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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

4.6
6,188 个评分
769 个审阅

课程概述

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....

热门审阅

RP

Apr 20, 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.

OA

Jul 13, 2018

I have been looking for a very non-complicated course on data analysis and I hit the Jackport with this course! Very simplified and explanatory. You should definitely take the course

筛选依据:

701 - 使用 Python 进行数据分析 的 725 个评论(共 767 个)

创建者 Robert P

May 17, 2019

Some concepts were quite confusing and not that well explained.

创建者 Maciej L

May 16, 2019

Too many complicated things happening at once. It is hard to digest and follow.

创建者 BT

May 28, 2019

Lots of good concepts. However, too complicated and could have been explained a bit more.

创建者 Jesse Z

Jun 05, 2019

For such a important topic, it seems like the videos sped through some essential topics.

创建者 Jackson V

Jun 06, 2019

Not as impressed with this course as the previous courses. My main complaints were:

-Seemed to be some gaps between the lectures and labs

-Some lectures seemed rushed through w/ simple questions, and did not prepare well for the lab

-Pre-written code in labs would produce errors

-Spelling mistakes (i.e. the week 5 "Quizz")

-No final project to conclude and summarize up our learning

创建者 Ahmad H

Jun 08, 2019

This course is very tough

创建者 Alton M

Jun 08, 2019

The course requires more interactive programming.

创建者 Ana C

Jun 11, 2019

To short

Goes to fast in some aspects, the theory is completely missing in this course

创建者 Alejandro A S

Jul 25, 2019

Experimented a lot of problems to complete the assignment

创建者 Rosana R M

Aug 13, 2019

The course is too long. The material should be divided and explained more detailed.

创建者 Hao Z

Aug 12, 2019

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.

创建者 Lyn S

Aug 16, 2019

It's difficult to rate this course, because based on other courses in the data analysis program I had low expectations. I am not sure this is good for a beginner, very poorly explained, the person who wrote it is knowledgeable, but he is not a teacher. You will struggle a lot if you don't already know a fair amount. I had to go to third party internet sources to understand a few things. But, this is pretty cheap and easy. I was looking to learn and to show a credential certificate, this supplies the latter, but not so much the former. The most disappointing issue is the time we have to spend with easily fixable issues, such as code not running, no upload buttons for some test answers. You have to search thru a lot of other discussion issues to find out what to do - after spending hours trying to figure out on your own - very disrespectful. I am ok with typos, but it does show the entire thing is very sloppy.

创建者 Arjun S C

Aug 14, 2019

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

创建者 Kristen P

Aug 19, 2019

The work in this course was incredibly interesting. However, there are many errors and the forums went for over a week without response to questions...It seems hastily put together.

创建者 Pedro F

Aug 22, 2019

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

创建者 Filipe S M G

Aug 24, 2019

Good introductory course on Data Analysus with Python. Since the course is short, the functions and concepts are explained very quickly. There are also many mistakes in the slides, notebooks and even in the final assignment.

创建者 Dominic M L C L

Sep 16, 2019

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

创建者 Abhishek K

Aug 26, 2019

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

创建者 Sathiya P

Aug 27, 2019

Nicely thought, but I felt concepts like Decision trees, Random forest were missing

创建者 Brett W

Sep 17, 2019

While the lecture material is well presented and certainly can be followed, the slides are littered with spelling mistakes, and many in important places (code that couldn't run as displayed.) Even the final assignment had formatting issues, and without the discussion forums suggesting removing the confidence interval, it was taking an excessively long time to run. These are generally minor issues that can be ignored, but as a mass, they are embarrassing at best.

创建者 Baptiste M

Nov 02, 2019

Final assignment is quite messy

创建者 Anmol K P

Oct 14, 2019

Course could have been more elaborate in depth and scenarios

创建者 Filippo M

Sep 27, 2019

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

创建者 Ying W O

Sep 27, 2019

There are lots of typos in the labs and assignments, which can be frustrating. I expect better quality from IBM. Content is great and easy to understand nevertheless.

创建者 Sachin L

Sep 26, 2019

More examples and detailed explanation