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Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
16,314 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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2226 - 2250 of 2,830 Reviews for Machine Learning with Python

By Santhosh R B

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Apr 7, 2020

Would have been more interactive if the grading was done after each and every week through assignments.

Thank you

By Thiago C

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Apr 13, 2020

The course is good but I will need to start at a beginner level in order to consider reapplying to this course.

By Jorge T

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Sep 23, 2022

An excellent opportunity to get your hands-on Pyhton and its ML libraries. More practical than theoretical.

By Suhan R

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Jan 11, 2020

The course is too short or rather a bit on the lighter side. Expected a bit more heavy and rigorous content.

By Giorgio G

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May 20, 2020

Great Course, Opportunities for improvement: go a little deeper on the algorithms strengths and weaknesses.

By Lakshit .

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Jul 25, 2021

The Content was brilliant but If you can add Reinforcement Learning to this course then it'll be more fun.

By Gabriel C

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Feb 19, 2020

Very comprehensive in terms of topics covered, but could be improved with videos to walk through tutorials

By Christian F

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Jun 3, 2020

Could have covered also Neural Networks and Random forest, but overall it was a very high-quality course.

By VARUN B

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Feb 11, 2020

Need more clarifications about the code in the lab session and the explanation of concepts are Excellent.

By Hichem D

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Jul 11, 2020

the course was awesome, easy to understand even for someone with no prior knowledge in machine learning

By William O

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Jun 24, 2020

Thank you so much!

The content was appropriate for my interests. I learned a lot and it was so accurate.

By Krishna M

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Apr 22, 2019

The course is aptly structured for intermediate learners - just the right level of complexity and ease.

By Abhijit S

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Jan 17, 2022

It's always better to study materials made by IBM. Understandable concepts & great project experience.

By Aditya S

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Jun 29, 2020

More peer graded assignments should be there , so that learners get more practice for building models.

By Brannon C

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Jun 21, 2020

Great overview for many of the key Machine Learning algorithm types using in Python for Data Science.

By ABU H M A R

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Jan 5, 2020

Great course for the fundamentals of different machine learning techniques. Enjoyed this wuite a kot

By Manal C

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Nov 27, 2019

Recommending more emphasis on the coding behind the algorithm (reminders / links to references ...)

By Matthew A

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Jun 14, 2019

This was a good course - but still could use more hands-on exercises to go along with the lectures.

By 018 A D

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May 19, 2020

it was a nice course but there must be a little explanation video of the codes written in the labs

By Brian G

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Jun 17, 2019

Would've liked the labs to be a little less demo and more DIY, but otherwise outstanding material.

By Mitchell H

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May 15, 2020

Covers all the basics of sklearn library. Would have been nice to have more assignments/practice.

By Joseph L

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Jul 24, 2019

I am enjoying the course so far. Very well explained with a pretty comprehensive course material.

By nilay m

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Mar 11, 2019

it was a nice course giving basics of every ML algorithm and i am all in all very much benefited.

By Saptashwa B (

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Mar 4, 2019

The course is pretty good, I just hope the printing mistakes in the slides will be corrected soon

By ADEJOKUN A

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Apr 27, 2020

The underlying concepts of the various algorithms were broken down and delivered with simplicity