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Python을 사용한 데이터 분석(으)로 돌아가기

IBM의 Python을 사용한 데이터 분석 학습자 리뷰 및 피드백

4.7
별점
12,959개의 평가
1,893개의 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
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.

SC
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 1,873개 리뷰 중 1376~1400

교육 기관: asher b

2018년 11월 12일

this course finally gets to some key Python functions for data analysis. Some of this may be difficult without a basic stats background. Only knock is there are MULTIPLE typos in the slides and labs. Needs to get fixed.

교육 기관: Miranda C

2020년 7월 23일

This course went fairly well, I just hope that the information will be repeated in the next course in the certificate program (IBM Data Science certificate) as I don't feel like the information has really sunk in . . .

교육 기관: Ankit S C

2020년 1월 15일

The Model Training and Evaluation weeks could have been more elaborate. Instead of just telling to do something, it would've been better to explain why we are doing it and how is it working internally, at a high level.

교육 기관: Mario A T

2020년 2월 28일

Tuve problemas con crear la cuenta en IBM cloud con mi correo personal primario , no pude encontrar soporte ni orientación de que hacer , me toco ingresar con otro correo , no se porque no fue posible con el mio

교육 기관: Junior N

2019년 8월 18일

This course is pretty good and give a good introduction to data analysis with python. However, there is a problem in the course's methodology : functions are given without any introduction...just implementations.

교육 기관: Glison M

2020년 8월 9일

The course was good in introducing Pandas, Numpy and Sci-kit to beginners. Adding more graded programming activities would be a great addition to this course, as there is only one graded programming assignment.

교육 기관: Orsolya N

2020년 6월 26일

Certain parts were too fast, and there were some technical issues with the labs at times, but there's always the possibility to look up the blurry parts online. Overall it was interesting and well put together.

교육 기관: Kyle H

2020년 2월 25일

This definitely could be more project based than it was, and focus more on applying coding skills than just reading them and watching videos about them, but it's a great overview of some useful techniques.

교육 기관: Keerthi S

2019년 11월 3일

The final assignment had some errors in submission with some questions not allowing for upload of the answers (Question 3, i.e.). Did not feel great about this error. Otherwise, great course - very useful.

교육 기관: Mantra B

2019년 11월 3일

Overall a great course. All essential Data Analysis processes are covered in this course. A small nitpick is that Week 5 material was a little less in depth. Moore examples in videos will be a great help!

교육 기관: Saptashwa B

2019년 1월 18일

Great course for introductory data analysis with Python. Very good for fundamental understanding of overfitting, underfitting, precision, accuracy and using grid search method to optimize fit parameters.

교육 기관: Harshit R

2020년 8월 8일

Some Statistical terms and concepts were covered quite briefly due to which some amateur student has to refer additional contents like Youtube. Same with me. Quizes can be made tougher to raise the bar.

교육 기관: Sule C

2020년 8월 12일

Thank you very much to the instructors. I liked the course but it could have been better designed. More exercises ascending from easy to hard & real and teaching quiz questions would make it perfect.

교육 기관: Roberto M

2020년 6월 10일

Great course to learn the basics for Data Analytics using Python.

I really liked the framework and data analysis template or process given in the labs. I will use them as a reference for my real job!

교육 기관: Brijesh D

2019년 11월 23일

Really interesting course, if one wants learn programming language. Well designed and structured. Only suggestion is, if the small videos contains example that be really great to understand it well

교육 기관: Luis M

2020년 3월 10일

Very good course that goes straight to the main topics needed to work on data analysis using Python. This will kick start my learning process which will be followed with a lot of coding practices.

교육 기관: Bharat M

2020년 7월 16일

Although good to learn the know-how of basic data analysis techniques, the quizzes are predictable and you don't end up coding as much as you should.

A good starter course to wet your feet in DA!

교육 기관: wangqiucheng

2020년 4월 7일

Very clear and easy to learn. The lab helps a lot, it gives me an intuitive instruction of the class. But some of the points seem too shallow, hope the course could provide some deep knowledge.

교육 기관: Rahi J

2018년 10월 17일

It will be helpful if a video is added on:

1) how to store multiple results from different models in single dataframe

2) how to automate the process. More example needed on Grid and Pipeline.

교육 기관: Rodrigo D

2019년 2월 24일

Great course, you can understand in a general way the use os Python to analyse raw data and organice it to create a better model. However I couldn't use in a proper way the external tool.

교육 기관: Mason C

2020년 4월 28일

Theory and examples are good. Suggest having full and complete Python course code with more examples of each coding. So we can get more ideas and understanding of the Python environment.

교육 기관: NAPA S M

2019년 5월 7일

Questions while listening to lessons in some of the lectures are coming before theory explained by the teacher .Better if question is at least 10 seconds after related theory explained.

교육 기관: Cristian A M L

2020년 2월 17일

Los temas tratados son muy útiles y se desarrollan de gran manera. El herramienta de LAB es la más completa del curso. Considero que se puede aumentar la rigurosidad de la evaluación

교육 기관: Daniel A

2019년 5월 31일

This was pretty good, I think maybe the best in the IBM machine learning certificate. I took Andrew Ng's course prior to this, so to watch python sklearn in action was a real treat.

교육 기관: SHALINI G

2018년 10월 1일

It is a good course for beginners but I feel that the quizzes could have been a bit more challenging. And if the codes were executed in the Python domain , it would have been nice.