The professional development courses offered by GET PHIT were developed based on a needs assessment of Texas public health agencies. The professional development courses are online only and self-directed. Although participants will need to register, the education will be offered at no charge for the duration of the grant (until September 2025). Continuing education certificates will be awarded upon the completion of each unit.
Benefits to you:
Main Topics & Course Areas:
Courses Available for Enrollment:
This course will introduce learners to the basics of epidemiology, including methods and research designs. In addition, we will discuss how to obtain large datasets; how to assure that the data are appropriately “matured,” and how data and information systems can be used to understand public health issues in populations.
This course introduces methods in health data science – defining the problem, accessing, and loading the data, formatting into data structures required for analysis. This course covers the basics of computational thinking to define a computational solution, methods to access healthcare data from a variety of sources (EHR data, UMLS, Medline, etc.), and in different data formats. The students will apply methods for data wrangling and data quality assessments to structure the data for analysis. The students will be introduced to basics of design and evaluation of algorithms and application of data structures for healthcare data. The course will use Python programming language and basic python libraries for data sciences such as numpy, scipy, matplotlib and pandas. This course is not an introduction to programming, and not a course to improve programming skills. Students are expected to have some experience with introductory / beginner level Python programming.
This course will introduce learners to the field of health equity and train students to critically understand how the nature of data collection, interpretation and use shape health outcomes. Students will review approaches used to detect and reduce health disparities among various groups of individuals across the global sociodemographic spectrum.
This course will introduce learners to the field of health informatics as applied to the multi-disciplinary study of public health. Concepts from computer science and information science will be used to show how informaticians enrich our understanding of health administration, epidemiology, environmental science, and social and behavioral sciences. Learners will be introduced to the field's history, key terms and concepts, applications of informatics in public health, and common informatics software.
This course aims to establish the foundations of public health analytics to transition data from information to knowledge and actionable wisdom. National data standards, data sources, data management, and approaches to analytics relevant to public health will be covered. This course builds on a foundation of statistics, basic analytics, evidence-based practice, and implementation science.