Course
Generative AI Training
Learn to build modern AI applications with large language models, prompt engineering, RAG, AI agents, and multimodal models.
Who this is for
Designed for learners with machine learning or deep learning fundamentals who want to build practical Generative AI applications. Suitable for AI engineers, data scientists, software developers, automation engineers, and professionals looking to integrate large language models into real-world products and business workflows.
Generative AI is transforming how software is built, how people work with information, and how businesses automate complex tasks. This course focuses on developing practical skills for building AI-powered applications using modern large language models and the surrounding ecosystem. You will learn how foundation models work, master prompt engineering techniques, build Retrieval-Augmented Generation (RAG) systems, create AI agents, work with vector databases, multimodal models, and model APIs, and understand when fine-tuning is appropriate. Throughout the course you will build real-world projects that combine LLMs with external tools, documents, APIs, and business workflows while learning current best practices for evaluation, safety, and deployment.
What you'll learn
Foundation models, Transformers, and Large Language Models (LLMs).
Prompt Engineering
prompting strategies, chain-of-thought concepts, structured prompting, and evaluation.
Embeddings, vector databases, semantic search, and Retrieval-Augmented Generation (RAG).
AI agents, tool calling, Model Context Protocol (MCP), and workflow automation.
Multimodal AI
text, images, audio, and vision-language models.
Fine-tuning fundamentals, parameter-efficient tuning (LoRA), and model customization.
LLM evaluation, safety, guardrails, hallucination mitigation, and responsible AI.
End-to-end Generative AI project integrating LLMs with external APIs and business data.
10 weeks
