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Bewertung und Feedback des Lernenden für Exploratory Data Analysis for Machine Learning von IBM

4.6
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739 Bewertungen
170 Bewertungen

Über den Kurs

This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing. By the end of this course you should be able to: Retrieve data from multiple data sources: SQL, NoSQL databases, APIs, Cloud  Describe and use common feature selection and feature engineering techniques Handle categorical and ordinal features, as well as missing values Use a variety of techniques for detecting and dealing with outliers Articulate why feature scaling is important and use a variety of scaling techniques   Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience  with Machine Learning and Artificial Intelligence in a business setting.   What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Calculus, Linear Algebra, Probability, and Statistics....

Top-Bewertungen

AE

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.

ML

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.

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151 - 174 von 174 Bewertungen für Exploratory Data Analysis for Machine Learning

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

G​ood 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

B​etter 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

Good content.

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.