Chevron Left
Back to Machine Learning with Python

Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7
stars
15,281 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:

1976 - 2000 of 2,670 Reviews for Machine Learning with Python

By Hiral

•

Aug 1, 2023

The course explains all the basics of Machine Learning in very simple and easy language; even the statistical and advance mathematic concepts are explained simply and graphically & also only as much in depth as needed to understand the ML algorithm properly.

Thanks!

By joe b

•

Oct 13, 2020

Working with the IBM notebook for the final assessment was a bit of a pain

And the peer assessment has no recourse, someone marked me down for something i had, i guess they didnt notice? but i dont have an easy way of getting that changed

Content is good stuff though

By Pratyush R

•

Feb 28, 2022

Very Good Crash Course. Concepts are explained efficiently without wasting much time on the Mathematical/Statistical stuff. Awesome Notebooks are given to code along with the concepts which is really helpful. Must learn deeper and further to become a Professional.

By Martin E

•

Apr 2, 2020

Content was good, but mainly classification. I was missing other aspects (like regression, deep-learning, ...). What really annoyed me a lot was the constant advertisement of the IBM infrastructure; for this course the IBM Watson thingy is largely overblown imho.

By ankit s

•

Jul 22, 2022

Reason for giving 4 rating

1) Proper explaination of all models & its concept

2) Exercise is good ,but you need to understand the python properly

Reason for deducting 1 rating-

1) No explaination about preprocessing of dataset

2) No pdf is given for future reference

By andrew r

•

Nov 16, 2020

Covers the basics and explains clearly the difference between regression and categorization. Lab work was instructive. Some of the material is now out of date, contains grammatical and spelling errors, and has inconsistencies with instructions and testing.

By Tauseef A

•

Jun 2, 2021

The hands on lab are not worth it, there is very less explanation about why we are doing particular step, take for eg final peer graded we just put Boolean value based on just the attribute value of master or above. Very poor last project to be honest.

By John V H

•

Nov 14, 2019

I liked the course overall. Some of the lectures did not break down real world data sets or examples as much as I would have liked. Additionally, it would be nice to have more real world data set examples or tutorials to study or analyze with Python.

By Michael L

•

Oct 23, 2019

The labs are great and the videos are spot on. However, there are numerous typos here and there and also the final project grading rubric had some issues and did not provide some people with guidance and submissions that were correct were marked wrong,

By Rick K

•

Feb 22, 2022

The course information was good. I wish the videos would have touched on the pythonic code for these examples, even just a little bit. The bad was that the labs were down through the majority of my class which made it difficult to see the python part.

By Saif E

•

Nov 19, 2023

I recently completed the "Machine Learning with Python" course, and I must say it has been an incredible journey. The course content, structure, and the hands-on approach make it a standout choice for anyone diving into the world of machine learning.

By PEDRO L S S

•

Aug 7, 2020

All classes was very well designed and structured. In my opinion was the best course I done by coursera. The inconvenience was due to IBM Watson. The Lite service plan offers 50 free hours of free use and I received 10 as the time limit.

Thank you.

By Miele W

•

Dec 21, 2019

A very good course to grasp the foundamentals of Machine Learning using python. Besides the math explanations, i reccomend to have at least a basic knowledge of python, in order to explore the jupyter labs which, in my opinion, are solid examples.

By Sean L

•

Aug 31, 2020

Really interesting course. I would have enjoyed if it went into more depth in some of the topics, for example being more specific with certain algorithms. Would also have liked a peer graded assessment on multiple topics (not just classifiers).

By Tom C

•

Aug 12, 2021

Excellent overview of machine learning in Python. Only reason I didn't give it a 5 is because I would have liked a little more content introducing more of the sklearn library in order to be better prepared for working on the project correctly.

By Karthik C

•

Aug 4, 2019

Hi all.I am so glad to participate this course this course provide me the practical exposure of the machine learning.And Add a credit to my resume and increase the ability to build a "ML model". Great and earn a certificate.from IBM is worthy

By C P

•

Sep 17, 2020

This was the meat of the IBM data science course set for me, and was really very informative. Extremely well presented and clear. I would have liked a bit more depth in this material, with a bit less emphasis on python/sql/tools issues.

By Ramakrishnaprasad

•

Dec 17, 2019

The Course is very valuable content for beginners and easy to understand, the explanation is very good with simple words and live examples. i had refereed this course to my friends to improve their technology stack, their feeds is also good.

By Olivia D

•

Jul 16, 2020

More interactive questions for the programming exercises. Also, the peer marking has room for error since we can't always identify mistakes in others code easily. A code that checks answers for each point and gives feedback would be better.

By Sankha C

•

Feb 22, 2019

Good introductory course for people to start off with Python. This course touches upon various aspect of the coding language and the lab environment made it easy to practice things. Looking forward to such informative courses going forwards

By Apostolos E

•

Aug 29, 2023

The theory is very well explained with nice examples. However the course doesn't explain very well how to use python. You can only open the Jupiter notebooks without providing explanations for the various steps and orders that are used.

By stephane d

•

Feb 1, 2020

4 stars = Great Course!

missing start = Cloud Management / course interrupted because of month credit expired, expected promo code never available...

Suggestion : Cloud "Assets" available for the entire course without a stupid limitation

By DINESH K K

•

Apr 7, 2020

All over about the course is good but little bit math behind the algorithm was not explained (iterative) and implementation with python also not discussed. Over all you will get to learn many things from this course.

Thanks

All d best

By Binod M

•

Jun 29, 2020

I was not satisfied with the way my final assignment was graded wrongly without any feedback. But overall the course is definitely helpful in introducing machine learning concepts with implementation using popular python libraries

By عبدالحليم أ

•

Sep 4, 2023

The course is great and has much basic information about machine learning. But, I think it would be better if labs were graded. I personally, didn't put a sufficient effort in them, although I think they are the most important.