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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
16,550 ratings

About the Course

Get ready to dive into the world of Machine Learning (ML) by using Python! This course is for you whether you want to advance your Data Science career or get started in Machine Learning and Deep Learning. This course will begin with a gentle introduction to Machine Learning and what it is, with topics like supervised vs unsupervised learning, linear & non-linear regression, simple regression and more. You will then dive into classification techniques using different classification algorithms, namely K-Nearest Neighbors (KNN), decision trees, and Logistic Regression. You’ll also learn about the importance and different types of clustering such as k-means, hierarchical clustering, and DBSCAN. With all the many concepts you will learn, a big emphasis will be placed on hands-on learning. You will work with Python libraries like SciPy and scikit-learn and apply your knowledge through labs. In the final project you will demonstrate your skills by building, evaluating and comparing several Machine Learning models using different algorithms. By the end of this course, you will have job ready skills to add to your resume and a certificate in machine learning to prove your competency....

Top reviews

RC

Feb 6, 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.

FO

Oct 8, 2020

I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.

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2176 - 2200 of 2,878 Reviews for Machine Learning with Python

By CHEN X

•

Jun 25, 2020

This course walks us through the fundamentals of machine learning methods. The capstone project is very useful for those who have previous knowledge of machine learning and Python programming.

By Ashraf S

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Oct 7, 2019

I think PCA would've been a very useful clustering method to teach. AUC are a great way to measure the effectiveness of a logistic regression algorithm, it would've been useful to learn here.

By aaditya r

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Aug 5, 2019

Very nice course with very less time .

But i though there should be some mathematical explanation in detail what i observed there is lack of mathematical explanation.. overall course is good

By Pierre P

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Mar 24, 2020

That course was very instructive and provides a very good start in the field. The instructors could dive a little bit into more into technical details, or give more examples of algorithm.

By Abhishek b

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Dec 30, 2019

its a great journey along with coursera family and very thankful of sponsering such good course.i have enjoyed alot and learning so much from you.its my pleasure to i done this course!

By Jose L B P

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Apr 27, 2022

Great course if you have a previous knowledge in ML and python, because there's not much deepening into every subject. Useful labs to understand the coding, but with not much difficulty

By Ed B

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Mar 27, 2020

Good course to introduce us to the fundamentals of ML. Some of the routines used are becoming deprecated in the notebooks, and there are quite some spelling errors within the notebooks.

By James S

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Nov 19, 2021

The modules and in particular the Labs are good background, pay attention to the optional labs because you are going to need it to complete the final project! :) really good learning

By Francesco C

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Oct 28, 2021

course is a good introduction for people who know 0 about ML (like me). I highly suggest to learn a bit of Pandas, Numpy and Scikit before taking the course, it's highly advantageous.

By mostafa m a

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Jul 22, 2024

I found that this course is very directional toward to understanding the basics of MLs techniques using python's libraries and how I can select the best choice for any phenomena.

By Stefan W

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Jan 22, 2020

Great content, peer review process can be a bit painful if someone has submitted a messy, hard-to-trace notebook with a lot of redundant / incorrect cells obfuscating the work.

By Nur C N

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Jul 20, 2019

Quite good in explanation and structured. Can be better by providing more sample study case and comment in each sample code to provide more explanation. Nice course!!! Thanks.

By Armen M

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Apr 15, 2020

Good course, could have been even better if the coding part was explained in the videos. Instead, it was left to figure out yourself. Still, I appreciate the video lectures.

By Oliver E A B

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Mar 25, 2020

The course has good explanations of the statistical background and is very practical, but it is unclear how good is the final project, you did it wrong? You will never know.

By Hui Y O

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Aug 22, 2020

Easy to understand, step-by-step. The only downside is that there are some bugs found in the lab which cannot be fixed, even many people have already conveyed to the admin.

By André M

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Nov 21, 2020

The content of the course is great and it's very instructive. Although I think that the certificate approval system should be harder and more inspected by the instructors.

By Aatmik J

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May 7, 2020

I think IBM Watson site has been updated after this course was last updated. Therefore, there are some differences in the final project guidance videos and actual website.

By Shubham S

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Jul 27, 2019

A really great course with loads of hands on coding experience. But some concepts need to be explained more deeply. Really happy to complete this & receive a certificate !

By Liam M

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Jan 31, 2019

Good stuff. Useful final project. More in depth research required if you want to actually learn how these algorithms work though - outside the scope of the course I guess.

By ERICK I M E

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Dec 30, 2020

Good course. I think the final project could be more interesting even but the peer review has to be optimized such that it avoids unfair ratings, either for good or bad.

By Carolina B

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Feb 3, 2020

I think more practice exercise with more variety in difficulty would be really help - as well as links to resources to practice key items (like nesting loops in python)

By Pratibha S

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Apr 28, 2020

It is one of the best courses for understanding the basics of Machine Learning. Moreover, it also includes hands on experience with different classifiers on notebook.

By Mihaly K

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Nov 6, 2019

There should be assignments every week, not just quizzes. Too easy to pass this way, not enough practice, at least if you already know the basics of machine learning.

By Brian B

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Dec 14, 2020

Great hands-on practice with many different modeling methods. A fun final project too. Just has a few technical and typo glitches that keep it from a perfect score.

By Sucheta

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Oct 1, 2019

Nicely designed course on ML. All labs are very well structured which help to understand the concepts. Final project is a good test of the lessons learnt in course.