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学生对 IBM 提供的 使用 Python 进行数据分析 的评价和反馈

14,447 个评分
2,143 条评论


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.


1776 - 使用 Python 进行数据分析 的 1800 个评论(共 2,138 个)

创建者 Angeliki M

Dec 2, 2019

A really good course. Probably the best so far in the IBM Certificate.

创建者 Nanjun L

Jan 9, 2019

Would be better if more programming-oriented assignments are provided.

创建者 Rahul P

May 12, 2020

Excellent course with detailed hands-on experience via lab exercises.

创建者 Manas C

Mar 31, 2020

The course covers all the fundamental concepts needed for a beginner.

创建者 Obong G

Feb 19, 2019

Though found the ending modules a bit challenging, its a great course

创建者 Padraig M D

Jun 7, 2020

Quite a challenging course, but very rewarding. I really enjoyed it.

创建者 mohsin a

Oct 17, 2020

Hands on Labs are awesome .They helped to consolidate my concepts .

创建者 Rohit P

Apr 25, 2019

Needed a more brief explanation on ridge regression and grid search

创建者 Ninad M K

Jul 14, 2020

It is a great course and it teaches me data analysis with python.

创建者 Ginger M

Mar 18, 2020

I think that for weeks 4 and 5 the course needs more explanation

创建者 Wen P

Dec 24, 2019

Easy understanding

Good sample and comprehensive

Good for beginner

创建者 Jeff J

Aug 27, 2019

Nicely explained. But many minor mistakes here and there though

创建者 Bashar M

Feb 5, 2019

thank you very much ,this course was very useful and interesting

创建者 Cherif H W A

Dec 14, 2019

as usual the labs are great but the videos could be much better

创建者 Secret S L

May 3, 2019

Good content. Still spelling errors and mistakes in some place.

创建者 Mudita N

Feb 20, 2019

Last few weeks were a bit confusing but overall a good course .

创建者 Ismayil J

Nov 5, 2018

Good overview of classic Statistic methods performed in Python.

创建者 Shine

Jun 18, 2019

There are something wrong in the final assignment submit page.

创建者 Tatiana K

Jan 25, 2019

Great course, but the number of errors in videos is tremendous

创建者 Logic

Jun 16, 2020

This is a good course for beginners, but not enough in-depth.

创建者 Eliezer A

Jul 30, 2019

there are some errors in the code lines through the lecutres.

创建者 WANG T

Jan 24, 2019

Typos in the videos and notebooks should have been corrected.

创建者 Raja U A

Mar 4, 2021

Course Contents were excellent but not well arranged/planned

创建者 alvaro a

Sep 30, 2020

Buen curso, los talleres permiten la aplicación de conceptos

创建者 Abhay S

May 12, 2020

Quiz sections are very simple in comparison to the lessons.