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Virtual Applied Data Science Training Institute (VADSTI) 2025 Training Series: Module 6 - Machine Learning II

Date Wed, Mar 26 - Thu, Mar 27
Time 5: 00 PM - 8: 00 PM
Location Zoom

Howard University Research Centers in Minority Institutions (RCMI), Public Health Informatics Technology for District of Columbia (PHIT4DC), and GHUCCTS are pleased to announce VADSTI 4.0, Spring 2025 Training Series to the Howard University research community, the workforce in the District of Columbia and the surrounding region. 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 and minority health and health disparities research.

This free Spring Training Series will cover topics including, Foundations of Data Science, Introduction to Python, Basic Statistical Concepts, Data Exploration & Visualization, Experimentation in Data Science, and introduction to algorithmic techniques in Machine Learning.

Program Objectives & Competencies

The primary objective of the 2025 VADSTI Spring Training Series is to provide training in data science fundamentals, and 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 principles of data science.
  • Gain practical, hands-on experience with Python and related libraries for accessing data from multiple sources and use analytic methods for analyses.
  • Learn about data exploration, and visualization using Python.
  • Be introduced to probability and statistical analysis concepts utilized in data science.
  • Learn about principles and applications of A/B testing
  • Understand the concepts of data partitioning and practice behind supervised learning.
  • Be introduced to algorithmic techniques in machine learning.

Digital Certificate of Completion: Participants who complete all the modules and submit their projects in the VADSTI GitHub 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 to the extent to which expectations and objectives were met.

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

Learn More | For questions contact: phit4dc@howard.edu and rcmi@howard.edu

Module 6 | Machine Learning II

Wednesday, March 26 & Thursday, March 27, 2025
5:00 PM – 8:00 PM EST


INSTRUCTOR:  Ebelechukwu Nwafor, PhD
Part II builds on these basics from Part I, introducing unsupervised learning techniques such as clustering and dimensionality reduction. The module will also cover key concepts like overfitting, and model selection. By the end, students will understand both theoretical and practical aspects of machine learning, with hands-on experience in building and evaluating models using tools like Scikit-Learn.

Upcoming Events
This free Spring Training Series will cover topics including, Foundations of Data Science, Introduction to Python, Basic Statistical Concepts, Data Exploration & Visualization, Experimentation in Data Science, and introduction to algorithmic techniques in Machine Learning.
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This free monthly webinar features Dr. Paul Kolm, Associate Director in the Department of Biostatistics and Biomedical Informatics at the MedStar Health Research Institute.
Feb 25
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