6. Feb. 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.
8. Okt. 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.
von OLENA S•
8. Apr. 2021
The course is very useful for the beginner as me. It contains a good math explanation of ML methods. The technical Python part in labs is good enough too for the beginner in Python/ Sometimes it don't correspond fully to the math part but it isn't critical. Thanks for the course!
von Edwin S•
25. Mai 2020
Good course syllabus. Some improvements needed: Jupyter notebooks contain many English typo errors. The final assignment rubric uses the wrong normalization technique for the test data where test data were normalized by itself instead of training a scaler with the training data.
von Fabrizio D•
20. Juni 2020
I noticed some (not critical) mistakes here and there during the video lectures and the quizzes.
Over all, a good course, but I think in order to gain a full understanding of the material one needs to look deeper into the literature. The course provides a good starting point.
von joe b•
13. Okt. 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
von Pratyush R•
28. Feb. 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.
von Martin E•
2. Apr. 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.
von andrew r•
16. Nov. 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 Some of the material is now out of date, contains grammatical and spelling errors, and has inconsistencies with instructions and testing.
von Tauseef A•
2. Juni 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.
von John V H•
14. Nov. 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.
von Michael L•
23. Okt. 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,
von Rick K•
22. Feb. 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.
von PEDRO L S S•
7. Aug. 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.
von Miele W•
21. Dez. 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.
von Sean L•
31. Aug. 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).
von Tom C•
12. Aug. 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.
von Karthik C•
4. Aug. 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
von Cynthia P•
17. Sep. 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.
17. Dez. 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.
von Olivia D•
16. Juli 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.
von S C•
22. Feb. 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
von stephane d•
1. Feb. 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
von DINESH K K•
7. Apr. 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.
All d best
von Binod M•
29. Juni 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
von Phalin D•
2. Juni 2020
The content in the course is very detail and clear. They illustrate each time difference technique where we can use in machine learning. Though, I found the exercise in are a little bit easy, but it's help a lot with learning.
von Venkatesh K•
3. Juni 2020
Best course to understand basic working of all algorithms. Assesments are goof for fresher and looks easy if one knows already. Ensemble techniques should also be included in this such as RandomForest and Boosting Algorithms.