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Bewertung und Feedback des Lernenden für Datenanalyse mit Python von IBM

4.7
Sterne
14,423 Bewertungen
2,139 Bewertungen

Über den Kurs

Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Datasets 2) Cleaning the Data 3) Data frame manipulation 4) Summarizing the Data 5) Building machine learning Regression models 6) Building data pipelines Data Analysis with Python will be delivered through lecture, lab, and assignments. It includes following parts: Data Analysis libraries: will learn to use Pandas, Numpy and Scipy libraries to work with a sample dataset. We will introduce you to pandas, an open-source library, and we will use it to load, manipulate, analyze, and visualize cool datasets. Then we will introduce you to another open-source library, scikit-learn, and we will use some of its machine learning algorithms to build smart models and make cool predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....

Top-Bewertungen

SC
5. Mai 2020

I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.

RP
19. Apr. 2019

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

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2001 - 2025 von 2,133 Bewertungen für Datenanalyse mit Python

von Juan S A G

20. Aug. 2020

very simple exercises which does not help to learn altough videos were exeptional

von Mohsen R

16. Juni 2020

The course does not explain the processes enough, there should be more examples.

von Maciej L

16. Mai 2019

Too many complicated things happening at once. It is hard to digest and follow.

von Tomasz S

19. Nov. 2018

Few small hiccups with the training videos and quite a few in the lab-excercise

von Steven B

3. Juni 2020

Overall I felt it was not broken down very well and seemed confusing at time.

von Pierre-Antoine M

19. Feb. 2020

Videos are nice but they are mistakes in the notebooks that disturbs learning

von Toan N

27. März 2020

The lab is disconnected every so often that can't complete it smoothly.

von Jessica B

14. Juni 2019

Good content, but lots of typos. The outsourcing is extremely evident.

von Arjun S C

14. Aug. 2019

Lots of bugs and errors. No instructors reply on the discussion forum.

von Anvit S

13. Mai 2020

Could have been more detailed....Important concepts just brushed thru

von Holly R

16. Apr. 2020

Could use some better mathematical description of the techniques.

von Filippo M

27. Sep. 2019

Useful course, but the IBM online platforms are not working well.

von Robert P

17. Mai 2019

Some concepts were quite confusing and not that well explained.

von Atharva Y

23. Jan. 2020

As compared to other courses this course seems to be too fast

von Nirav

26. Juni 2019

Lot's of errors in this course, please update and correct it.

von Anmol P

14. Okt. 2019

Course could have been more elaborate in depth and scenarios

von Tichaona M

5. Aug. 2020

This is a great course for building the base to use Python!

von 林tanya

27. Dez. 2019

the lab is extremely useful, however, videos are too short

von Michael A D R

1. Nov. 2019

Extremely interesting BUT it gets long and hard to follow.

von Nihal N

18. Apr. 2019

not in depth.... needs more clarity on a variety of topics

von Alejandro A S

25. Juli 2019

Experimented a lot of problems to complete the assignment

von Troy S

14. März 2019

Quizzes are too easy. Don't even need to watch the videos

von Anurag P

18. Jan. 2020

Mostly theoretical; very little to implement on our own.

von Pulkit D

29. Juni 2019

Please update and explain Rigid Regression a little more

von Appa R M

24. Okt. 2019

The kernal is stuck for some questions and its annoying