Learner Reviews & Feedback for Data Analysis with R by IBM

4.7

stars

309 ratings

About the Course

The R programming language is purpose-built for data analysis. R is the key that opens the door between the problems that you want to solve with data and the answers you need to meet your objectives. This course starts with a question and then walks you through the process of answering it through data. You will first learn important techniques for preparing (or wrangling) your data for analysis. You will then learn how to gain a better understanding of your data through exploratory data analysis, helping you to summarize your data and identify relevant relationships between variables that can lead to insights. Once your data is ready to analyze, you will learn how to develop your model and evaluate and tune its performance. By following this process, you can be sure that your data analysis performs to the standards that you have set, and you can have confidence in the results. You will build hands-on experience by playing the role of a data analyst who is analyzing airline departure and arrival data to predict flight delays. Using an Airline Reporting Carrier On-Time Performance Dataset, you will practice reading data files, preprocessing data, creating models, improving models, and evaluating them to ultimately choose the best model. Watch the videos, work through the labs, and add to your portfolio. Good luck! Note: The pre-requisite for this course is basic R programming skills. For example, ensure that you have completed a course like Introduction to R Programming for Data Science from IBM....

Top reviews

Dec 5, 2021

It is excellent course. I recommend for all that do not have a lot of knowledge and experience in data analysis with R Programming. Thank you for this opportunity.

Aug 3, 2021

I could not use WatsonStudio and used RStudio instead. It might have caused problems to the reviewers of peer assignment. Course content is good.

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26 - 43 of 43 Reviews for Data Analysis with R

By Suvegan G

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Nov 17, 2021

Course is very good.

By gerald m

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Jul 31, 2023

Excellent course

By Kyla M T D C

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Jul 1, 2022

learned a lot!

By Wahab A

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Feb 27, 2023

Best Course.

By Janna D

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Jul 10, 2022

nice course

By Ahnami A

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Jul 17, 2024

Fantastic

By Krishna S A T

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Apr 11, 2023

VERY GOOD

By Kevin Q

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Nov 10, 2022

next onE

By Ramzi B S

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Sep 3, 2023

Great

By B A

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Oct 9, 2024

Good

By Eslavath S

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Sep 17, 2024

nice

By Deependu G

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Oct 1, 2023

The only problem for me was understanding that lab practice problems are in Jupyter Notebook, instead of the R script! Strange but dealt with it!

By Respect M

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Sep 24, 2022

this course is not for the week, its not challenging but you have to litle dictated...

By Fateme E

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Jan 16, 2024

This course was more theoretical than practical

By Franchesca L R D

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Apr 18, 2022

A few issues but fixable.

By TheNanoDudE D

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Jun 29, 2023

Honestly, I was a little underwhelmed by the way this course was delivered. There were a number of new and complex topics that were introduced but were very poorly discussed, including tidy models using recipes, and regularization using lasso and regression. Some of these things were quite new to me, and it would have helped to get specific practice. Alternatively, it seemed the course tried to cover too many things, and things like the recipes could have been dropped. I also did not understand why I ended up spending so much time setting up a Watson account, when my time was limited on it, and I could have done the project in the Jupyter notebook anyway.

By Brad C

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Oct 11, 2024

The first four modules are pretty good, albeit fast-paced. Module 5 presents a lot of information too quickly; it would be better split across multiple modules and more labs. The AI grader for the final project seems overly harsh/buggy and it was challenging to figure out what needed to be included in the screenshot to get credit.

By Marciano A P

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Jan 31, 2023