4.6
stars
33,077 ratings

Jeff Leek, PhD +2 more instructors

687,941 already enrolled

Offered By

Johns Hopkins University

About this Course

257,567 recent views

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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Approx. 18 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish

What you will learn

Set up R, R-Studio, Github and other useful tools
Understand the data, problems, and tools that data analysts use
Explain essential study design concepts
Create a Github repository

Skills you will gain

Data Science
Github
R Programming
Rstudio

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Approx. 18 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish

Instructors

Instructor rating

4.48/5 (4,507 Ratings)

Offered by

Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.

Syllabus - What you will learn from this course

Content Rating96%(120,913 ratings)

Week

Week 1

5 hours to complete

Data Science Fundamentals

In this module, we'll introduce and define data science and data itself. We'll also go over some of the resources that data scientists use to get help when they're stuck.

5 hours to complete

5 videos (Total 40 min), 2 readings, 5 quizzes

Week

Week 2

5 hours to complete

R and RStudio

In this module, we'll help you get up and running with both R and RStudio. Along the way, you'll learn some basics about both and why data scientists use them.

5 hours to complete

5 videos (Total 34 min)

Week

Week 3

4 hours to complete

Version Control and GitHub

During this module, you'll learn about version control and why it's so important to data scientists. You'll also learn how to use Git and GitHub to manage version control in data science projects.

4 hours to complete

4 videos (Total 28 min)

Week

Week 4

5 hours to complete

R Markdown, Scientific Thinking, and Big Data

During this final module, you'll learn to use R Markdown and get an introduction to three concepts that are incredibly important to every successful data scientist: asking good questions, experimental design, and big data.

5 hours to complete

4 videos (Total 34 min)

Reviews

4.6

7064 reviews

5 stars
69.41%
4 stars
23.29%
3 stars
5.29%
2 stars
1.08%
1 star
0.90%

HIGHLIGHTS

"Foundational tools" in 243 reviews

"Introductory course" in 1056 reviews

TOP REVIEWS FROM THE DATA SCIENTIST’S TOOLBOX

by MFApr 12, 2020

Yeah, the robot voice is annoying. There needs to be better instruction on getting R Markdown to work. I tried in vain and gave up on it after looking at multiple forums with my same issue. Oh well.

by CCJun 10, 2016

A good basic class and collection of the tools. I wish there had been a little more explanation of what we would use the software for, but I found the lecture parts to be both concise and informative.

by KCJan 3, 2021

This course spoon-fed me as a beginner, which was great. The quizzes were well-done because they brought to light any weakness or gaps in my understanding so I could go back and review the processes.

by WCSep 25, 2017

I really don't know much about this stuff, I think the jury's still out on whether the last four weeks will be helpful in the future. We'll see how much I think I've learned at the end of the course

View all reviews

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

The Data Scientist’s Toolbox