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Course Catalog

140.711.01 Advanced Data Science I

Department:
Biostatistics
Term:
1st term
Credits:
3 credits
Academic Year:
2017 - 2018
Location:
East Baltimore
Class Times:
  • M W,  1:30 - 2:20pm
Auditors Allowed:
No
Grading Restriction:
Letter Grade or Pass/Fail
Contact:
Jeffrey Leek
Course Instructors:
Resources:
Prerequisite:

R programming experience

Description:

Provides an intensive introduction to applied statistics and data analysis. Trains students to become data scientists capable

of both applied data analysis and critical evaluation of the next generation next generation of statistical methods. Since both data analysis and methods development require substantial hands-on experience, focuses on hands-on data analysis.

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:

Four data analysis projects (25% each)

Enrollment Restriction:

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:

jtleek@gmail.com

Special Comments:

One 1-hour lab per week (time TBA)