Chevron Left
Back to Machine Learning with Python

Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
16,540 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

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.

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.

Filter by:

2676 - 2700 of 2,878 Reviews for Machine Learning with Python

By Vibha S

•

Aug 28, 2020

It would have been helpful to have an explanation of t each of the lines in the code, especially the ones that created the graphs.

By Louis C C I

•

Mar 25, 2021

I learned a lot but wish the coding was explained better. The final project could have been better if it had more instructions.

By Rohith P R

•

Apr 24, 2020

Need more clarity while explaining the algorithms. Also need video lectures on the code used in the lab and how the code flows.

By Amal J (

•

Jul 16, 2020

Peer review was problamatic , IBM Watson was tough to grasp could have been more informative .

But the course was really good

By Shankari S

•

Aug 31, 2020

This course covers the basic of major algorithms. It could be useful if they add more examples and more metrics calculation.

By AINUR A

•

Mar 25, 2021

Why am I not eligible to upgrade to a New version of a specification if it exists and I already paid for the next months??

By Manuel D

•

Oct 3, 2023

Basic Mahcine Learning course. It goes through the very basics of several models, but lacks practice and true excercises

By Pratik P

•

May 1, 2023

Was not able to get a clear understanding of the applications of Statistical concept applied in different ML algorithms.

By Bob D

•

Jan 25, 2022

Some useful material, but again plagued by bad spelling, punctuation and technical issues. Nowhere near good enough.

By Diwakar S

•

Apr 19, 2020

a very short video on theory part and without practical example. then we directly jump on notebook assignment.

By Pedro S

•

Nov 16, 2022

I understand that this a introduction course but I believe some things should have been taught in more depth.

By Muhammad S

•

Oct 10, 2022

The answer to questions were very difficult to interpret. The feedback from staff was not very satisfactory

By Raed K

•

Aug 11, 2020

I felt that it needs to be guided more it was tough to take the final project. But thank you for the course

By Pedro V

•

Jan 10, 2022

Rather basic but pretty well explained. I was expecting something more advanced and with much more Math

By Kiran V

•

Sep 4, 2019

Some concepts should be dealt with more explanation (SVM, recommedor system- collaborative filtering)

By Johan

•

Mar 31, 2020

The statistical equations can be explained better to enable better application in the real world.

By Andrew P

•

Jan 17, 2020

Would have preferred more step by step explanations to the process, even if it is in written form

By Dhananjay K

•

May 1, 2020

this course quite difficult to complete. please add some normal application in this course.

By DHAVAL J

•

Feb 26, 2020

Could have been better especially in optimization part and pratical coding in video itself.

By Pablo V V

•

Mar 26, 2019

I prefer a blackboard videos likek Khan Academy. Instructor looks like a robot. But its ok.

By Sokob C

•

Jul 25, 2020

I prefer to have more lab work to help with maintaining what was covered in each section.

By Mike B

•

Aug 30, 2021

some errors in the code. Seemed like a marketing tool for IBM vs. a training session.

By Yunqi H

•

Jul 22, 2019

The course contents are okay. However, the labs and final exam are not well designed.

By Mahan M

•

Oct 13, 2019

very hard compared to the other courses in this data science package, but good info

By Karan S

•

Aug 20, 2024

it was good theoretically, but have could have been better in practical learning.