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Python을 사용한 데이터 분석(으)로 돌아가기

IBM의 Python을 사용한 데이터 분석 학습자 리뷰 및 피드백

4.7
6,574개의 평가
815개의 리뷰

강좌 소개

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....

최상위 리뷰

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

필터링 기준:

Python을 사용한 데이터 분석의 809개 리뷰 중 751~775

교육 기관: 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.

교육 기관: Sachin L

Sep 26, 2019

More examples and detailed explanation

교육 기관: 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.

교육 기관: Appa R M

Oct 24, 2019

The kernal is stuck for some questions and its annoying

교육 기관: Michael A D R

Nov 01, 2019

Extremely interesting BUT it gets long and hard to follow.

교육 기관: Baptiste M

Nov 02, 2019

Final assignment is quite messy

교육 기관: 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.

교육 기관: 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.

교육 기관: Abdul M A

Apr 17, 2019

Not very interactive with fewer help to learners

교육 기관: Maciej L

May 16, 2019

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

교육 기관: Filippo M

Sep 27, 2019

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

교육 기관: Deren T

Jan 07, 2019

This is the 6th course of the specialization and I gave 5 stars to the previous courses. But this course have many typos in videos and codes. It makes harder to understand some points.

교육 기관: Ashwin G

Apr 26, 2019

Too fast and could have included more examples.

교육 기관: Felix S

Jul 01, 2019

Material to learn data analysis was very good but had quite a few bugs. It was very annoying to review the assignment of a peer because it is not possible to zoom into the screenshot. Furthermore did I need to flag a person because he had copied screenshots and his notebook was empty or only with screenshots but I was still required to review a second person to complete the course.

교육 기관: Joseph M

Feb 21, 2019

There were serious problems with this course, not in the instructional material but in the execution. There were multiple typos in the code. The especially grievous ones being in the dictionary names.

교육 기관: Ramakrishna B

Jun 19, 2019

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

교육 기관: Anmol K P

Oct 14, 2019

Course could have been more elaborate in depth and scenarios

교육 기관: Nadeesha J S

Apr 11, 2019

I would like to see a final project in this course. It will encourage the learners to do more work.

교육 기관: Malcom L

Jan 11, 2019

more hands on, project based/game based learning. Mindlessly watching videos and regurgitating code in the labs can not be the only way.

교육 기관: Steve S

Jan 07, 2019

Rather poor way to get hands on learning. The "lab" does not offer an effective way to learn. This course was a poor substitute for a real instructor. Also, the last two weeks' material became more complicated but the information supplied to learn it did not increase nor provide clear or different explanations.

교육 기관: Mehul A

Dec 24, 2018

This course is not friendly to new beginners in Python. Especially the weeks 3-5 are too intensive without any real explanations of the logic behind the code shown. Linear Regression, ridge regression, etc are too advanced for new joiners who struggle with basic python. Also, there are some erroneous slides present in a couple of videos that add to the confusion. Would not recommend this course to any Python beginners.

교육 기관: Ruben W

Oct 06, 2018

The content is good, but if you are not familiar with Python, I wouldn´t recommend this course. There are a lot of typos in the video. The code contains a lot of errors where you have to find a solution. So, you are forced to debug their code often.

But if you are only interested in the course certificate, you could quickly go through the videos and quizzes, without any problems. It's easy to pass because the questions are like: What is the result of print("Hello world"). So no real challenges at all.

Please, try to fix the typos. Sometimes it was very embarrassing. Example (Week 3) instead of

"from sklearn.metrics ..." the video comes up with "from sklearn.metrixs ..."

교육 기관: Rajesh W

Oct 17, 2018

There are plenty of mistakes in the videos and in the lab session as well. Hope you guys can clear out those.

교육 기관: Ubaid M W

Oct 22, 2018

In lab there are many funtion , libiraries Which have been used first time with out any description , then I have to search for each and every funtion or lib which is way time consuming which make this course worst courses in my list.

교육 기관: Alistair J W

Nov 17, 2018

There were numerous issues with editing of the content in this course that certainly impacted its effectiveness. While that is not uncommon the forums indicated that these had been identified by other learners months ago and not addressed.