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.
Offered By
Johns Hopkins University
About this Course
384,388 recent views
Learner Career Outcomes
39%
started a new career after completing these courses
35%
got a tangible career benefit from this course
What you will learn
Create a Github repository
Explain essential study design concepts
Set up R, R-Studio, Github and other useful tools
Understand the data, problems, and tools that data analysts work with
Skills you will gain
Data ScienceGithubR ProgrammingRstudio
Syllabus - What you will learn from this course
Week
13 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 videos (Total 40 min), 2 readings, 5 quizzes
5 videos
What is Data Science?9m
What is Data?6m
Getting Help10m
The Data Science Process9m
2 readings
Welcome5m
A Note of Explanation2m
5 practice exercises
What is Data Science?6m
What is Data?6m
Getting Help Quiz6m
Data Science Process8m
Module One Summative Quiz30m
Week
23 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 videos (Total 34 min), 6 quizzes
6 practice exercises
Installing R8m
Installing R Studio4m
RStudio Tour8m
R Packages10m
Projects in R6m
Module Two Summative Quiz30m
Week
32 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 videos (Total 28 min), 5 quizzes
4 videos
Github and Git8m
Linking Github and R Studio4m
Projects under Version Control4m
5 practice exercises
Version Control6m
GitHub and Git10m
Linking Git/GitHub and RStudio6m
Projects under Version Control8m
Module Three Summative Quiz30m
Week
45 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.
4 videos (Total 34 min), 6 quizzes
5 practice exercises
R Markdown10m
Types of Data Science Questions6m
Experimental Design14m
Big Data6m
Module Four Summative Quiz30m
4.5
4223 ReviewsTop reviews from The Data Scientist’s Toolbox
Highlights
Introductory course
(1056)Foundational tools
(243)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.
This course was a good intro especially in setting all the necessary software for future courses. I suggest to read the manuals, books and other readings the profs suggest. The resources are helpful.
Instructors
Jeff Leek, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Roger D. Peng, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Brian Caffo, PhD
Professor, BiostatisticsBloomberg School of Public Health
About 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.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
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.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.