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學生對 IBM 提供的 使用 Python 进行数据分析 的評價和反饋

14,899 個評分
2,236 條評論


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....




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.



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.


2051 - 使用 Python 进行数据分析 的 2075 個評論(共 2,238 個)

創建者 Xuecong L


Thanks for teaching me the systematic way to do data analysis! However, I found quite a few mistakes in the lectures in this course, hope it will improve!

創建者 Namra A


This course was good if you study the course and study the material from other sources and books too ,so it will give you deeper and more understanding

創建者 Hao Z


IBM Cloud is difficult to use.

The generated link of notebook will not share the latest version, if you click the share icon before editing the notebook.

創建者 Neo B


Data visualization was taught in details in course 7 and regression was taught in course 8. With no backgrounds, the codes in this course are scaring pe

創建者 Goh S T


The section on model development and evaluation is not so clear. It is difficult to understand if you have no prior knowledge of machine learning.

創建者 Girgis F


Course was great however i felt a lot of material was covered in a short period of time, this course can be 2 or 3 courses based on the content

創建者 Guillermo M M


It is missing a last project like in the two other courses... It would have been quite fun to be able to apply what we learnt in a project.

創建者 A P


Lots of spelling and grammatical errors that made it difficult to understand some of the material. It is otherwise an interesting course.

創建者 靳文彬


There is no slides to download or review after class which makes it hard to go over the knowledge again without watching the video again

創建者 Siwei L


The video is too short and many concepts remain unclear or poorly explained. More contents need to be added to the questions and tests.

創建者 Carlos G R G d l C


It's an excellent course; the best part is the labs. It's a pity that we (the students) have a lot of problems loading the labs.

創建者 Pedro F


Little bit confusing, unstructured and not easy to follow. Material inside is good though, but the course needs to be improved.

創建者 sangeet a


Things are too fast in this course and many things remain unexplained which makes it difficult for one to understand properly

創建者 Dominic M L C L


Too many errors in the code and explanations. Makes it very difficult to understand which is the right procedure/conclusion.

創建者 Adam J L J H


This course focuses a lot on the theory and explanation. However, there isn't much hands-on practice for the coding itself.

創建者 Osama W


*No response to some questions/comments on the forum

*More details/thorough clarification required for some points covered

創建者 Rishika A


There are many errors and this was even the toughest course I have taken yet since many things were not explained clearly

創建者 Kuzi


Course is flawless but when i had a technical challenge the Coursera team were clueless on how to fix it.

Otherwise good.

創建者 akash t


Few of the video requires improvement in terms of its quality. Particularly the lectures corresponding to week 4 and 5

創建者 Teofilo E d A e S


Too complex for easy understand. Should have some documentation explaining the process and comparing the new methods.

創建者 Julia S


I​t is okay in the sense that you learn something but the questions should be harder and it should go more in depth.

創建者 Vrinda M K


Topics covered are important but videos end abruptly as if narrator was saying something more and video just ended

創建者 Marc T


why is sharing of the notebook worth 3 points? That has absolutely nothing to do with python or data analysis!

創建者 Abhishek K


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

創建者 Sarah s


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