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TADA Courses

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TADA Coursework

The following coursework is required of all TADA fellowship and certificate trainees. Courses are open to all Laney Graduate students with permission from the course instructors, with priority given to fellowship and certificate students.

This course will prepare students to conduct ethical, rigorous, and theoretically-informed analyses of two types of “big data” (administrative and geospatial data) in the context of research and interventions into intersecting crises of substance use disorders (SUDs) and drug-related harms. It will apply the strengths of social and behavioral sciences – including a focus on theory and validity – to the emerging field of advanced data analytics. 

Pre-Requisites: This course will require computing in different programs and different environments. Familiarity and comfort with the following is needed to successfully complete the course:

  • Regression (examples: BIOS 501, BSHES 700)
  • SAS (examples: BIOS 501)
  • R (examples: BIOS 544)

This course will prepare students to conduct ethical, rigorous, and theoretically-informed analyses of unstructured “big data” (machine learning/social media) in the context of research and interventions into intersecting crises of substance use disorders (SUDs) and drug-related harms. It will apply the strengths of social and behavioral sciences – including a focus on theory and validity – to the emerging field of advanced data analytics.

 

Pre-Requisites: It is recommended that students be comfortable programming in R or a similar programming language. Prior completion of the following courses/ equivalents is also needed to successfully complete this module:

 

  • Regression (e.g. BIOS 501, BSHES 700, BMI 510)
  • At least one statistical programming course, such as SAS (e.g.BIOS 501),  R (e.g.BIOS 544) or Python (BMI 500)

This is a reading/seminar course to be taken four semesters during the dissertation phase. Course activities include:

  1. TADA Journal Club: readings of scientific literature, group discussion, demonstrations of techniques, and two to four in-depth discussions with authors of recent research in the area detailing data sources, techniques used, and challenges along the way
  2. Professional development: selected topics to enhance students’ professional trajectories as research professionals applying advanced data analytics to address drug-related harms
  3. Dissertation workshop: Each student provides updates on their dissertation progress and will be encouraged to bring questions/challenges to the class for discussion.

Prerequisite: Open to current TADA fellows and certificate students. Other interested graduate students may enroll with approval from the instructors.

Tracks include: 

  • Geospatial analysis
  • Analyzing large administrative databases
  • Machine learning

Each course must be a minimum of 2 credits. Courses completed prior to fellowship may apply with approval from TADA director(s)

See list for course ideas. You are not limited to this list and may request approval to take courses outside of Emory with TADA leadership approval.

Trainees in SBS departments typically gain these competencies as part of their required coursework.

Data science students will use electives to fulfill this requirement with either:

  • Advanced Social Epidemiology (EPI594, 3 credits)
  • Structural Interventions in Public Health. (EPI 590R, 2 credits)