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Bewertung und Feedback des Lernenden für Datenanalyse mit Python von IBM

14,243 Bewertungen
2,110 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....


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.

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.

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1951 - 1975 von 2,104 Bewertungen für Datenanalyse mit Python

von Marc T

3. Feb. 2020

why is sharing of the notebook worth 3 points? That has absolutely nothing to do with python or data analysis!

von Abhishek K

26. Aug. 2019

Model creation and analysis part are too short, should have more details to understand the concepts better.

von Sarah s

2. Jan. 2019

This course seems to have an exponential increase in a learning curve. It seemed to be all over the place.

von Ramakrishna B

19. Juni 2019

More explanations would be great. Its very difficult to understand Data exploration / evaluation sections

von Camilo P T

15. Juni 2020

Creo que le hace falta unas guías, toda la información se da por videos. Recomendado para principiantes.

von Kenneth S

12. Jan. 2020

As always, the final project always ruins good courses. LAZY design of the projects is unacceptable.

von Bjoern K

14. Juni 2019

Week 4 is somewhat hard to follow - Here, an overview over the different concepts would really help

von Nadeesha J S

11. Apr. 2019

I would like to see a final project in this course. It will encourage the learners to do more work.

von Edward S

2. Aug. 2020

The week 4 lab had issues with pipelines and did not function well and the final exam locked up.

von Miguel V

12. Nov. 2020

Needs more information on statistical tests. Specifically, when to use one model over another.

von Poorna M

24. Juni 2020

Videos in this section could be little more descriptive. It was not in the pace of a beginner.

von Nathan P

1. Jan. 2020

It was cool to see the stuff at work but I need more hands on practice to really learn stuff.

von Varun V

18. Dez. 2018

This looks good for experienced but not the best of course for beginners/intermediate level.

von Connor F

27. März 2020

when it got to model development it got too complicated too fast. The first half was great.

von Badri T

28. Mai 2019

Lots of good concepts. However, too complicated and could have been explained a bit more.

von Jesse Z

5. Juni 2019

For such a important topic, it seems like the videos sped through some essential topics.

von Debra C

24. März 2019

Course was worthwhile for general understanding of what can be accomplished with Python.

von Mil Á

13. Mai 2020

Exelent training to get familiar and intruducing to Python capabilities and programing

von Xinyi W

26. Jan. 2020

Superfacial level of Python while being not very through on the data analysis methods.

von Ana C

11. Juni 2019

To short

Goes to fast in some aspects, the theory is completely missing in this course

von Sathiya P

27. Aug. 2019

Nicely thought, but I felt concepts like Decision trees, Random forest were missing

von Rosana R

12. Aug. 2019

The course is too long. The material should be divided and explained more detailed.

von Amanda A

16. Apr. 2020

There were many typos in the labs which made it difficult to understand at points.

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.