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Advanced Data Science I

East Baltimore
1st term
3 credits
Academic Year:
2019 - 2020
Class Times:
  • M W,  1:30 - 2:50pm
Auditors Allowed:
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructor s:
Stephanie Hicks

R programming experience


Focuses on hands-on data analyses with a main objective of solving real-world problems. Teaches the necessary skills to gather, manage and analyze data using the R programming language. Covers an introduction to data wrangling, exploratory data analysis, statistical inference and modeling, machine learning, and high-dimensional data analysis. Teaches the necessary skills to develop data products including reproducible reports that can be used to effectively communicate results from data analyses. Trains students to become data scientists capable of both applied data analysis and critical evaluation of the next generation next generation of statistical methods.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. Obtain, clean, transform, and process raw data into usable formats
  2. Formulate quantitative models to address scientific questions
  3. Organize and perform a complete data analysis, from exploration, to analysis, to synthesis, to communication
  4. Apply a range of statistical methods for inference and prediction
Methods of Assessment:

This course is evaluated as follows:

  • 99% Homework

Enrollment Restriction:

Enrollment restricted to Biostatistics 2nd-year PhD and 2nd-year master's students only

Instructor Consent:

Consent required for some students

Consent Note:

Consent required for anyone who is not a Biostatistics 2nd-year PhD or 2nd-year master's student

For consent, contact: