140.629.71
Data Science for Public Health II
Cancelled
- Location:
- Internet
- Term:
- 4th term
- Department:
- Biostatistics
- Credits:
- 4 credits
- Academic Year:
- 2022 - 2023
- Instruction Method:
- Synchronous Online
- Class Times:
-
- Tu Th, 8:30 - 9:50am
- Auditors Allowed:
- Yes, with instructor consent
- Undergrads Allowed:
- Yes
- Grading Restriction:
- Letter Grade or Pass/Fail
- Course Instructor:
- Contact:
- Brian Caffo
- Frequency Schedule:
- One Year Only
- Resources:
- Prerequisite:
140.628, prior programming experience, precalculus mathematics
- Description:
-
Presents the basics of data science using the python programming language. Teaches basic unix, version control, graphing and plotting techniques, creating interactive graphics, web app development, reproducible research tools and practices, resampling based statistics and artificial intelligence via deep learning, focusing on practical
implementation specifically tied to computational tools and core
fundamentals necessary for practical implementation. Culminates with a web app development project chosen by student (who will come out of this course sequence well-equipped to tackle many of the data science problems that they will see in their
research).
- Learning Objectives:
-
Upon successfully completing this course, students will be able to:
- Demonstrate proficiency in data-orientedR programming
- Practice basic data cleaning in R
- Implement and demonstrate proficiency in tidyverse commands
- Implement plotting and interactive graphics tools on novel data sets
- Implement artificial intelligence programs on novel data sets
- Create a web application
- Implement resampling-based statistics
- Synthesize concepts of machine learning overfitting
- Synthesize concepts of probabilistic inference
- Methods of Assessment:
This course is evaluated as follows:
- 66% Homeworks/coding projects
- 33% Final Capstone Project
- Instructor Consent:
No consent required