LLM Application Development: Build AI Agents and Crypto AI Systems

The era of simple chatbots is evolving into the age of autonomous AI agents that can think, collaborate, and execute actions across the web. If you want to move beyond basic API calls and build intelligent systems that interact with social networks and decentralized protocols, this course is your starting point. Through this text-based guide, you will transition from a curious learner to an AI developer capable of designing, configuring, and deploying multi-agent architectures. You will learn how to set up local environments, orchestrate multiple agents to solve complex tasks, and connect your creations to real-world platforms. What you'll learn: - Understand the foundational architecture of LLM-based autonomous agents and multi-agent systems. - Configure open-source models like DeepSeek, Llama, and Qwen locally using Ollama. - Implement advanced communication patterns using AutoGen and the Model Context Protocol (MCP). - Integrate AI agents with external platforms, including Telegram, social media, and Web3 frameworks like Virtual Protocol. - Apply Retrieval-Augmented Generation (RAG) and Vision-Language Models (VLM) to expand agent capabilities. - Design custom workflows where agents autonomously collaborate, analyze data, and manage simulated crypto tokens. The course starts with essential terminology and the core mechanics of LLM reasoning. You will then progress through step-by-step written guides to configure agent environments, manage memory, and implement multi-agent communication protocols. This course is designed for aspiring AI developers, software engineers, and tech enthusiasts who want to build next-generation applications. No prior experience with AI agents or blockchain is required, though a basic understanding of programming concepts is helpful. Start reading today to build your first autonomous AI agent network.