26. Sep. 2021
Very detailed course of Exploratory Data Analysis for Machine learning. Ready to take the next step in data science or Machine learning, this is great course for taking you to the next level.
21. Sep. 2021
Excellent, very detailed. However, if the lessons can be expand for hypothesis testing and some of their common test like T test, Anova 1 and 2 way, chi square,..it would be better further.
von Medha J•
14. März 2022
Very Nice course , will teach you in detail all the techniques of EDA with practical code.
von Aravind S•
11. Apr. 2022
Was able to learn and practice many topics in this course. Very useful for Data Analysis.
von Sebastian N•
16. Mai 2022
Good instructor, good knowledge level, minor mistakes in some of the notebooks provided.
von Joseph F•
2. Mai 2022
Good introduction. Quiz questions mostly on terminology and not understanding.
von Roberta D•
13. Apr. 2022
Very interesting course, good for getting ideas to deepen the topic!
von Daren L P•
27. Juni 2022
I enjoyed the course, the example code/labs were awesome
von Olivier F•
7. Okt. 2021
Good introduction and Exploratory Data Analysis course.
von CHIARA B•
18. Sep. 2021
A good background in math and some python is needed.
von Miguel D•
12. Mai 2021
I wish the hypothesis part was a bit more detailed
von DONG C•
9. Sep. 2021
Better than other IBM ML certificate series
von Tania L•
19. Okt. 2021
Quite interesting course for beginners
von Chandan K G•
19. Juli 2021
It was nice learning experience.
von OMAR A H H•
1. Nov. 2020
Very well structured
von Pampa D•
18. Apr. 2022
von Hossam G M•
27. Mai 2021
The course material should be provided to allow better absorption of the large amount of information presented. some of the topics needs to be discussed further with more examples and concept declaration especially the hypothesis testing section.
von Gabriel Y H M•
25. Feb. 2021
I liked the course content but I would like a more interactive approach that show us how to do hypothesis testing in python. The teacher just reads the courses.
von Azmine T W•
16. Apr. 2022
I think, instructor went too fast in many cases. Some topics needs to be restructured with more real life examples and interpretations.
von Simon N•
19. Apr. 2021
I do like the course in generall. But some slides, are very text heavy, which i do not prefer.
von Busola A•
29. März 2022
The videos are not well explanatory enough.
von Oleg O•
25. März 2022
This course is too surface. You must have a solid background in statistics and be familiar with pandas/numpy python libraries, otherwise you will spend a lot of time just to learn these libs. Also there is some basic info in lectures but assignments contain much complex and harder tasks which were not discussed in the lecture. And the tasks already have answers , so there are questions and solutions in one place, it is very weird and annoying
von Stephen C•
3. Jan. 2022
Frankly, the presenter is a poor educator and the course materials are weak. The examples are limited, some explanations verge on incorrect (description of p-values), and several of the graded test questions are ambiguous and encourage rote learning of the teacher's preference/positions, rather than testing the underlying concepts. I expect better from IBM.
von Dimitrios T•
13. Juni 2022
Poor explanation of many concepts. Felt i the instructor was reading the material in a neutral manner and was not emphasizing on key moments. Also lack hands on opportunities and practice to help understand the concepts.
Overall seemed more like a summary of various titles and definitions.
von Mpho M•
1. Dez. 2020
Course videos are way too long.
No Jupyter support, so for the coding exercise one has to download the notebooks and either use Google Colab or locally installed Jupyter notebook.
von Walter c•
14. Juni 2021
The course starts well. Then it goes to statistics and not so much to machine learning. The assignment is not so geared towards machine learning.