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学生对 IBM 提供的 Data Analysis with Python 的评价和反馈

4.7
19,378 个评分

课程概述

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement....

热门审阅

RP

Apr 19, 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.

VS

Jan 30, 2022

This is totally one of the hardest course I've ever taken on Coursera. It's packed with knowledge I did not know before. Definitely recommended for people who want to learn data analysis with Python.

筛选依据:

2851 - Data Analysis with Python 的 2875 个评论(共 3,064 个)

创建者 Abhishek K

Aug 26, 2019

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

创建者 Sarah S

Jan 2, 2019

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

创建者 Sara J H

Jan 6, 2023

Will be easy if you have prior experience with Python/statistics. I don't and I didn't learn much at all.

创建者 Ramakrishna B

Jun 19, 2019

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

创建者 Camilo P T

Jun 15, 2020

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

创建者 Kenneth S

Jan 12, 2020

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

创建者 Bjoern K

Jun 14, 2019

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

创建者 Nadeesha J S

Apr 11, 2019

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

创建者 Kareem A

Aug 11, 2025

This course is useful, however, it is somehow dry. It could be made more engaging or less robotic.

创建者 Manu K

Jan 6, 2025

It was okay , but the Lab environments don't run properly without some proper libraries installed.

创建者 Edward S

Aug 1, 2020

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

创建者 Miguel V

Nov 12, 2020

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

创建者 Poorna M

Jun 23, 2020

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

创建者 Nathan P

Jan 1, 2020

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

创建者 Varun V

Dec 18, 2018

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

创建者 Connor F

Mar 27, 2020

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

创建者 Badri T

May 28, 2019

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

创建者 Jesse Z

Jun 5, 2019

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

创建者 Debra C

Mar 24, 2019

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

创建者 Miguel A I B

May 13, 2020

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

创建者 Xinyi W

Jan 26, 2020

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

创建者 Ana C H

Jun 11, 2019

To short

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

创建者 Sathiya P

Aug 27, 2019

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

创建者 Ros R

Aug 12, 2019

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

创建者 Amanda A

Apr 16, 2020

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