine Learning course. On that same day, The New York Times featured his course (along with two other Stanford courses).
Andrew left Baidu earlier this year to work on his own AI projects. In a post on Medium, he announced that he is working on three different AI projects with Deeplearning.ai being the first one. He describes it as “a project dedicated to disseminating AI knowledge.”
8 million learners have signed up for his Machine Learning course. Andrew Ng is no longer at Coursera full time, but acts as the co-chairman of the board. He left Coursera in May 2014 to join Baidu.
Work when your mind is fit and healthy — there is no need to force your brain to understand deep neural networks when you’re tired, so try to study when you’re feeling energetic and ready to learn
The course is divided into four weeks and three programming exercises.