Created by:  Johns Hopkins University

  • Roger D. Peng, PhD

    Taught by:  Roger D. Peng, PhD, Associate Professor, Biostatistics

    Bloomberg School of Public Health

  • Jeff Leek, PhD

    Taught by:  Jeff Leek, PhD, Associate Professor, Biostatistics

    Bloomberg School of Public Health

  • Brian Caffo, PhD

    Taught by:  Brian Caffo, PhD, Professor, Biostatistics

    Bloomberg School of Public Health
Basic Info
Course 4 of 10 in the Data Science Specialization.
Language
English, Subtitles: Chinese (Simplified)
How To PassPass all graded assignments to complete the course.
User Ratings
4.6 stars
Average User Rating 4.6See what learners said
Syllabus

FAQs
How It Works
Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers
Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates
Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Creators
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.
Pricing
AuditPurchase Course
Access to course materials

Available

Available

Access to graded materials

Not available

Available

Receive a final grade

Not available

Available

Earn a shareable Course Certificate

Not available

Available

Ratings and Reviews
Rated 4.6 out of 5 of 1,973 ratings

I love the course. However, the treatment of PCA, SVD, and colors seems to me very long and slow. Maybe a more direct and quick overview would be better. Even with that expection I really enjoy the course.

Graphs and plotting is at the heart of data analysis and data science, and without it you would have difficulty conveying ideas, and having graphs to explain numerical/statistical data is always handy. Visual representation of a data set, and using visual cues to gain an understanding of data, can save a lot of time, and can help you gain additional insights into the data. This course teaches you key techniques on how to apply some graphing and plotting methods to visually explore data, and it does so really well and in great detail, and also provides some good demos.

Clustering is overwhelming field of knowledge.

It was a lot of material in a short time frame, but I feel like I really have a good grasp of creating graphs in R.