LLM Tool Use and Function Calling in Python

Transforming unstructured language model outputs into dependable software components requires disciplined engineering and structured tool execution. This text-based course guides you through connecting models to Python functions, external services, and data pipelines with predictability and precision. What you'll learn: Understand foundational concepts behind tool calling, function schemas, and model context management. Define strict data contracts and structured outputs using modern Python type hints and schema validation. Build resilient multi-step execution loops equipped with error recovery and retry logic. Implement modular architectures using the Model Context Protocol for reusable tool integration. Practice handling unpredictable model outputs and edge cases with clean error handling strategies. The course begins with core definitions and terminology before guiding you through structured code examples and clean implementation patterns. Perfect for beginners and Python developers looking to build dependable, tool-enabled AI systems from scratch. Start reading to turn language models into practical, functional software.