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Exploratory Data Analysis for Machine Learning(으)로 돌아가기

IBM의 Exploratory Data Analysis for Machine Learning 학습자 리뷰 및 피드백

4.6
별점
688개의 평가
159개의 리뷰

강좌 소개

This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing. By the end of this course you should be able to: Retrieve data from multiple data sources: SQL, NoSQL databases, APIs, Cloud  Describe and use common feature selection and feature engineering techniques Handle categorical and ordinal features, as well as missing values Use a variety of techniques for detecting and dealing with outliers Articulate why feature scaling is important and use a variety of scaling techniques   Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience  with Machine Learning and Artificial Intelligence in a business setting.   What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Calculus, Linear Algebra, Probability, and Statistics....

최상위 리뷰

AE

2021년 9월 26일

Very detailed course of Exploratory Data Analysis for Machine learning. Ready to take the next step in data science or Machine learning, this is great course for taking you to the next level.

ML

2021년 9월 21일

Excellent, very detailed. However, if the lessons can be expand for hypothesis testing and some of their common test like T test, Anova 1 and 2 way, chi square,..it would be better further.

필터링 기준:

Exploratory Data Analysis for Machine Learning의 163개 리뷰 중 26~50

교육 기관: Abhinav S

2022년 1월 10일

This course is not good at all. It is like the teacher is just the reading the screen and you wont understand anything. Not recommended professional certificate too.

교육 기관: SMRUTI R D

2021년 7월 26일

Although I had done such data analysis elsewhere in Coursera, this I found very comprehensive and systematic. I wish the topic of statistical significance tests was covered in some detail based on real data, rather random data generated for the purpose. I feel this area should receive more attention from the designers of the course. Thanks for all efforts put in by the faculty and all support person in the background. Thanks a lot..

교육 기관: ulagaraja j

2022년 1월 20일

Very friendly and extraordinary course for those who are looking for machine learning profession. The Data analysis and other process were well taken throughout the course. The Teaching members are well qualified and understandable so that we can have a clear thought on a particular concept. Finally an awesome course that no one should miss!!!

교육 기관: Nosaybeh A P

2022년 2월 5일

Thanks Coursera

my life has changed after Corona crisis and founding you!!!

Recommended for beginners as well as for those students, professionals who want to get their hands dirty in the data science life cycle.

Thanks to learning on Coursera , I'm able to add my courses to my Linkedin and resume that make me stand out from my peers.

교육 기관: Abhinav M

2020년 10월 25일

Peer Review needs some moderation, someone marked all zeros, for one of my assignments. We are doing Machine Learning clearly an algorithm for such can be made available. Overall a great Introduction and hands-on guidance towards the Tools and Statistics involved for various business applications in the real world.

교육 기관: Sarath B S

2020년 11월 26일

This is a real useful course which helps even a rookie to understand the nuances when it comes to Artificial Intelligence, Machine Learning. Interpreting Data etc.,

Subjects were taught well by the experts. I thoroughly enjoyed the learning session.

교육 기관: Orah S

2021년 1월 22일

Very! very!! interesting course, I really enjoy it, I will continue to put more effort into acquiring new skills as much as possible. Thank your IBM and Coursera for giving me this opportunity to learn through this platform.

교육 기관: Bishmer S

2021년 1월 25일

Thorough, clear video lectures, and good, meaningful exercises. An excellent introduction to the topic of Exploratory Data Analysis and figuring out the general characteristics of any given dataset and its features.

교육 기관: Chien N

2021년 6월 16일

A​ solid introduction to data analysis. There is a small note: the instructor uses a new version of pandas. If your notebook produces errors which are not suppose to appear, please update your pandas library.

교육 기관: Luis P S

2021년 4월 17일

Excelente como primera iniciativa en el mundo de Coursera empezar IBM. Claras las explicaciones de todos los videos. Muy buenos notebooks para el seguimiento de los temas aprendidos. Excelente!

교육 기관: ASIFIWE E

2021년 9월 27일

Very detailed course of Exploratory Data Analysis for Machine learning. Ready to take the next step in data science or Machine learning, this is great course for taking you to the next level.

교육 기관: Minh L

2021년 9월 22일

Excellent, very detailed. However, if the lessons can be expand for hypothesis testing and some of their common test like T test, Anova 1 and 2 way, chi square,..it would be better further.

교육 기관: Noor-ul-ain S

2021년 11월 23일

The course is exceptional and a huge learning opportunity for Exploratory Data Analysis. The final project is the best part of the course and helps to apply the concepts to real life data.

교육 기관: Ajay K S

2021년 8월 16일

IBM courses are most valuable courses, quite a lot of learning happens here. I recommend students when it is time to chose a Brand IBM can be considered in top 5 List. Happy learning.

교육 기관: VARUN B 2

2021년 6월 10일

Very nice course which explains beautifully about data cleaning and the statistical approach and then statistic model and then it ends with the hypothesis testing.

교육 기관: Chris B (

2021년 8월 2일

T​his course was really good for me because it went into depth on what I believe is the most important part of ML which is the data analysis and preparation.

교육 기관: Aman K

2021년 8월 13일

This is by far the best course I've encountered. It has an in-depth explanation of the codes they provide. Smooth and easy to understand language.

교육 기관: konutek

2020년 12월 7일

The instructor from videos is amazing. Great tutor. So far the courses from IBM Machine Learning Professional Certificate are really, really good.

교육 기관: Aleksandr K

2020년 12월 5일

I really liked, that you need to spend time on the independent work which consists of data preprocessing, EDA, and hypothesis testing.

교육 기관: My B

2021년 3월 31일

This is a well-structured course with easy-to-understand lectures and practical examples that help a lot in real data analysis life.

교육 기관: Rohit B

2021년 12월 9일

Very Clear ,Easy to Understand ,Good Explanation,Very Good Course.I just Upgrade myself doing this course.Thank you IBM Teachers :)

교육 기관: Pankaj Z

2021년 4월 7일

Very well curated course. Walks through all the topics in detail. Would be better if the professor had a little bit higher voice.

교육 기관: Suliman A

2022년 4월 13일

V​ery clear and well structured. You can see that lots of time went into the preparation of the course. Kudos to the lecturer.

교육 기관: Stephen C

2021년 6월 27일

A great course. You'll want to brush up on your python if you don't have a lot of time to dedicate after starting the course.

교육 기관: Ali A

2021년 5월 5일

This course was very helpful.I have learned a lot about feature engineering,expolatoray data analysis and hypothesis testing