學生對 IBM 提供的 Exploratory Data Analysis for Machine Learning 的評價和反饋

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.

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.

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.

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.

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.

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!

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.

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.

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.

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.

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.

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.

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.

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

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

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

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

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

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.

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

Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.

Recommended course for those wanting to advance their understanding about Exploratory Data Analysis for Machine Learning.

Best course very professional ,looking forward to complete the entire IBM Machine learning professional certificate

It was pretty good, just one of the reviewer gave me 0 points for some reason and I had to resubmit my assigment.

I learned a lot throughout this course. Also, i have my own project through the assignment! Thank you, Coursera.