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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

4.7
14,231 個評分
2,109 條評論

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....

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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.

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.

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76 - 使用 Python 进行数据分析 的 100 個評論(共 2,103 個)

創建者 Rene P

2019年3月24日

There could be links to functiones libraries in the lab for a fast check of a function if needed.

創建者 Ugur S O

2020年12月21日

I think the quizzes can be in the format of programming required questions.

創建者 Charles C

2019年2月5日

Some mistakes/ typos in the exercises and slides, but great overall

創建者 Yogish T G

2019年3月30日

An assignment should have been included

創建者 Miguel E M

2020年4月15日

There where some typos in the labs that could confuse most learners. I didn't feel like the course prepared people for real applications. The final project was quite hard because of this .

But it does give you a wide vision on hoy pandas work and some basic but apparently often used tools.

I see this course as a complement to a more detailed data analysis resource or perhaps as simply as an introductory view.

創建者 Jaime V C S

2019年2月22日

Hello,

in this course there were some errors on the slides, and some quite complicated topics (almost every time related to statistics) was given in a very over-viewed way. Also, some of the python codes were not explained very well, with some terms of them seem to be kind of arbitrary for those who are beginners in the language. My impression is that this course should be longer and more detailed.

創建者 arda

2018年11月20日

Overall I benefitted the course material as a beginner in python and data analysis. The questions were too trivial but maybe that helped me remain engaged with the course and complete it in a short time frame. There were some bugs, typos and minor quality issues that did not really effect my overall experience.

創建者 Katarina P

2019年6月27日

Many typos in videos, stats explained on a very rudimentary way (and often inaccurate), Watson environment is awful as it takes ages for some simple regression plots to be made, it freezes and the interface is not user-friendly, yet we have to use it.

創建者 Sadanand B

2019年2月7日

Seems like there are quite a few errors in the labs that confuse the heck out of a student. The labs need to be fixed else the material becomes useless.

創建者 Ravindra D

2020年5月11日

Course content does not give proper understanding of the different approaches. For the person who is not from mathematics background it is confusing.

創建者 Bhuvaneswari V

2019年3月9日

The statistics background needed for the course need to be better explained. or at least reference to related learning materials to be given

創建者 Russell K

2020年4月26日

Too many errors in the lab examples can be rather confusing.

Also, the Seaborn code was not working in IBM Watson Studio

創建者 Mariam H

2020年5月2日

Great course but some of the concepts are not explained very well. I got lost towards the end but overall i like it.

創建者 Andre L

2019年3月10日

Lot of information, but offered in a very choppy manner. Was hard to follow, will need to review many many times

創建者 Abdulaziz A

2020年4月11日

the course content is excellent but some Technical issues occurred in doing the lab exercises

創建者 Chau N N H

2020年1月29日

The lesson need more explanations on Polynomial Regression, Pipeline, Ridge Regression.

創建者 Fayja H

2021年1月19日

too much content all at once

創建者 Alex H

2019年10月4日

Begins relatively clear. The practice labs were coherent and straightforward.

Around Week 4, things started to get convoluted. Small things, things that you don't notice at first.

Week 5 was where it really started to fall apart. You could tell whoever made this course lost interest or just did not have the capacity to teach the information effectively.

A great example of the lack of understanding or knowledge of how Coursera works is something you can view yourself.

Week 6 is the Final Project

Week 7 is one statement about your certificate.

Usually in most courses, the final project will be in end of the final week. That week having multiple modules that you have to complete leading up to the final. It was worrying for me as I thought the approach to this was on accident, but it seems likely that it was just due to ignorance.

Just as well, the Final Project was botched, the software and questions were depreciated and even written wrong by the creator. And when you would upload your pictures in the end to show you had worked out the problem, one of the upload buttons was missing in lieu of the letter "Y"....

Y indeed. Y was the ending of this course so terrible? A little more investment in the people you are teaching would go a long way. Very disappointed.

創建者 Philip P

2021年1月9日

Course lacks thorough rigor or genuine assessment.

Labs are training on copy/paste and using the Shift+Enter command in the Jupyter notebook.

Assessments are multiple choice. No assessments on ability to write scripts to undertake data analysis to seek solutions.

創建者 Brandon S

2021年1月7日

Again, the use of the IBM cloud is a useless buffering of site traffic for your own products and does not provide anything for the course. Little to no 'challenge' questions that push the student to go beyond the hand held procedure of the labs.

創建者 Elvijs M

2020年4月18日

The course makes you aware of some Data Analysis techniques, but you learn very little. The explanations are very superficial. And since nearly all the code is are already there, you are not forced to think about the concepts and methods.

創建者 Utkarsh S

2020年6月25日

The course was quite good until Week 3 but after that it was poorly structured. A lot of concepts were randomly introduced without proper explanation in Week 4 and Week 5, thereby killing the fun of learning.

創建者 Ibrahim A

2020年4月27日

This course ranks the least of the wonderful courses I have taken with coursera. There is definitely room for improvement in the delivery of materials.

創建者 Muzamal A

2020年4月22日

I'll be honest this course for a beginner is difficult and incomprehensible as thereare many new things introduced which are not explained properly

創建者 Sharvinee

2020年11月23日

yOU DEFINITELY NEED SOME BASIC PROGRAMMING BACKGROUND. i FOUND IT TOUGH