This involves gaining an understanding of the complex dynamics, systems, and stakeholders within the health- care industry. It includes learning about healthcare organizations, regulations, policies, and the various players involved such as hospitals, clinics, insurance companies, pharmaceutical companies, and government agencies.

This module focuses on the use of statistical methods and analytical techniques to extract meaningful insights from healthcare data. It includes topics such as probability theory, hypothesis testing, regression analysis, ma- chine learning, and predictive modeling applied specifically to healthcare datasets.

Here, the emphasis is on learning the best practices for gathering, storing, and managing healthcare data. This GE involves understanding data collection techniques, data governance principles, data quality assurance, and the use of databases or other data management systems commonly employed in healthcare settings.

This module involves learning how to assess the effectiveness and quality of healthcare services and interventions. It covers methodologies for measuring clinical out- comes, patient satisfaction, healthcare costs, and other performance metrics to evaluate the impact of health care initiatives and interventions.

In this component, individuals learn to leverage business intelligence tools and techniques to create insightful visualizations and dashboards from healthcare data. This includes using tools such as Tableau, Power Bl, or Qlik to generate interactive charts, graphs, and reports that communicate complex healthcare information in a clear and intuitive manner.

Finally, the program aims to facilitate a smooth transition for individuals seeking to enter or advance their careers in healthcare analytics or related fields. This may include providing career guidance, networking opportunities, resume building interview preparation, and access to job placement resources to support individuals in achieving their career goals in the healthcare industry.