Chevron Left
The Data Scientist’s Toolbox に戻る

ジョンズ・ホプキンズ大学(Johns Hopkins University) による The Data Scientist’s Toolbox の受講者のレビューおよびフィードバック



In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio....
Foundational tools
Introductory course



Sep 08, 2017

It was really insightful, coming from knowing almost nothing about statistics or experimental design, it was easy to understand while not feeling shallow. Just the right amount of information density.


Apr 15, 2020

As a business student from Bangladesh who is aspiring to be a data analyst in near future, I love this course very much. The quizzes and assessments were the places to check how much I exactly learnt.


The Data Scientist’s Toolbox: 426 - 450 / 5,972 レビュー

by N S C R

Mar 09, 2019

This course helps to understand the usage of R with RStudio and Git integration with RStudio.

I Recommend this course to all those aspirants who are moving towards Data Science.

by Rushil K

Mar 04, 2018

Everrything is good but how do I access some links in the video. The PDF files I download, also don't seem to have it. Unless it is a problem with my adobe reader - let me know

by Solange M T Y

Nov 15, 2017

I liked very much, brought lots of information according to Data Science. Thanks! I appreciate a lot the first course and preparing myself to participate of the others courses.

by Connor H

Sep 18, 2017

Maybe a little slow if you already have some technical exposure, but pretty straight forward and easy to follow if you don't. A well balanced class in my not so humble opinion.

by Rafael S

May 16, 2017

This course is great, mainly for people without any experience in the field as it is very basic and introductory, I'm very anxious to see how we are going to advance from here!

by miguel G

Mar 06, 2017

This course is the first step to dive into the data science course. One finds a lot of videos about how to create and use the tools to carry out the specialization. Great job!

by Nicolas A

Jul 05, 2020

Es una Especializacion muy importante y el manejo pedagogico y metodologico Que realizan los profesores,ayuda mucho a los que estamos iniciando en este campo del conocimiento

by Zhou C

Jan 14, 2018

Great first course of the whole specialization! This basic one is very important for later study because "Grinding a chopper will not hold up the work of cutting firewood" : )

by Rian D

Jan 08, 2018

Great overview to all the skills and applications we will be using later in the Data Science Specialization. It is brief but was great to get an overview of R, github, etc ...

by Garima S

Sep 11, 2020

I found the course really useful. It helped me to develop a basic understanding of Data Science. I'm really looking forward to continue with the remaining courses. Thank you.

by Jan K

Mar 07, 2017

Nice introduction to many basic tools and concepts that are substantial to the work of a data scientist. Also, a good start for a person encountering MOOC for the first time.

by Ayesha S

Jan 04, 2017

Thorough grounding in the basics. Even a novice like me could grapple with it, even though it did not come naturally, all the information was accessible for tasks. Thank you.

by Dr. R R K

Aug 07, 2020

It's quite challenging learning this course being a biotechnologist. With coursera, the concepts and skills which I learned can be directly applied to my field of research.

by Bhargava B

Feb 16, 2018

This is an introductory course. This helps those who are starting from the absolute basis level, and the course does a good job with regard to getting the feel of the tools.

by Farhan

Dec 02, 2017

Great Introductory course on Data Science. Would have been better if it covered a little more. But as the first course in the specialization, it covers all the basic fields.

by Ozgur O C

Jan 04, 2017

Fantastic introduction to a topic I always found daunting. Thanks to everyone involved for preparing such an informative and soft approach to a hard topic like data science.

by Jonathan L

Jun 11, 2016

Very simplistic and could be covered in a handout as part of another course. Unfortunate that this is a requirement of the specialization, otherwise I would have skipped it.

by André A

Sep 24, 2020

Very good course, it gives a good start at data science and gives a good explanation about version control and linking Git and Github with RStudio, which is very important.

by Ludwing G F F

Aug 23, 2020

A pretty good introductory course to Data Science, delivers the good tools to know the environment, the main theory and some useful guide to how resolver incoming problems.

by Prem K S

Jun 16, 2019

Interactive, informative, valuable course for beginners who wants to make career in data science and analysis. Learned data analysis tools and introduction on data science.

by Eduardo A R A

Dec 31, 2017

Very nice course to present a panorama of what is data science as well as the main tools used. I strongly recommend buy the "Elements of Data analytics style" From J. Leek.

by Shashikesh M

May 16, 2017

This was a great experience for me, I would personally recommend every data science aspirant to take this course before starting with programming in R or Python language.

by Mikkel H J

Mar 17, 2017

Give a brief and concise introduction to many of the tools a data scientists should be familiar with. It serves as a good starting point for someone getting into the field.

by JT

Apr 04, 2016

As a novice to data science, this was an excellent introduction into the (very) basics behind how to get started in the field. Great way to begin an education in this area.

by Vicki P

Aug 30, 2020

I think that the course was great for a beginner. It explained things clearly and went through things step by step. While a lot was covered, it wasn't overwhelming at all.