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

4.7
19,524 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

AM

Apr 16, 2023

Thanks for course! I met some errors, described them in your forms. I liked every models, but the final assignment was not interesting. I think it can be done better, with decisions and conclusions.

BM

Jul 16, 2020

Although good to learn the know-how of basic data analysis techniques, the quizzes are predictable and you don't end up coding as much as you should. A good starter course to wet your feet in DA!

筛选依据:

2901 - Data Analysis with Python 的 2925 个评论(共 3,097 个)

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.

创建者 Juan S A G

Aug 20, 2020

very simple exercises which does not help to learn altough videos were exeptional

创建者 Naresh T

Aug 11, 2023

It's really good course i really enjoyed learning new things in data analaytics.

创建者 Naf

Nov 1, 2022

It was a good course but maybe a little too easy with all the prompts provided.

创建者 Mohsen R

Jun 16, 2020

The course does not explain the processes enough, there should be more examples.

创建者 Maciej L

May 16, 2019

Too many complicated things happening at once. It is hard to digest and follow.

创建者 Tomasz S

Nov 19, 2018

Few small hiccups with the training videos and quite a few in the lab-excercise

创建者 Craig S M

Mar 21, 2022

It ok. Some parts of the course were bare bone. I liked the hands on sections.

创建者 Steven B

Jun 3, 2020

Overall I felt it was not broken down very well and seemed confusing at time.

创建者 Pierre-Antoine M

Feb 19, 2020

Videos are nice but they are mistakes in the notebooks that disturbs learning

创建者 Toan N

Mar 27, 2020

The lab is disconnected every so often that can't complete it smoothly.

创建者 Jessica B

Jun 14, 2019

Good content, but lots of typos. The outsourcing is extremely evident.

创建者 RODOLFO C R

Jan 24, 2022

This course focus on very important subjects but in a sketchy aproach

创建者 Arjun S C

Aug 14, 2019

Lots of bugs and errors. No instructors reply on the discussion forum.

创建者 Anvit S

May 13, 2020

Could have been more detailed....Important concepts just brushed thru

创建者 Nourhan A Y

Aug 28, 2024

This course needed to be updated it lacks a lot of important basics

创建者 Dibyendu M

May 20, 2023

The practical lab having technical issue .PDF is not downloadable.

创建者 Holly R

Apr 16, 2020

Could use some better mathematical description of the techniques.

创建者 Filippo M

Sep 27, 2019

Useful course, but the IBM online platforms are not working well.

创建者 Robert P

May 17, 2019

Some concepts were quite confusing and not that well explained.