Generative AI Foundations: Prompting, RAG, and Application Design

Generative artificial intelligence is reshaping how we build software, analyze data, and automate workflows, yet getting started can feel overwhelming. This text-based course simplifies the landscape, guiding you from foundational AI concepts to practical implementation strategies. You will transition from a curious beginner to a confident practitioner capable of designing prompts, understanding model architectures, and planning AI-driven applications. What you'll learn: 1. Understand the core mechanics of large language models and generative architectures. 2. Practice advanced prompt engineering techniques to elicit precise, high-quality outputs. 3. Explore modern integration patterns like Retrieval-Augmented Generation (RAG) and vector databases. 4. Evaluate AI safety, ethical considerations, and bias mitigation strategies. 5. Design workflows that connect generative models with external data sources and APIs. The curriculum begins with essential terminology and the mechanics of language models before moving into structured prompting techniques and modern system architectures. You will read through clear explanations, conceptual breakdowns, and practical text-based exercises designed to reinforce your understanding. This course is designed for absolute beginners, developers, and tech enthusiasts who want a solid conceptual and practical grounding in generative AI without needing prior machine learning experience. Begin your journey into the world of generative AI and start building smarter applications today.