Foundations of LLMs and AI Agents: Design Intelligent Workflows

Large Language Models (LLMs) are transforming how we interact with technology, but the real power lies in building autonomous AI agents that can plan, use tools, and solve complex problems. This text-based course guides you through the foundational concepts of LLMs and agentic workflows without requiring prior AI experience.\n\nYou will transition from understanding basic prompts to designing structured AI agents capable of executing multi-step tasks. By reading through conceptual breakdowns and practical text examples, you will gain the confidence to implement modern AI architectures in your own projects.\n\nWhat you'll learn:\n- Understand the core architecture of Large Language Models and how they process information\n- Master foundational prompt engineering techniques to guide model behavior effectively\n- Implement Retrieval-Augmented Generation (RAG) to connect LLMs with external data sources\n- Design autonomous AI agents that utilize planning, memory, and tool-calling capabilities\n- Explore modern agent frameworks and orchestration patterns for multi-agent systems\n- Address ethical considerations, safety guardrails, and cost management in AI deployment\n\nThe curriculum starts with essential terminology and the mechanics of language models before progressing to vector databases, RAG, and agent architectures. You will explore structured text-based walkthroughs that illustrate how agents think, plan, and execute tasks.\n\nThis course is designed for curious beginners, software developers, and product managers who want to understand the mechanics of modern AI. No prior background in machine learning or advanced programming is required.\n\nStart reading today to unlock the potential of autonomous AI agents and modern language models.