Generative AI Foundations in Python

Generative AI is transforming how we build software, but understanding the core mechanics behind large language models is key to leveraging their true potential. This text-based course guides you through the foundational concepts of generative AI using Python, demystifying how these powerful systems work. You will transition from a curious developer to a practitioner capable of conceptualizing, designing, and implementing basic generative AI workflows. You will learn to work with modern APIs, structure effective prompts, and understand how to ground model responses with external data. What you'll learn: 1. Understand core generative AI terminology, neural network concepts, and how transformer models process text. 2. Set up a modern Python development environment using virtual environments and secure API key management. 3. Implement programmatic API calls to interact with large language models and handle structured outputs. 4. Apply foundational prompt engineering techniques directly in your Python scripts to guide model behavior. 5. Explore the retrieval-augmented generation (RAG) pattern and how vector databases store and retrieve semantic information. 6. Practice building a basic text-generation application that combines user input with context retrieval. The course begins with essential definitions and the theoretical intuition behind language models, then moves into hands-on Python implementation, API integration, and modern architectural patterns. Through clear written explanations and step-by-step code walkthroughs, you will build your understanding from the ground up. This course is designed for beginner developers, data enthusiasts, and software engineers who are new to artificial intelligence and want a clear, conceptual, and practical introduction using Python. No prior AI or machine learning experience is required, though basic Python familiarity is helpful. Start reading today to unlock the fundamentals of generative AI and begin building your own intelligent text applications.