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Learner Reviews & Feedback for Datenanalyse mit Python by IBM

4,698 Bewertungen
584 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....



Apr 20, 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.


Jul 13, 2018

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

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226 - 250 of 581 Reviews for Datenanalyse mit Python

von sushil k

Nov 01, 2018

Very crisp, concise and informative

von Gregory R G J

Nov 04, 2018

Overall a give this course a Thumbs Up!

Would like to have Peer Assignment to really test my knowledge.

von Gaurav K

Nov 04, 2018

This course covered the basics of data analysis. Could be improved

von Piotr M

Nov 05, 2018

Simple, clear.

von Xiaoqi Z

Nov 11, 2018

Very systematic and clear.

von Valerii P

Nov 25, 2018

That was a great start for Data Analysis field's discovery!

von Suprabhat D

Nov 25, 2018

Highly recommended for beginners and intermediate!! :)

von Haixia J

Nov 26, 2018

very concise script - time saving and clear.

von Manuela G

Nov 19, 2018

Very interesting. Very good taught.

von Shailesh M

Nov 22, 2018

Detailed Analysis on Data Science with python.....


Nov 24, 2018

Thank You!!!

von Bhuvana P K P

Nov 24, 2018

Informative course which is easy to learn

von Natalia M

Oct 07, 2018

Great and informative - amazing basis for Data Analytics with Python

von Muhammad Y

Oct 08, 2018

This course is probably the most concise and well explained course I have ever taken on the subject. Materials are explained very well, and in a concise manner. The only downside is that the assessment for this course is based on quizzes, which are way too easy. Nevertheless, the course contains ungraded labs which are really useful.

von Satyam K C

Oct 07, 2018

Challenging task, Make it perfect!!

von Muhammad A

Oct 08, 2018

best course ever

von Girish O

Oct 08, 2018

Good Start for Data Analysis with Python

von Mukesh K

Aug 20, 2018

Nice tutorials and experience was wonderful

von Zheng Z

Aug 19, 2018

Very useful

von Siripat W

Sep 22, 2018

This course are difficult to me, but I think it awesome!. It's make me know much better, I surely repeat this course.

von Jimut B P

Sep 22, 2018


von Loïc B

Sep 17, 2018

Very good labs and videos. Thank you!

von Sagar S

Sep 17, 2018

This is very condense course. However the quizzes after every chapter are very timely, and one at the end of the week for entire week, helped a lot. The labs seems very real world, downloaded some notebook am sure will be using them in real world later on.

von Jaimahaprabhu A

Nov 30, 2018


von Slim S

Nov 30, 2018

Simple and Efficient