AI Full Stack Engineering (School of AI) — ML/Deep Learning/NLP/CV/Generative AI certificate training
Completed structured AI training covering machine learning, deep learning, NLP, computer vision, and generative AI concepts used to support downstream data annotation and labeling workflows. Built and iterated end-to-end AI applications in healthcare, including prediction modeling and retrieval-augmented generation (RAG) systems that require preparing and validating training/evaluation datasets. Applied explainability techniques to assess model behavior for real-world adoption readiness. • Trained and evaluated healthcare-related ML pipelines using tabular patient data. • Implemented healthcare prediction systems and RAG-powered applications for clinical document Q&A. • Focused on dataset preparation and model validation concepts typical of annotation-to-model lifecycles. • Used explainability (e.g., SHAP) for assessment and evaluation of model outputs.