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

4.7
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15,272 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....

Top-Bewertungen

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.

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.

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2101 - 2125 von 2,310 Bewertungen für Datenanalyse mit Python

von Filipe S M G

24. Aug. 2019

Good introductory course on Data Analysus with Python. Since the course is short, the functions and concepts are explained very quickly. There are also many mistakes in the slides, notebooks and even in the final assignment.

von Benoit P D

4. Mai 2019

The content of the course is very interesting. There are lots of typos in the lab workbooks though. Additionally, i found having to use Watson Studio for the assignment / labs as opposed to plain Jupyter a little annoying.

von CHEW K C

14. März 2021

it will be better if you can illustrate how to solve the problem step by step and explain what is the parameters that you put inside the function. Some videos are great but some videos seems a bit rush.

von Sadanand U

9. Apr. 2019

It would be great if we go in a little more details of when to use which metrics for evaluation. Instead of running through a bunch of concepts you could have spent a little more time in each of them.

von Joseph M

21. Feb. 2019

There were serious problems with this course, not in the instructional material but in the execution. There were multiple typos in the code. The especially grievous ones being in the dictionary names.

von Tejas M J

4. Mai 2021

Few mistakes in the questions made for this course. Also, more questions for quizzes are needed to test the learner's abilities better. Slightly harder coding assignments would also be a great idea.

von Michael L

1. Jan. 2021

Ran into some roadblocks during the peer assignment. It would have been nice to have had access to someone to discuss the roadblocks and assist me with understanding how I went wrong.

von Deren T

7. Jan. 2019

This is the 6th course of the specialization and I gave 5 stars to the previous courses. But this course have many typos in videos and codes. It makes harder to understand some points.

von Kristen P

18. Aug. 2019

The work in this course was incredibly interesting. However, there are many errors and the forums went for over a week without response to questions...It seems hastily put together.

von L V P K M

14. Mai 2020

Videos are very fast and dont go into details. Assignment is very easy, it could have been more challenging which can test and make learner to think using several concepts learned.

von Taqi H

18. Juli 2022

one must have prior knowledge about python and have little bit understanding of statistics. over all course was good but should be improved in terms of Data, ML terminologies, etc

von Ivan L

28. Apr. 2019

Typos are very unprofessional and spoil impressions of the course. Tests and labs are super-easy and do not make you think, and you only need to repeat commands from the lectures.

von Vladimir K

24. Feb. 2020

So many errors in materials. It's unacceptable for course of such level. Even though people mentioned these errors in discussion forumns noone seems to bother about correct em.

von Naveen B

12. Juli 2019

Some of the codes shown in the videos had minor errors. Also, a bit more explanation for function (in statistics terms) would have helped in having a better understanding.

von Sruthi A

20. Jan. 2021

This course covered all the topics and overall it's a good one. I wish there were more examples, as it was hard to understand the details in depth with just one example .

von Marta I

23. Aug. 2020

This is a good course for beginners with Python. The content is explained in a very direct and comprehensible way, but more programming exercises and tasks are required.

von Ying W O

27. Sep. 2019

There are lots of typos in the labs and assignments, which can be frustrating. I expect better quality from IBM. Content is great and easy to understand nevertheless.

von Matteo T

1. Jan. 2020

This course is quite good. The bad thing is that the arguments of the last "lesson week" are treated very superficially, taking for granted some advanced knowledge.

von Marcel V

28. Juni 2019

A lot (too much maybe) is covered in this coarse

It really helps a lot when you know some statistics. Like linear regression,

Why gridsearch was covered I wonder.

von Milica V

24. März 2022

It could be better. It provides a lot of coding, but it does not explain all the aspects of it. The tests are not a good representation of what has been done.

von Dylan H

3. Apr. 2019

While a bit fast and loose with the concepts, does contain a lot of practical code as to how exactly to bring things discussed about, which is appreciated.

von Xuecong L

16. Feb. 2019

Thanks for teaching me the systematic way to do data analysis! However, I found quite a few mistakes in the lectures in this course, hope it will improve!

von Namra A

8. Aug. 2021

This course was good if you study the course and study the material from other sources and books too ,so it will give you deeper and more understanding

von Hao Z

12. Aug. 2019

IBM Cloud is difficult to use.

The generated link of notebook will not share the latest version, if you click the share icon before editing the notebook.

von Neo B

11. Feb. 2019

Data visualization was taught in details in course 7 and regression was taught in course 8. With no backgrounds, the codes in this course are scaring pe