LLM Developer: Building Applications with Large Language Models

Artificial intelligence is transforming how we build software, making skills in large language models (LLMs) highly sought after by modern development teams. This text-based course provides a structured pathway to understanding and building applications powered by LLMs. You will transition from a curious programmer to an application builder capable of leveraging LLM APIs. You will understand the foundational architecture of transformer models and learn how to programmatically interact with them to solve real-world problems, build smart agents, and handle unstructured data. What you'll learn: - Understand the foundational concepts of generative AI, transformer architectures, and text processing. - Apply prompt engineering techniques programmatically to control model outputs and behaviors. - Configure Retrieval-Augmented Generation (RAG) pipelines to connect LLMs with custom external data. - Integrate vector databases to store and search semantic embeddings efficiently. - Implement modern LLM orchestration patterns to chain prompts and manage conversation context. - Evaluate model performance and implement basic observability to monitor application outputs. The course begins with essential AI terminology and foundational concepts before moving into hands-on integration. Through comprehensive written explanations and practical code examples, you will explore API communication, data ingestion, and modern application design patterns. This course is designed for software developers, technical product managers, and technology enthusiasts who want to learn LLM development. No prior machine learning or data science background is required, though basic programming familiarity is helpful. Start your journey into LLM application development today.