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140.629.41
Data Science for Public Health II

Location:
East Baltimore
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
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:

  1. Demonstrate proficiency in data-oriented python programming
  2. Practice basic data cleaning in pythnon
  3. Implement and demonstrate proficiency in tidyverse commands
  4. Implement plotting and interactive graphics tools on novel data sets
  5. Implement artificial intelligence programs on novel data sets
  6. Create a web application
  7. Implement resampling-based statistics
  8. Synthesize concepts of machine learning overfitting
Methods of Assessment:

This course is evaluated as follows:

  • 66% Homeworks/coding projects
  • 33% Final Capstone Project

Instructor Consent:

No consent required

Special Comments:

Please note: This is the virtual/online section of a course that is also offered onsite. Students will need to commit to the modality for which they register.