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Bewertung und Feedback des Lernenden für Datenanalyse mit Python von IBM

15,083 Bewertungen
2,272 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....



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.


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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2176 - 2200 von 2,278 Bewertungen für Datenanalyse mit Python


6. Apr. 2022

I am not able to download my certificate.

von Fariha M

28. Sep. 2020

The course didn't seem challenging to me.

von Sachin L

26. Sep. 2019

More examples and detailed explanation

von Nilanjana

12. Juli 2019

More examples and code examples needed

von Hamed A

8. Apr. 2019

The course needs a final assignment!

von piyush d

6. Dez. 2019

exercises could have been better.

von Jyoti M

26. März 2020

I felt it was too fast to grasp.

von Baptiste M

2. Nov. 2019

Final assignment is quite messy

von Murat A

21. Apr. 2021

could not access the labs.

von Yuanyuan J

17. Jan. 2019

Not clear on the last part

von Ahmad H

8. Juni 2019

This course is very tough

von conan s

20. Dez. 2019

Lots of technical issues

von David V R

17. Juni 2019

Exams should be harder

von Riddhima S

8. Juli 2019

la lala la la laa aaa

von Daniel S

8. Feb. 2019

Not easy to follow.

von Allan G G

10. Mai 2022

Muy poco practico


27. Sep. 2021

très bon cours

von Vidya R

16. Apr. 2019

Very Math!

von James H

29. Apr. 2020

Definitely not one of my favorite courses in the Data Science Certificate series. There were times I was ready to give up the pursuit of the certificate altogether during this class... There should have been a prerequisite for this course of the statistical tools and methods that would be covered in here... Sure I could program these things after this class, but i still dont understand why I would choose to use one over another? This is one of those classes where you walk away feeling more confused than when you went in... Also there were a lot of mistakes, typos, and obsolete things in the labwork - some reported and acknowledged months ago, but still not fixed in the lab (video I can understand, but not the labs)

von Ruben W

6. Okt. 2018

The content is good, but if you are not familiar with Python, I wouldn´t recommend this course. There are a lot of typos in the video. The code contains a lot of errors where you have to find a solution. So, you are forced to debug their code often.

But if you are only interested in the course certificate, you could quickly go through the videos and quizzes, without any problems. It's easy to pass because the questions are like: What is the result of print("Hello world"). So no real challenges at all.

Please, try to fix the typos. Sometimes it was very embarrassing. Example (Week 3) instead of

"from sklearn.metrics ..." the video comes up with "from sklearn.metrixs ..."

von Chris M

16. Okt. 2020

Seems more adequate for people who have a background in statistical analysis. The labs are confusing and there is no orientation to the tool being used so it has taken me quite a while to figure out how to even proceed through a lab. After spending considerable time doing the lab, it may not submit the results and Coursera assumes you haven't take it yet which means you have to do it all over again. Other courses I've taken are structured much more clearly, step-by-step, providing activities that allow you to gain confidence before throwing you off the deep end. This one could use the help of an instructional design expert.

von Micheal D L

29. Juli 2019

many typos, errors, mislabeled... just felt like a sloppy product were paying for. I was very frustrated as well by certain features not functioning... for example, after following specif instructions to share a notebook, just as I have done many times while working on this certification... testing the link comes back as unshared no matter what I do. This and the SQL course have been the worst so far in this Data Science cert but at least this course ended up marked as completed. If I wasn't already this far invested in the cert I would definitely quit and use free resources while I built my portfolio.

von Thomas S

17. März 2020

-1- The training and quizzes are full of errors. You need someone to actually review the content before publishing.

-2- The education focused more on the mechanics of how to run certain commands to obtain results rather than explaining why a data scientist would want to run these certain commands and how to best interpret them.

-3- I would embed more but perhaps smaller lab assignments rather than going over many concepts and making the person go through the steps (with minimal explanation) at the end of the module. This is particularly applicable for weeks 4 & 5.

von Chris M

23. Dez. 2021

Not a very good course. The information given in the videos was not explained well and key concepts seemed to be brushed past. The graded assignments were very dumbed down and did not reflect the difficulty of the videos. This was quite lucky though as the videos were not very good either. It seems like the graded assignments were dumbed down so that the course could actually be completed without further background reading.

More information should be added, longer length videos, and get rid of the peer-review system. Lazy.

von Joseph G

5. Jan. 2020

There were so many typos and errors about the very topics they were teaching. It is as if they don't actually care that people are trying to learn this and just view this course as a way to promote their Watson Studio. Normally I would forgive these errors, but there are programmers so paying attention to detail is paramount. Also, misspelling method names while you are teaching those very methods and then never showing how to spell them again makes for some serious confusion.