Development Multi Agent And Ai Agent In Crypto
Published 7/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 4h 4m | Size: 241 MB
AI Agent and Crypto
What you'll learn
Create a crypto token for an AI agent in Virtuals Protocol.
Run DeepSeek, Qwen, and Llama models locally.
Create a Multi Agent based on the G.A.M.E. framework from Virtuals Protocol.
Build Multi-Agent systems with RAG for freelance projects.
Develop an X-bot for analysing tweets and posting tweets with LLM based on the G.A.M.E. framework from Virtuals Protocol.
Create a Telegram bot for analysing graphs with VLM based on the AutoGen framework.
Build AI systems from freelance projects based on the AutoGen framework.
Create a knowledge base using Qdrant to implement RAG architecture.
Requirements
No programming skills required, you will learn everything you need to know.
Need to be in a good mood
Need enthusiasm, engagement, and active participation in comments and reviews
Description
Dive into LLM app development Create tokens for Crypto AI Agent.Master tools: Virtual Protocol, GAME, AutoGen, Ollama, MCP Work with DeepSeek, Llama, Qwen models Build AI Agents, Multi-Agent, RAG, VLM, and integrate with Virtual Protocol, Telegram and X.Practice-focused, innovate from automation to analyticsA friendly international community with support for any questions. Be sure to join this community.Course ObjectivesEquip you with the skills to build innovative applications using LLMs, leveraging tools like AutoGen, GAME, Virtual Protocol, MCP, Ollama, and models such as DeepSeek, Llama, Qwen, plus AI Agent, Multi-Agent, VLM, and RAG. You'll master the development of intelligent agents and learn to apply various integrations. Why Choose This Course?Helps you create relevant Pet Projects (AI Agents / RAG). Strong focus on practical application. Covers the full journey-from core concepts to advanced solutions. Modular structure suitable for all skill levels. Built on best practices for effective learning. Taught by a practitioner with experience in major projects and a teaching background. Memes SupportWhat You'll Gain After Completing the Course Pet Projects with AI in your portfolio. Skills in working with AutoGen, RAG, VLM, and LLM optimization. Ability to design multi-agent systems. Expertise in data integration Experience building AI-driven applications. Course HighlightsPrepares you for the latest industry challenges. Goes beyond basic courses with cutting-edge IT knowledge. Real-world examples from practice. Challenges, metaphors, and humor for engaging learning. What You'll Be DoingStudying theory paired with hands-on tasks. Analyzing real-world scenarios. Exploring programmatic implementations of AI Agents and applying your knowledge. Course Topics and Tasks Building Telegram Bots and bots for X Creating a portfolio with AI-driven projects. Fundamentals of Multi-Agent Systems and RAG. Optimizing and fine-tuning LLMs. Working with VLM. Integrating with modern solutions. And much more!Who This Course Is For
evelopersYou build apps and integrate AI, but struggle with quickly implementing AI agents and Multi-Agent systems. Learn to use AutoGen, GAME, Virtual Protocol, MCP, and Ollama for innovative solutions.Situation: "I need to speed up chatbot creation, but traditional approaches slow me down."ML EngineersYou work with DeepSeek, Llama, Qwen models but want to enhance RAG and VLM for complex tasks. This course optimizes data and integrates with AI agents.Situation: "My models need more context, but data processing takes hours."Career UpgradesYou want to refresh your skills and master modern AI tools. The course covers Multi-Agent, RAG, and LLM tuning, preparing you for 2025 industry challenges.Situation: "My current skills are outdated; I need to learn 2025 trends."Trend ExplorersYou follow tech advancements and want to dive into cutting-edge AI Agent and VLM approaches. Gain practical skills with the latest frameworks.Situation: "I want to understand how Multi-Agent systems are reshaping the market, but don't know where to start."Crypto AI Agent SpecialistsYou work in blockchain and aim to automate trading or market analysis with AI. Learn to build predictive agents.Situation: "I need to forecast Bitcoin trends, but current tools lack accuracy."What You'll Gain:In-demand skills for LLM tasks (AI Agents/RAG).Knowledge employers seek in AI.Hands-on practice with theory.Diverse examples-from basic to advanced-for your portfolio.Access to a community forum for solutions and discussions.
Who this course is for
A course for Python developers who want to create a smart agent with LLM, a browser, custom tools, and AutoGen.
For AI enthusiasts who want to use MCP, Ollama, and AutoGen to create interactive and flexible assistants.
For AI enthusiasts who want to use large language models on their own hardware or in closed systems. Local launch (self-host / on-premises) DeepSeek / Qwen / Llama.
Suitable for developers familiar with Python who want to learn how to integrate LLM and tools into a single agent.
A course for those who want to dive deeper into AutoGen and build their own agent with web search and code execution capabilities.
Ideal for developers learning DeepSeek / Qwen / Llama and AutoGen and wanting to build a next-generation agent.
A course for professionals interested in creating LLM agents that can combine web tools and custom functions.
For advanced users interested in using local LLMs, such as LLaMA, in conjunction with external APIs.
Suitable for Python developers who want to implement custom functions and web tools in their AI assistants.
The course will be useful for developers who are already familiar with the basics of LLM and want to build an agent with complex behaviour.
For engineers interested in AutoGen, async architecture, and the practical implementation of agents with MCP tools.
Development Multi Agent And Ai Agent In Crypto
