AI Application Development with the OpenAI API and Function Calling

Moving beyond simple chat interfaces requires a structured approach to API integration and system reliability. This course teaches you how to turn generative AI models into functional components of a modern software stack by focusing on production-ready patterns. You will transition from writing basic prompts to architecting systems that can interact with external tools, validate user inputs, and maintain high standards of safety and performance. What you'll learn: - Learn foundational API concepts and authentication workflows for secure integration. - Implement function calling to allow AI models to interact with external databases and services. - Apply moderation and validation techniques to ensure safe and predictable model outputs. - Understand Retrieval-Augmented Generation (RAG) patterns for grounding responses in specific data. - Practice systematic testing and evaluation strategies to improve application reliability. - Configure observability and monitoring to track model performance in live environments. The curriculum begins with core API definitions and basic request structures before moving into complex logic like tool use and safety layers. You will read through practical implementation scenarios and code-based explanations that mirror real-world development challenges. This course is designed for beginners and developers who are familiar with basic programming and want to build sophisticated AI-driven software. No prior experience with artificial intelligence is required. Start building production-grade AI systems today through structured written lessons.