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学生对 IBM 技能网络 提供的 使用 Python 进行数据分析 的评价和反馈

15,264 个评分


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....



May 5, 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.


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.


2201 - 使用 Python 进行数据分析 的 2225 个评论(共 2,309 个)

创建者 Gerhard E

Feb 12, 2019

Copy of videos, not a fan of tools used in labs

创建者 Aditya D J

Mar 8, 2022

Nice, but I can't try IBM Cloud Trial for free

创建者 Yasmin A

Feb 3, 2020

Un cours riche et adéquat pour les débutants

创建者 Hiro H

Nov 27, 2019

Very nice course. It gives you what you need

创建者 Brian S

Mar 29, 2020

Notebooks are sloppy, with typos and errors

创建者 Anjali

Apr 6, 2022

I am not able to download my certificate.

创建者 Fariha M

Sep 28, 2020

The course didn't seem challenging to me.

创建者 Sachin L

Sep 26, 2019

More examples and detailed explanation

创建者 Nilanjana

Jul 12, 2019

More examples and code examples needed

创建者 Hamed A

Apr 8, 2019

The course needs a final assignment!

创建者 piyush d

Dec 6, 2019

exercises could have been better.

创建者 Jyoti M

Mar 26, 2020

I felt it was too fast to grasp.

创建者 Baptiste M

Nov 2, 2019

Final assignment is quite messy

创建者 Murat A

Apr 21, 2021

could not access the labs.

创建者 Yuanyuan J

Jan 17, 2019

Not clear on the last part

创建者 Ahmad H

Jun 8, 2019

This course is very tough

创建者 conan s

Dec 20, 2019

Lots of technical issues

创建者 David V R

Jun 17, 2019

Exams should be harder

创建者 Riddhima S

Jul 8, 2019

la lala la la laa aaa

创建者 Daniel S

Feb 8, 2019

Not easy to follow.

创建者 Allan G G

May 10, 2022

Muy poco practico


Sep 27, 2021

très bon cours

创建者 Vidya R

Apr 16, 2019

Very Math!

创建者 James H

Apr 29, 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)

创建者 Ruben W

Oct 6, 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 ..."