Chevron Left
Back to Machine Learning with Python

Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
16,914 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 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:

2751 - 2775 of 2,952 Reviews for Machine Learning with Python

By Pedro V

•

Jan 10, 2022

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

By its m

•

Jan 21, 2025

Coding part wasnt discussed in videos and it was left upto us to read and understand from lab exercises

By Kiran V

•

Sep 3, 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 冷茗彬

•

Mar 1, 2025

Mathematical explanation is not enough. But it is a good course for general overview.

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.

By Asavari P

•

Feb 26, 2021

Good learning, but very fast paced. A little more practice assignments would help

By shankar p

•

May 27, 2020

Watson Studio was not enough explained. extremely difficult to work on it.

By Jayesh M

•

Jan 27, 2020

Too complex course, some one will do not understand many things out of it.

By Jofre T C

•

Aug 5, 2024

I have ended the course with Honors and is not visible on my certificate

By Abdulwahab A

•

Apr 3, 2020

Was not easy to use the code on my local machine.

I was using spyder IDE

By VRS

•

Jul 24, 2019

Should be an extensive course.The coding part should be explained more.

By Scott M

•

Dec 6, 2020

Course content was good however the final assignment was confusing.

By Dani S P

•

Mar 7, 2025

Some materials contain errors, and the libraries are bit outdated.

By UWIMANA L

•

Jun 17, 2024

I liked the course, but at times, I felt like I had less practice.

By Madhurima M

•

May 20, 2020

Lab works are not well explained. Otherwise, it's a great course.

By Chen Y

•

Mar 27, 2019

The lectures that are longer than 5 minutes are hard to tolerate.