Chevron Left
Python을 사용한 데이터 분석(으)로 돌아가기

IBM의 Python을 사용한 데이터 분석 학습자 리뷰 및 피드백

6,106개의 평가
759개의 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


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.


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 751개 리뷰 중 701~725

교육 기관: 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.

교육 기관: Abhishek K

Aug 26, 2019

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

교육 기관: Sathiya P

Aug 27, 2019

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

교육 기관: 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.

교육 기관: Appa R M

Oct 24, 2019

The kernal is stuck for some questions and its annoying

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: 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: Sachin L

Sep 26, 2019

More examples and detailed explanation

교육 기관: Filippo M

Sep 27, 2019

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

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: Anmol K P

Oct 14, 2019

Course could have been more elaborate in depth and scenarios

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.

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: 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: 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: 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: 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: 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: Somak D

Oct 30, 2018

moderators do not respond to questions raised in forum. leading to incomplete learning

교육 기관: Karthik S

Jul 13, 2018

This course let me down. The crux of real-world is in analysis and in this course the author, IMHO, didn't do justice in explaining the concepts, the why are things done the way they are clearly; instead the author opted to breeze through things.

교육 기관: Santanu B

Apr 16, 2019

Not a great course. Sometimes it is too fast and the explanations are very short. More hands on exercises would have been more helpful.

교육 기관: jitao f

May 02, 2019

The content of this course is too basic. Though it provides enough knowledge to start a practice. No 0 to 1 but more like 0 to 0.1. And Forum support is terrible. Can't really answer my question( don't even think they have read it ).

교육 기관: Edwin S J

May 25, 2019

Suddenly introduced complex codes and statistical functions. Videos were way too fast.

교육 기관: Ismael S

Jun 02, 2019

Content is thrown to the student with too much information and videos of only 3-4 minutes. Too much to absorb and too little to practice properly