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Python을 사용한 데이터 분석(으)로 돌아가기

IBM의 Python을 사용한 데이터 분석 학습자 리뷰 및 피드백

4.7
별점
15,077개의 평가
2,271개의 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 2,276개 리뷰 중 26~50

교육 기관: Peter A

2019년 10월 16일

Too many mistakes in the lectures and the main lab. Confusing for new learners when the math is wrong or the python syntax is wrong. Anyone who rates this above 3 stars you are simply not paying attention to the myriad of mistakes.

교육 기관: Ivo M

2018년 12월 19일

The course had plenty of errors in the videos, Labs and quizzes. The explanations were rushed at times and quite a bit was not easy to follow. The worst course so far!

교육 기관: Javier M

2021년 4월 28일

The content is solid. However, the labs which are the best tools of this course because they allow you to actually do the exercises and go deeper in the concepts are not working. It has been like that for some weeks.

I contacted support and I saw in the course forum lots of people complaining about it but either Coursera or IBM don't seem to care. No answer from them for weeks. I had to dig into forums in the Internet to find alternative solutions to access the labs... which was a waste of time considering that I'm not auditing but paying for this course.

So terrible customer experience, that's why I put one star.

교육 기관: Sobhan A

2020년 5월 6일

Low quality.

Do not recommend this course at all.

Boring teaching method.

Full of errors.

No IT support for problems.

교육 기관: HIMANSHU S

2020년 7월 30일

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.

교육 기관: Usman A

2020년 7월 29일

AN excellent course. Hands-on training on the cloud makes an individual really involved. So far the best online course I have ever taken, and I have learned Python programming a lot from this course.

교육 기관: Hakki K

2020년 7월 9일

Hi,

I completed entire program and received the Professional Certificate. On the Coursera link of my certificate "3 weeks of study, 2-3 hours/week average per course" is written. This information is not correct at all, it takes approximately 3 times of that time on average! I informed Coursera about it but no correction was made. It should be corrected with "it takes approximately 19 hours study per course" or "Approx. 10 months to complete Suggested 4 hours/week for the Professional Certificate".

Here is the approximate duration for each course can be found one by one clicking the webpages of the courses in the professional certificate webpage: (*)

Course 1: approximately 9 hours to complete

Course 2: approximately 16 hours to complete

Course 3: approximately 9 hours to complete

Course 4: approximately 22 hours to complete

Course 5: approximately 14 hours to complete

Course 6: approximately 16 hours to complete

Course 7: approximately 16 hours to complete

Course 8: approximately 20 hours to complete

Course 9: approximately 47 hours to complete

This makes in total approximately 169 hours to complete the Professional Certificate. As there are 9 courses, each course takes approximately 19 hours (=169/9) to complete.

(*): https://www.coursera.org/professional-certificates/ibm-data-science?utm_source=gg&utm_medium=sem&campaignid=1876641588&utm_content=10-IBM-Data-Science-US&adgroupid=70740725700&device=c&keyword=ibm%20data%20science%20professional%20certificate%20coursera&matchtype=b&network=g&devicemodel=&adpostion=&creativeid=347453133242&hide_mobile_promo&gclid=Cj0KCQjw0Mb3BRCaARIsAPSNGpWPrZDik6-Ne30To7vg20jGReHOKi4AbvstRfSbFxqA-6ZMrPn1gDAaAiMGEALw_wcB

교육 기관: Matthew A

2021년 4월 13일

During the 4th week of the course, lots of important information and explanations are over summarized and in some cases skipped over. Learning tools outside of what is provided in the course or a decent understanding statistics is required in order to be successful in this course.

교육 기관: Vincent L

2018년 9월 17일

Ton of errors, both minor and major, in the videos and the quizzes. For example, saying the a difference between two variables is significant because p > 0.05. I report them all and I've stopped counting.

Not professional at all.

교육 기관: Thamarak

2020년 8월 22일

This course is too hard. This should be go on more slowly and explain more about meaning of each value described. The course is not for beginner and not for a person who doesn't have enough statistics background.

교육 기관: Anastasiya B

2019년 9월 22일

Low technical quality of the course with lots of typos, errors and comletely mess in final assignment.

Low quality of material, bad structure, and you can get your certificate just by clicking shift+ enter

교육 기관: John K

2019년 7월 7일

Poorly put together course - especially the labs. Frequent misspellings, incorrect links and confusing instructions. The technical problems are a greater challenge than the course material.

교육 기관: Titans P

2020년 8월 17일

worst ever

the greatest thing i have learned here is patience and searching online

교육 기관: Uygar H

2019년 3월 14일

I have really learned many things in this course which are meaningful and helpful in real life. It is not just lines and numbers , it is exciting how you can apply these methods to find solutions in your real life problems. Combined with strong Python skills , you will enjoy more..Thank you

교육 기관: Daniel T

2019년 4월 9일

This was a great review of stuff math I learned in high school and college. Of course it's all easy now because it's baked into Python. We used to do it by hand and with slide rules back in the early 1970s

교육 기관: Shashank S C

2020년 5월 6일

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.

교육 기관: Firat E

2019년 6월 4일

It is really a good course, simple to understand and very complete. Thank you !

교육 기관: Ashirwad S

2019년 5월 21일

Recommended course to understand the how to do data analysis using python

교육 기관: Jim C

2019년 5월 20일

Well organized, good explanations, and very good labs.

교육 기관: Aditya M

2019년 5월 21일

Overall apt content for beginners and naive learners.

교육 기관: Vineet M N D

2019년 5월 20일

Great experience

교육 기관: Shernice J

2019년 3월 30일

Instead of having a lab after each topic, this course one lab per week encompassing all of the topics. Some might find that better than having smaller labs but to me the information was assimilated better when i did a lab right after the topic. That being said, you can open the lab first and follow along with/after each video. You just need to be mindful of what works best for you. Taking time to understand the code is a must and some more documentation would be helpful. I wasn't a beginner with Python and it took some time and work out what was happening at times.

교육 기관: Akiru J C

2022년 4월 12일

I really enjoyed this course. Few things to suggest:

- Go over Statistics in more detail. Had I not studied Statistics in university, I may have found this topic confusing.

- Felt like I could have learned more if the labs were not filled-out halfway

- Too many multiple choice questions in the quiz and final. These should be more interactive with lines of code we would type insetad of clicking a bullet.

- The math covered in this course was very high level. I.e., Chi-square and linear regression require more hands-on practive in order to grasp.

교육 기관: Itshak C

2021년 4월 13일

Loved the labs. Hated the Videos. The amount of information that is thrown at you in a 1 min video is very unsettling as it makes you think you haven't understood a word of what they say and then the labs immediately clear everything up and then you feel like the smartest person alive. It's an uphill battle at times but the end result is pretty helpful regardless of the reason you're perusing the course.

교육 기관: Devansh N

2020년 5월 5일

Was a bit tough to keep up at the week 4 and week 5 but overall a very good course