The “Generative AI for Healthcare Data Analyst & Professionals” course offers a comprehensive, practical exploration of how modern AI systems like LLMs can transform clinical data workflows, documentation, compliance, and decision-making in healthcare environments. Starting with foundational knowledge, learners are introduced to what Generative AI is, the architecture of models like GPT, and how they process structured, unstructured, and multi-modal data—from tabular EHR entries to physician notes and imaging metadata. The course then delves into the practical application of instructional and analytical prompts tailored to medical contexts, emphasizing advanced strategies like zero-shot, one-shot, and few-shot prompting for various use cases, including patient segmentation, SOAP note generation, and readmission forecasting.
Participants will learn how to chain prompts together for end-to-end task automation, from summarizing visit notes to drafting discharge summaries. Tools such as LangChain, LlamaIndex, and Azure OpenAI Studio are introduced to operationalize these capabilities in clinical data pipelines. A strong emphasis is placed on using Generative AI for healthcare reporting and documentation, such as generating HL7/FHIR messages, insurance claims, pre-authorization letters, audit narratives, markdown summaries, PowerPoint presentations, and KPI dashboards. Additional focus areas include synthetic data generation for model training, risk prediction narratives, compliance report generation, and missing value imputation through AI.
- Healthcare Data Analysts seeking to generate summaries, dashboards, and SQL queries from patient records using AI.
- Clinical Informaticists and EHR Specialists who want to streamline SOAP notes, discharge summaries, and referral letters with prompt-based automation.
- Medical Researchers and Biostatisticians interested in synthetic data generation, risk modeling, and pattern discovery.
- AI Engineers and Prompt Designers looking to specialize in healthcare applications using LLMs and RAG systems.
- Hospital IT Teams aiming to build chatbots, integrate FHIR-compatible outputs, and automate compliance reports.
- Healthcare Administrators and Compliance Officers needing tools for documentation, audit support, and policy enforcement via AI.
- Public Health Analysts working on large datasets and population-level risk narratives or forecasts.
- Medical Students and Technologists interested in bridging clinical knowledge with next-generation AI capabilities.
