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Bewertung und Feedback des Lernenden für Datenanalyse mit Python von IBM Skills Network

16,195 Bewertungen

Über den Kurs

Analyzing data with Python is an essential skill for Data Scientists and Data Analysts. This course will take you from the basics of data analysis with Python to building and evaluating data models. Topics covered include: - collecting and importing data - cleaning, preparing & formatting data - data frame manipulation - summarizing data - building machine learning regression models - model refinement - creating data pipelines You will learn how to import data from multiple sources, clean and wrangle data, perform exploratory data analysis (EDA), and create meaningful data visualizations. You will then predict future trends from data by developing linear, multiple, polynomial regression models & pipelines and learn how to evaluate them. In addition to video lectures you will learn and practice using hands-on labs and projects. You will work with several open source Python libraries, including Pandas and Numpy to load, manipulate, analyze, and visualize cool datasets. You will also work with scipy and scikit-learn, to build machine learning models and make predictions. If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge....



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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1801 - 1825 von 2,449 Bewertungen für Datenanalyse mit Python

von Vera C

11. Sep. 2019

The course is quite challenging for me as a beginner of using python to perform linear/non-linear model development. It is good in terms of the plenty of content for people to learn but it is quite hard also as it would be better to have more practice / examples.

von Piyush J

27. Jan. 2020

This course teaches you important python liabraries like pandas, scikit-learn. It also provides information about regression and helps us to build a model for a given case. Overall its very nice course for getting idea about how to do Data Analysis using Python

von Anton V

15. Jan. 2019

I think this is a decent course that introduces data analysis on a basic level. The first 3 weeks were really well written, the last 2 weeks have some faults in them though, like values referred in the text which does not match with values written in the code

von Jessie J

6. März 2020

Very good introductory course on data analysis using Python! It is best for people who already had some level of analytics experiences before as it sometimes goes a little bit fast. But very good in general, covers a wide range of topic, with good exercises.

von Avish J

15. Dez. 2019

Good to start with, this course provide you with the step involved in Data analytics but no logic behind these steps are provided. If you are new to python library this course will be helpful for you as it involve use of pandas, Scikit, Scipy and matplotlib.

von Bernardo N B C F

2. Juli 2019

Really enjoyed the Labs, specially the last ones that were long and covered a lot of material in depth. I think the course would have a better user experience if it wasn't for the many spelling mistakes and small bugs, specially in the Jupyter notebook Labs.

von Zayani M

11. Dez. 2018

Toughest course so far. I liked being able to visually see the statistics behind data analysis, which was much more helpful than the textbooks I had to use to earn my math degree! However, the final week was still a challenge to get through and understand.

von Tracey C

11. Feb. 2021

I liked the structure and pace of this course. The videos and exercises were helpful and the final project was a very good measure of what we had done in the course. I took off a star because there were more typos in this course than some of the others.

von Lakshmi h

9. Juli 2020

There should be an Handicap assistance in the course as some of the visually impaired people are finding it difficult to read the assignment codes with their screen reader nvda.

The assignment notebooks code settings need to be modified to support this.

von Dean E B

28. Mai 2021

Covers lots of materials. Lab is at end of each week, but I did better following along with coding during each lesson, A good framework, but with a lot of jumps and not much depth. With additional studying from other sources, I got a lot of knowledge.

von Whale M J

2. Sep. 2020

A lot of concepts are packed into this little course. The course materials are a bit too concise for the concepts to be elaborated properly, so I need to search a lot extra online for concepts behind. But in general, they can be used a starting point.

von Antas J

8. Jan. 2020

the course was great and informative, however the pace and information in this course is not sufficient for a person who is new to the python libraries and analytical features, if i may add MSE and R^2 and plots are still not so much understood by me.

von Aylin G

2. Jan. 2020

Some questions in the peer-graded assignment are not clear and answer box of some questions are not visible so I could not get any point from them. You should better check the contents of the tutorial and make sure that there is no technical issues.

von giuseppe t

31. März 2022

It is a well structured and quite valuable course; it could have been a masterpiece, if it had provided more connections, explanations, insights, in other words programming background related to all those different topics touched over the weeks.

von Monalisa p

4. Nov. 2019

This Course is very helpful for the beginners. This course is very detailed, and well explained. You will go through all the important things required for data analysis. This course's Lab is very strong, I must recommend you to do this course.


10. Feb. 2022

Bom conteúdo na abordagem das principais funções para análise de dados, porém, carente de fundamentação teórica em relação às análises. Por não haver pre requisito, os fundamento poderiam ter sido abordados, ainda que de forma superficial.

von Sachin G

4. Mai 2020

Very informative course... very well designed... a bit fast-paced but concise and clear

it's just that if the final project could have been little more challenging so that there are more opportunities to apply what we learnt in the course.

von Terry G

1. Mai 2020

Great course. I felt like I can run my own models and test them now. There were some strange errors throughout the notebook that were raised in the forums but not addressed in the documents. Aside from that, it was pretty good for a MOOC.

von Adarsh K P

26. Sep. 2019

ton of new stuff to learn from.... super informative course...this course will introduce you to a lot of useful and important stuff and the best part is that each topic is explained first then comes the coding part which is just awesome.

von Chris A B

15. Sep. 2019

This was a challenging course that covered a lot of items. I believe I need more practice in these items (Linear Regression, Polynomials, Ridge, Fit, Predict, etc.) in order to have a much better understanding of the course materials.

von Guilherme P d C

7. Apr. 2019

Model Development and Model Evaluation content requires more intuitive examples, maybe adding some flowchart to explain the reasons of every step in Modeling and Evaluation. I am making this suggestion to make the course even better.

von Joe M

27. März 2020

Interesting class. Clearly designed to cover a lot of ground but not always in the detail some may like. Emphasizes showing some basic analytic work flows, but does not always explain how or why of a particular step in the workflow.

von Logan W

7. Nov. 2019

This was a very comprehensive course, but it could definitely use some revising on the labs that caused output issues. Additionally, some of the peer-graded material couldn't be uploaded due to syntax. Other than that, very helpful!

von João L F C

16. Apr. 2020

It was a good introductory and pocket course for Data Analysis with Python to me. The concepts were given pretty much straight forward, and the assignement didn't diverged much from what had been already seen throughout the course.

von Jhon P

4. Juni 2021

At the end, the final project link was wrong and nobody from coursera or ibm give me an answer. Fortunately, course partners share the right notebook and thus, I could finish my course. The topics are very well for this course.