Build practical Generative AI and Large Language Model applications using Python, RAG, AI agents, fine-tuning, multimodal AI, and production deployment.
Develop the skills to take LLM applications from prompt design and prototypes to reliable, secure, production-ready AI solutions.
This hands-on Specialization guides you through the complete LLM application development lifecycle. Start by integrating LLM APIs with Python, applying zero-shot and few-shot prompting, generating structured outputs, and building practical AI applications.
Progress to Retrieval-Augmented Generation using embeddings, semantic search, FAISS, and ChromaDB to build document-aware AI systems. Learn to fine-tune LLMs, prepare training datasets, develop AI agents that automatically select tools, and build multimodal applications using text and images.
Finally, evaluate LLM quality, optimize token usage and caching, strengthen applications against prompt injection, and deploy an end-to-end LLM solution to the cloud.
By completing the Specialization, you'll have practical experience designing, building, evaluating, optimizing, securing, and deploying modern Generative AI applications.
Applied Learning Project
Apply Generative AI and LLM development skills through hands-on projects, including an AI-powered Resume Analyzer, a document-aware RAG system, fine-tuned language models, tool-using AI agents, and a multimodal image captioning application. In the final capstone project, design, evaluate, secure, optimize, and deploy a production-ready LLM application to solve a practical business problem.
