Virtual Applied Data Science Training Institute (VADSTI) Training Series

Technological advancements and efficient use of computational tools have made it possible to generate and store large amounts of heterogeneous and complex datasets in many disciplines, including public health, clinical, biomedical, and genomics. There is therefore increased demand for data analytics capabilities including Artificial Intelligence (AI), and Machine learning (ML) to look at trends, predict outcomes, and make better clinical and health policy decisions.

The Howard University Research Centers in Minority Institutions, the AIM-AHEAD Data Science Training Core, and the Public Health Informatics Technology for District of Columbia (PHIT4DC) program is pleased to announce VADSTI 3.0, Spring 2024 Training Series to the Howard University community of researchers and beyond. The goal is to enhance data science capability and application by providing training in the foundations of programming and critical data analytic skills for planning and conducting research involving big data pertinent to biomedical, minority health and health disparities research. The Spring Training Series is project-based and will cover topics including AI and ML, Data Exploration and Visualization, Natural Language Processing and Large Language Models among others.

For questions, contact VADSTI at vadsti@howard.edu or John Kwagyan, Ph.D. at jkwagyan@howard.edu

For more information, visit rcmi.howard.edu/vadsti24

Program Objectives & Competencies

The primary objective of the 2024 VADSTI Spring Training Series is to provide training in data science fundamentals and cloud computing skills with hands-on application to minority health and health disparity datasets. Over the course of the training program, participants will:

• Be introduced to the foundations of AI and ML.
• Learn about various classification methods for ML.
• Learn about fairness and biases in AI and ML
• Lear about data exploration, and visualization using Power BI.
• Learn about natural language processing.
• Be introduced to large language models for healthcare data.
• Learn about security in the cloud environment.

Digital Certificate of Completion: Participants who complete all the modules and submit their projects in the VADSTI GibHub Data Science Project Portfolio will receive a verified digital certificate of completion.

Evaluation: At the end of each training module, you will be requested to complete electronic feedback forms on the extent to which expectations and objectives were met.

Registration & Fees: No fees for participation, but registration is required to attend.