Chevron Left
Python을 사용한 데이터 분석(으)로 돌아가기

IBM 기술 네트워크의 Python을 사용한 데이터 분석 학습자 리뷰 및 피드백

15,288개의 평가

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


2019년 4월 19일

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.


2020년 5월 5일

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.

필터링 기준:

Python을 사용한 데이터 분석의 2,311개 리뷰 중 2126~2150

교육 기관: Neo B

2019년 2월 11일

Data visualization was taught in details in course 7 and regression was taught in course 8. With no backgrounds, the codes in this course are scaring pe

교육 기관: Goh S T

2020년 4월 8일

The section on model development and evaluation is not so clear. It is difficult to understand if you have no prior knowledge of machine learning.

교육 기관: Girgis F

2018년 12월 31일

Course was great however i felt a lot of material was covered in a short period of time, this course can be 2 or 3 courses based on the content

교육 기관: Guillermo M M

2018년 8월 20일

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.

교육 기관: A P

2019년 6월 14일

Lots of spelling and grammatical errors that made it difficult to understand some of the material. It is otherwise an interesting course.

교육 기관: 靳文彬

2020년 3월 11일

There is no slides to download or review after class which makes it hard to go over the knowledge again without watching the video again

교육 기관: Siwei L

2020년 1월 23일

The video is too short and many concepts remain unclear or poorly explained. More contents need to be added to the questions and tests.

교육 기관: Carlos G R G d l C

2020년 3월 26일

It's an excellent course; the best part is the labs. It's a pity that we (the students) have a lot of problems loading the labs.

교육 기관: Pedro F

2019년 8월 22일

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

교육 기관: sangeet a

2020년 4월 8일

Things are too fast in this course and many things remain unexplained which makes it difficult for one to understand properly

교육 기관: Dominic M L C L

2019년 9월 15일

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

교육 기관: Adam J L J H

2020년 5월 24일

This course focuses a lot on the theory and explanation. However, there isn't much hands-on practice for the coding itself.

교육 기관: Osama W

2020년 8월 25일

*No response to some questions/comments on the forum

*More details/thorough clarification required for some points covered

교육 기관: Rishika A

2020년 3월 26일

There are many errors and this was even the toughest course I have taken yet since many things were not explained clearly

교육 기관: Kuzi

2020년 5월 6일

Course is flawless but when i had a technical challenge the Coursera team were clueless on how to fix it.

Otherwise good.

교육 기관: akash t

2020년 7월 11일

Few of the video requires improvement in terms of its quality. Particularly the lectures corresponding to week 4 and 5

교육 기관: Teofilo E d A e S

2019년 4월 16일

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

교육 기관: Julia S

2022년 2월 11일

I​t is okay in the sense that you learn something but the questions should be harder and it should go more in depth.

교육 기관: Vrinda M K

2019년 11월 25일

Topics covered are important but videos end abruptly as if narrator was saying something more and video just ended

교육 기관: Marc T

2020년 2월 3일

why is sharing of the notebook worth 3 points? That has absolutely nothing to do with python or data analysis!

교육 기관: Abhishek K

2019년 8월 26일

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

교육 기관: Sarah s

2019년 1월 2일

This course seems to have an exponential increase in a learning curve. It seemed to be all over the place.

교육 기관: Ramakrishna B

2019년 6월 19일

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

교육 기관: Camilo P T

2020년 6월 15일

Creo que le hace falta unas guías, toda la información se da por videos. Recomendado para principiantes.

교육 기관: Kenneth S

2020년 1월 12일

As always, the final project always ruins good courses. LAZY design of the projects is unacceptable.