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返回到 使用 Python 进行数据分析

學生對 IBM 技能网络 提供的 使用 Python 进行数据分析 的評價和反饋

4.7
15,298 個評分

課程概述

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....

熱門審閱

RP

2019年4月19日

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

2020年5月5日

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.

篩選依據:

2176 - 使用 Python 进行数据分析 的 2200 個評論(共 2,313 個)

創建者 Pierre-Antoine M

2020年2月19日

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

創建者 Toan N

2020年3月27日

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

創建者 Jessica B

2019年6月14日

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

創建者 Rodolfo R

2022年1月24日

T​his course focus on very important subjects but in a sketchy aproach

創建者 Arjun S C

2019年8月14日

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

創建者 Anvit S

2020年5月13日

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

創建者 Holly R

2020年4月16日

Could use some better mathematical description of the techniques.

創建者 Filippo M

2019年9月27日

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

創建者 Robert P

2019年5月17日

Some concepts were quite confusing and not that well explained.

創建者 Atharva Y

2020年1月23日

As compared to other courses this course seems to be too fast

創建者 Nirav

2019年6月26日

Lot's of errors in this course, please update and correct it.

創建者 Anmol P

2019年10月14日

Course could have been more elaborate in depth and scenarios

創建者 Tichaona M

2020年8月5日

This is a great course for building the base to use Python!

創建者 林tanya

2019年12月27日

the lab is extremely useful, however, videos are too short

創建者 Michael A D R

2019年11月1日

Extremely interesting BUT it gets long and hard to follow.

創建者 Nihal N

2019年4月18日

not in depth.... needs more clarity on a variety of topics

創建者 Alejandro A S

2019年7月25日

Experimented a lot of problems to complete the assignment

創建者 Troy S

2019年3月14日

Quizzes are too easy. Don't even need to watch the videos

創建者 Anurag P

2020年1月18日

Mostly theoretical; very little to implement on our own.

創建者 Pulkit D

2019年6月29日

Please update and explain Rigid Regression a little more

創建者 Appa R M

2019年10月24日

The kernal is stuck for some questions and its annoying

創建者 Qing L

2020年1月26日

Kurs gut organisiert aber

die Fragen sehr oberflächlich

創建者 Jakubina K

2018年12月19日

It would be more useful if labs were be rated as well.

創建者 Ankit K S

2020年1月29日

It would be nice if the course had more assignments.

創建者 Bhanu S

2019年4月28日

It was difficult to retain the knowledge imparted.