CS 89.20/189: Data Science for Health
This course will cover state-of-the-art methods for data acquisition and analysis in a range of application domains such as cancer, cardiovascular diseases, diabetes, mental health, etc. Students will develop their skills by reading, presenting, and critiquing seminal research papers. The course will include assignments and a term-long project to reinforce concepts and methods widely used in data science.
It is critical to note that this is an advanced course that will be conducted in a seminar-style format.
A large amount of self-learning is required in this course. This includes digging into the details of data science methods presented in the readings to know when and how to use such methods in other applications.
COSC 74 (Machine Learning and Statistical Data Analysis) or instructor's permission
Experience with Python for data wrangling (COSC 1 alone is not sufficient)
Build data science competency by reading, presenting, and critiquing top research in the field
Practice with assignments and a project (all done with python)
Communicate your work through written and oral presentations
What is Data Science
“The ability to take data — to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it”