What you'll learn
Week 2: Installing the Toolbox
Week 3: Conceptual Issues
Week 4: Course Project Submission & Evaluation
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.
Access to a computer or mobile device with an internet connection.
Motivation to learn!
There are no special materials or prerequisite knowledge required for this course.
Who this course is for
Students who are new to this field
Students willing to put in a couple hours to learn about The Data Scientist’s Toolbox
Advanced students wanting to add another skill to their portfolio
Jeff Leek, PhD – Associate Professor, Biostatistics – Bloomberg School of Public Health
Roger D. Peng, PhD – Associate Professor, Biostatistics – Bloomberg School of Public Health
Brian Caffo, PhD – Professor, Biostatistics – Bloomberg School of Public Health
This course includes
Option for learning at your own pace
Videos and reading material about the course
Assessed tasks with feedback from other course participants
Evaluated tests with feedback
Evaluated programming tasks