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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
17,141 ratings

About the Course

Python is one of the most widely used programming languages in machine learning (ML), and many ML job listings require it as a core skill. This course equips aspiring machine learning practitioners with essential Python skills that help them stand out to employers. Throughout the course, you’ll dive into core ML concepts and learn about the iterative nature of model development. With Python libraries like Scikit-learn, you’ll gain hands-on experience with tools used for real-world applications. Plus, you’ll build a foundation in statistical methods like linear and logistic regression. You’ll explore supervised learning techniques with libraries such as Matplotlib and Pandas, as well as classification methods like decision trees, KNN, and SVM, covering key concepts like the bias-variance tradeoff. The course also covers unsupervised learning, including clustering and dimensionality reduction. With guidance on model evaluation, tuning techniques, and practical projects in Jupyter Notebooks, you’ll gain the Python skills that power your ML journey. ENROLL TODAY to enhance your resume with in-demand expertise!...

Top reviews

FO

Oct 9, 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.

RC

Feb 7, 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.

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251 - 275 of 3,001 Reviews for Machine Learning with Python

By Vamsi K

•

Oct 17, 2021

Very nice course. I was able to get the basic idea of machine learning after completing this course. Hope I will be able to build upon what I have learned here. Thanks to course instructors and all the people who are behind this course.

By kiran v

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May 4, 2020

This is one of the best machine learning courses i have taken with good practicals and nice examples. Moreover the instructor was good and has a funny way of talking which i enjoyed. Overall a full score worthy course. Keep it up IBM!!

By Felix F

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Mar 29, 2021

I really liked the flexibility of this course. It worked well with busy scheduling, and the expectations were clear and upfront. A great introductory course on machine learning that makes me eager to continue with the specialization.

By Oksana Z

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Jun 6, 2020

This course is exceptional in IBM Data Science Professional Certificate Program. It provides newcomers with the ready-to-use tools in machine learning. I especially liked the part on recommendation systems and wish it had more content!

By Abhijit H J

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Dec 15, 2019

The course was awesome, I got a good understanding of the ML algorithms. If the explanation would have been along with the python code, then it would have been better for understanding.

But still, I must say the course was just awesome.

By Jafed E G

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Jul 6, 2019

I enjoy the lectures. The professor has a good speaking and teaching style which keeps me interested. Lots of concrete math examples which make it easier to understand. Very good slides which are well formulated and easy to understand

By Edward J

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Aug 12, 2020

Loved the video and loved the exercises. My only criticism would be greater opportunities to practise the coding in the labs rather than just actioning the code already given - I guess that might be more specialist though. Thank you.

By Rupam H

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Jun 16, 2020

Gone through so many courses but didn't find like this before. This course is too good. As an intermediate, I can say that this course described very complex topics in such a easy way making it very much understandable for beginners.

By Chandan K S

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Apr 26, 2020

For absolute beginners, this course is really amazing. If anyone don't know anything or any algorithms of machine learning. Then this course is for them. So, i would like to say for beginners this course is really amazing. Thank you!

By YASH G

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Feb 18, 2020

The course was helpful and the final assignment was very good. You have to go through all of the concepts again. But it would be great if assignments would be different for everyone, then validating part would be interesting as well.

By Mahdi G

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Jun 27, 2023

Really it is Worthfull Course. Helpfull Training Method. Nice Videos & Specially The Labs Are Worthfull & Helpfull.

I extend my thanks and gratitude To Coursera & IBM To give me chance learning. i Say Best Wishes & Regards. u r great

By Petros L

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Sep 23, 2020

Very well structured and interesting course! Would be nice if you could include a small introductory section about Python code basics, in order for the code, that would be later used during the course, to be much easier understood.

By ong k s

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Nov 13, 2019

Awesome machine learning course. Unlike most of other courses which come with technical mathematic jargon, this course explain everything in laymen term. Even myself without in depth knowledge in maths can understand it. Well done.

By Robert v d V

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Jul 14, 2020

Overall good introduction to machine learning, it would be nice for the final assignment to create some kind of test to see if everybody understands the concepts. Now the course is passable with copying code of the previous weeks.

By Omid C

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Feb 27, 2020

The course provides an excellent overview of some essential algorithms in the field of Machine Learning. The instructor has the ability to explain the core idea of each algorithm in an intuitive way. I liked the course so much :)

By Nazmus S S

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Apr 8, 2020

This course is awesome in one word. This course is great for learning the classification algorithms in such an ease with all the power these algorithms possess. I loved the way instructor SAEED AGHABOZORGI instructed the course.

By Ashish B

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Feb 2, 2020

This is a very informative course. The content is amazingly put together. Not only is this course rich in concepts of Machine Learning, but it is also robust in the implementation of ML with Python. This course is a must-read!

By АнГрей Š›

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Aug 5, 2019

Thank you very much. It was not easy, but very interesting to learn, to create and to code.

This course, especially its practice part got me deeper understanding what else I should to learn and read about.

Thank you! Good luck!

By Aurora S P

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Jan 10, 2022

Very interesting course. What I like the most are the practial exercises, which can be easily followed and you can always play with them trying different cases by your own. The theory is also very well organized. Thank you!

By Anirban M

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May 23, 2020

Teaching was good but since the title refers ML with python expected more deep dive with some ML associated libraries in python and implementation. The course was more over Theoratical but good for the beginners.

Thanks alot

By Joe A

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Feb 10, 2020

I enjoy this course - the content, the pace and the Notebook exercizes. It didn't bog me down and gave me a great insight into what Supervised and Unsupervised ML entails. I have lots to learn and practice ahead. Thank you.

By Arnold K

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Apr 7, 2020

this is an intermediate level but it blends in well with beginner's basics, allowing even people with less experience or perhaps only theory to jump in right away. Also makes foundation for advanced level. i recommend it.

By Thanh N N

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Mar 22, 2019

Amazing course. I learnt a variety of machine learning model here. Complete the course, I feel confident in understanding and applying them. It is also the foundation for me in further learning of machine learning. Thanks!

By Manuel C C

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Apr 15, 2025

Detailed explanation of topics. Good balance between theory and practice. Real-life use cases with real-world data. Some minor issues related to library versions should be taking into account or addressed by instructors.

By Venkata S M I

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Nov 2, 2019

The course content provides a great insight into how we can create different types of models using Machine Learning algorithms. This is the best place to start if you want to really pursue a career towards Data Science.