Machine Learning for Data Science and Analytics

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6/10 stars
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edX online courses
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Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with edX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be taught by David J. Malan, a senior lecturer on computer science at Harvard University for the School of Engineering and Applied Sciences. But there's not just one professor - you have access to the entire teaching staff, allowing you to receive feedback on assignments straight from the experts. Pursue a Verified Certificate to document your achievements and use your coursework for job and school applications, promotions, and more. EdX also works with top universities to conduct research, allowing them to learn more about learning. Using their findings, edX is able to provide students with the best and most effective courses, constantly enhancing the student experience.

Provider Subject Specialization
Sciences & Technology
Business & Management
23485 reviews

Course Description

Machine Learning is a growing field that is used when searching the web, placing ads, credit scoring, stock trading and for many other applications.

This data science course is an introduction to machine learning and algorithms. You will develop a basic understanding of the principles of machine learning and derive practical solutions using predictive analytics. We will also examine why algorithms play an essential role in Big Data analysis.

Machine Learning for Data Science and Analytics course image
Reviews 6/10 stars
3 Reviews for Machine Learning for Data Science and Analytics

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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.

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Birgit profile image
Birgit profile image

Birgit

2/10 starsDropped
2 years, 3 months ago
"Data Science for Executives…is perfect for anyone who wants to understand basic concepts in data science without getting into the weeds of programming. Aimed at organization leaders, business managers…” – Definitely not, this is a course for professionals with according technical and mathematical prerequisites. I appreciated the dedication with which all teachers held the courses and I am sure they are very smart in their individual subject matter. However, the communication was in no way target group oriented. The target group – as described in the course intro – is not the one who is doing the calculations and programming work. They need to understand the basic ideas, technologies and methods in a mere descriptive way and in order to understand the product professionals in the company. Business managers themselves think in patterns, pictures and stories against the background of time pressure and this influences how they expec... "Data Science for Executives…is perfect for anyone who wants to understand basic concepts in data science without getting into the weeds of programming. Aimed at organization leaders, business managers…” – Definitely not, this is a course for professionals with according technical and mathematical prerequisites. I appreciated the dedication with which all teachers held the courses and I am sure they are very smart in their individual subject matter. However, the communication was in no way target group oriented. The target group – as described in the course intro – is not the one who is doing the calculations and programming work. They need to understand the basic ideas, technologies and methods in a mere descriptive way and in order to understand the product professionals in the company. Business managers themselves think in patterns, pictures and stories against the background of time pressure and this influences how they expect to receive information – hence bring information to the point otherwise they will not lend you their ear. I started the course for curiosity and for the fun of learning. May aim was to get a receipt of “participation”, I don’t need a “successful pass”. However, now at the end of the course I see that this is not possible. So I cannot even mention this course in my CV. That’s disappointing. Maybe my comments sound a bit harsh - I don’t want to blame anyone but I really would have liked to benefit from your hard effort in this obviously very interesting matter.
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Greg Schreiter profile image
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Greg Schreiter

5/10 starsCompleted
3 years, 11 months ago
This course was just okay - I would recommend it only as an introduction for absolute ML newbies. It is basically just a survey course that has no programming assignments - the descriptions of "what you'll learn" are a bit dishonest in light of this. Also, only 2 out of the 5 weeks actually cover ML topics. There are many courses out there that are better than this one.
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student

8/10 starsCompleted
4 years ago
I think that the content of this course was superior to that of the other course, Statistical Thinking for Data Science and Analytics. Unfortunately, I had to go over data structures and algorithms - two topics which I'm fairly familiar with, but I guess the overview kept me up to speed in any case. Otherwise, most of this information in this course I found to be brand new. I think that I have a very good conceptual grasp of not only which machine learning methods are out there but how some of them work and what they're good at doing. I think that this was an excellent course for anyone who's interested in machine learning and needs somewhere to start. I don't have any prior experience in machine learning other than some articles on the internet and a high school background in computer science. I found the professors in this course more interesting or funny than the ones in Statistical Thinking, so that was a plus as well, although t... I think that the content of this course was superior to that of the other course, Statistical Thinking for Data Science and Analytics. Unfortunately, I had to go over data structures and algorithms - two topics which I'm fairly familiar with, but I guess the overview kept me up to speed in any case. Otherwise, most of this information in this course I found to be brand new. I think that I have a very good conceptual grasp of not only which machine learning methods are out there but how some of them work and what they're good at doing. I think that this was an excellent course for anyone who's interested in machine learning and needs somewhere to start. I don't have any prior experience in machine learning other than some articles on the internet and a high school background in computer science. I found the professors in this course more interesting or funny than the ones in Statistical Thinking, so that was a plus as well, although this could be skewed by the fact that I knew less about the material at hand than I did with Statistical Thinking.
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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.