26 de set de 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 de set de 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.
por CHIARA B•
18 de set de 2021
A good background in math and some python is needed.
por Miguel D•
12 de mai de 2021
I wish the hypothesis part was a bit more detailed
por DONG C•
9 de set de 2021
Better than other IBM ML certificate series
por Tania L•
19 de out de 2021
Quite interesting course for beginners
por Chandan K G•
19 de jul de 2021
It was nice learning experience.
por OMAR A H H•
1 de nov de 2020
Very well structured
por Pampa D•
18 de abr de 2022
por Gert-Jan D•
29 de jul de 2022
Potentially this is a great course, but it falls short on a number of points.
* Content is mixed and/or duplicated
* Lab exercises are mostly just demo's. The video's 'explain' no more than you can read in the notebooks.
* The videos show a 'talking head' that is clearly reading the text from a screen. Not very engaging.
* The explanations are not very clear.
It is possible to learn from this course, but then you will have to work on the demo's yourself (deleting the answers first) and read more clear explanations on the topics from other sources.
por Hossam G M•
27 de mai de 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.
por Gabriel Y H M•
25 de fev de 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.
por Azmine T W•
16 de abr de 2022
I think, instructor went too fast in many cases. Some topics needs to be restructured with more real life examples and interpretations.
por Alexander D•
7 de ago de 2022
Exam questions are phrased very poorly in a lot of cases and often don't do a good job of assessing what was taught.
por Simon N•
19 de abr de 2021
I do like the course in generall. But some slides, are very text heavy, which i do not prefer.
por Busola A•
29 de mar de 2022
The videos are not well explanatory enough.
por Oleg O•
25 de mar de 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
por Stephen C•
3 de jan de 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.
por Mpho M•
1 de dez de 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.
por Walter c•
14 de jun de 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.
por Brinda p•
26 de jul de 2022
i purchased whole machine course but after payment i can only able to access 1 course among all 6 and they ask me to pay extra for another 5 course.
por Eman A•
1 de ago de 2022