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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
5,715 个评分
712 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:

626 - 使用 Python 进行数据分析 的 650 个评论(共 716 个)

创建者 Damian D

Feb 13, 2019

There are some mistakes in the course (wrong transcryptions, missing cells in LAB).

The material is quite difficult and more explanation / exercises would be needed.

There is no assignment at the end of the course which I consider as minus.

创建者 Mbongeni N M

Sep 09, 2018

It was educational, but when you pass a quiz, there should be an option to get answers to the questions you got wrong. And the practice exercises were filled with mistakes, particularly week 5. And the instructor was not responding to students' questions for week 5, which was one of the most challenging weeks. That was annoying.

创建者 Raghav N

Sep 14, 2018

This course is definitely very helpful to people who are passionate about Data science and have basic to intermediate understanding of Python but this course can be much better if it includes coding assignments rather than quiz submission. It was a great experience.

创建者 Guillermo M M

Aug 20, 2018

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.

创建者 Toan T L

Oct 23, 2018

Decent videos on Data Analysis techniques.

But the labs are poorly constructed: typos, inconstant question and solution, un-commented code and under-explained lab result.

It's a shame since the labs in other courses in this series are very high-quality.

创建者 Tomasz S

Nov 19, 2018

Few small hiccups with the training videos and quite a few in the lab-excercise

创建者 Raj K

Jul 06, 2018

It would be great course for beginner to have idea about different steps involve in data science job. I would recommend to go with this course. I just took 3 days to complete this course and you can do in 2 days also. Depending on your speed.

创建者 Teofilo E d A e S

Apr 16, 2019

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

创建者 Abdul M A

Apr 17, 2019

Not very interactive with fewer help to learners

创建者 Nihal N

Apr 18, 2019

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

创建者 Vidya R

Apr 16, 2019

Very Math!

创建者 Benoit P D

May 04, 2019

The content of the course is very interesting. There are lots of typos in the lab workbooks though. Additionally, i found having to use Watson Studio for the assignment / labs as opposed to plain Jupyter a little annoying.

创建者 Ashwin G

Apr 26, 2019

Too fast and could have included more examples.

创建者 Bhanu S

Apr 28, 2019

It was difficult to retain the knowledge imparted.

创建者 Ivan L

Apr 29, 2019

Typos are very unprofessional and spoil impressions of the course. Tests and labs are super-easy and do not make you think, and you only need to repeat commands from the lectures.

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 Maciej L

May 16, 2019

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

创建者 David V R

Jun 17, 2019

Exams should be harder

创建者 Ramakrishna B

Jun 19, 2019

More explanations would be great. Its very difficult to understand Data exploration / evaluation sections

创建者 Nirav

Jun 26, 2019

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

创建者 Marcel V

Jun 28, 2019

A lot (too much maybe) is covered in this coarse

It really helps a lot when you know some statistics. Like linear regression,

Why gridsearch was covered I wonder.

创建者 Brisa A

Jun 28, 2019

A lot of errors make the course confusing. Also, the assigments and labs are "too easy"... it is clearly shown in the videos that there is much more to be done, but the course only demands you do about 50% of what is taught. How are we supposed to really learn without practice?? Give us real and demanding projects!

创建者 Pulkit D

Jun 29, 2019

Please update and explain Rigid Regression a little more

创建者 Alejandro A S

Jul 25, 2019

Experimented a lot of problems to complete the assignment

创建者 Robert P

May 17, 2019

Some concepts were quite confusing and not that well explained.