ADTDS: Curriculum Overview

The ADTDS training program builds upon existing graduate training programs within the CWRU School of Medicine to develop competencies focused on Alzheimer’s Disease, with training at the intersection of data science and clinical/translational research.
These competencies emphasize quantitative skills that will allow the in-depth analyses of complex big data sets and include topics including:

•    Statistical and Computational Approaches
•    Alzheimer’s Disease Mechanisms
•    Data Generation and Integration
•    Communication Skills
•    Data Stewardship and Bioethics
Specific required core courses: 

•    PQHS 431: Statistical Methods I
•    PQHS 490: Epidemiology: Introduction to Theory and Methods
•    PQHS 451: A Data-Driven Introduction to Genomics and Human Health
•    MMED 501: Principles of Clinical and Translational Research
•    MMED 415 or CBIO 453: Cell Biology

Together, these courses enforce cross-training between the Data Science and Clinical/Translational Science areas and provide a strong foundation in the basic skills necessary to become a capable researcher in both domains. 

Electives are usually determined by the graduate program each student is already in. The ADTDS program only requires this core set of courses, most of which trainees will have had already as part of their graduate training.

The program also includes regular meetings of the cohort to discuss work, and related published research, and to informally exchange ideas in a supportive environment.

Each trainee will select a mentor and a dissertation committee – as with any PhD program – and must pass a progress exam on didactic learning typically scheduled early in the second year of their PhD program. That is followed by a proposed dissertation defense, and then the defense of the final thesis as the culmination of their studies.