What you'll learn
Build AI-powered clinical assistants using GPT models.
Analyze breast cancer reports with AI precision.
Classify genomic mutations using machine learning.
Integrate LLMs into medical diagnostic systems.
Automate clinical workflows with GPT-based agents.
Design healthcare chatbots for genetic counseling.
Use NLP to interpret clinical and lab reports.
Apply AI for breast cancer detection insights.
Develop genomic data processing pipelines.
Build interactive GPT tools for clinicians.
Learn fine-tuning and prompt engineering for LLMs.
Implement medical AI ethics and data privacy.
Visualize genomic data for patient analysis.
Integrate AI tools with EHR and hospital systems.
Use Python and AI libraries for healthcare projects.
Understand clinical report structures and datasets.
Deploy healthcare GPT apps using open-source tools.
Build end-to-end AI pipelines for medical use cases.
Learn real-world healthcare AI implementation steps.
Master GPT and LLMs for clinical and genomic AI solutions.

Requirements
Basic understanding of Python programming.
Familiarity with AI or machine learning fundamentals.
Interest in healthcare, genomics, or clinical data.
Curiosity to explore GPT and large language models.
No medical background required, concepts explained simply.
Willingness to learn coding through hands-on projects.
Enthusiasm to build real-world healthcare AI tools.