140.711.01
Advanced Data Science I
Location
East Baltimore
Note: Due to the COVID-19 Pandemic, this
course was held in a virtual/online format.
Term
1st Term
Department
Biostatistics
Credit(s)
3
Academic Year
2020 - 2021
Instruction Method
TBD
M, W, 1:30 - 2:50pm
Auditors Allowed
No
Available to Undergraduate
No
Grading Restriction
Letter Grade or Pass/Fail
Course Instructor(s)
Course Instructor(s)
Jeffrey Leek
Contact Name
Frequency Schedule
Every Year
Resources
Prerequisite
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:
- Obtain, clean, transform, and process raw data into usable formats
- Formulate quantitative models to address scientific questions
- Organize and perform a complete data analysis, from exploration, to analysis, to synthesis, to communication
- Apply a range of statistical methods for inference and prediction
Methods of Assessment
This course is evaluated as follows:
- 99% Homework
Final grade applies to all terms
Enrollment Restriction
Enrollment restricted to Biostatistics 2nd-year PhD and 2nd-year master's students only