{"id":26563639,"url":"https://github.com/panaversity/learn-agentic-ai","last_synced_at":"2025-05-14T18:05:55.087Z","repository":{"id":244004487,"uuid":"814028199","full_name":"panaversity/learn-agentic-ai","owner":"panaversity","description":"Learn Agentic AI using Dapr Agentic Cloud Ascent (DACA) Design Pattern and Agent-Native Cloud Technologies: OpenAI Agents SDK, Memory, MCP, A2A, Knowledge Graphs, Dapr, Rancher Desktop, and Kubernetes.","archived":false,"fork":false,"pushed_at":"2025-05-13T12:25:12.000Z","size":140670,"stargazers_count":2088,"open_issues_count":16,"forks_count":491,"subscribers_count":106,"default_branch":"main","last_synced_at":"2025-05-13T13:43:30.193Z","etag":null,"topics":["a2a","agentic-ai","dapr","dapr-pub-sub","dapr-service-invocation","dapr-sidecar","dapr-workflow","docker","kafka","kubernetes","langmem","mcp","openai","openai-agents-sdk","openai-api","postgresql-database","rabbitmq","rancher-desktop","redis","serverless-containers"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/panaversity.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2024-06-12T07:50:04.000Z","updated_at":"2025-05-13T13:41:40.000Z","dependencies_parsed_at":"2024-08-26T16:53:53.998Z","dependency_job_id":"d30cb6d3-a0bc-4b9f-be4c-e5296234de60","html_url":"https://github.com/panaversity/learn-agentic-ai","commit_stats":null,"previous_names":["panaversity/learn-prompt-eng-gpts-ai-agents","panaversity/learn-generative-ai-fundamentals","panaversity/learn-agentic-ai-fundamentals","panaversity/learn-agentic-ai-engineering"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/panaversity%2Flearn-agentic-ai","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/panaversity%2Flearn-agentic-ai/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/panaversity%2Flearn-agentic-ai/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/panaversity%2Flearn-agentic-ai/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/panaversity","download_url":"https://codeload.github.com/panaversity/learn-agentic-ai/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254198514,"owners_count":22030965,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["a2a","agentic-ai","dapr","dapr-pub-sub","dapr-service-invocation","dapr-sidecar","dapr-workflow","docker","kafka","kubernetes","langmem","mcp","openai","openai-agents-sdk","openai-api","postgresql-database","rabbitmq","rancher-desktop","redis","serverless-containers"],"created_at":"2025-03-22T16:01:47.746Z","updated_at":"2025-05-14T18:05:50.068Z","avatar_url":"https://github.com/panaversity.png","language":"Jupyter Notebook","funding_links":[],"categories":["📚 Projects (1974 total)","Openai","A01_文本生成_文本对话","Repos","Jupyter Notebook","MCP Resources \u0026 Educational Materials","🤖 AI \u0026 Machine Learning","Tutorials \u0026 Learning Resources"],"sub_categories":["MCP Servers","大语言对话模型及数据","Gateways"],"readme":"# Learn Agentic AI\n\nThis repo is part of the [Panaversity Certified Agentic \u0026 Robotic AI Engineer](https://docs.google.com/document/d/15usu1hkrrRLRjcq_3nCTT-0ljEcgiC44iSdvdqrCprk/edit?usp=sharing) program. It covers AI-201 and AI-202 courses.\n\n![Agentic AI Top Trend](toptrend.webp)\n\n## Watch The NVIDIA CEO Jensen Huang Keynote at CES 2025\n\n[![HR for Agents](hr.jpeg)](https://www.youtube.com/watch?v=k82RwXqZHY8 \"NVIDIA CEO Jensen Huang Keynote at CES 2025\")\n\n\nReference:\n\nhttps://www.linkedin.com/posts/alexwang2911_aiagents-robotics-technology-activity-7282829390445453314-QLeS\n\n**[OpenAI Agents SDK vs LangGraph vs Autogen vs CrewAI](https://composio.dev/blog/openai-agents-sdk-vs-langgraph-vs-autogen-vs-crewai/)**\n\nThe following chart clearly identifies why we are using OpenAI Agents SDK as our main framework for Agentic development:\n\n![comparision](./comparison.png)\n\n[Abstraction and Power in AI Agent Frameworks: A Comparative Analysis of OpenAI Agents SDK, CrewAI, AutoGen, and LangGraph](https://g.co/gemini/share/e73d75492cf4)\n\nAlso listen to this discussion: \n\n[Listen: AI Agent Frameworks: OpenAI, CrewAI, AutoGen \u0026 LangGraph - Decoding the Power](https://g.co/gemini/share/5e4123e6bfeb)\n\n\n### AI-201: Fundamentals of Agentic AI  -  From Foundations to Autonomous Agents\n\nAI 201 Fundamentals of Agentic AI we cover chapters: 00-06\n\nKickstart your journey into Agentic AI! This course provides a rapid yet comprehensive introduction to Conversational, Generative, and Agentic AI.  You'll master the foundational concepts using **OpenAI Agents SDK**, then immediately build practical Conversational AI applications to understand human-AI interaction firsthand.  The focus quickly shifts to Agentic Design Patterns, which you'll implement using OpenAI Agents SDK to create truly autonomous AI agents.  You'll become proficient with OpenAI Agents SDK, developing agents ready for real-world tasks.  Furthermore, you'll gain the unique skills to construct Model Context Protocol (MCP) servers and agents, enabling you to build next-generation augmented LLMs. Finally, we'll explore the groundbreaking potential of Agentic Payments, envisioning the future of AI in finance.\n\n\n**[AI-201 Video Playlist](https://www.youtube.com/playlist?list=PL0vKVrkG4hWovpr0FX6Gs-06hfsPDEUe6)**\n\nNote: These videos are for additional learning, and do not cover all the material taught in the onsite classes.\n\n\n\n### AI-202: Advanced Agentic AI Engineering - Master Enterprise-Scale AI Agent Development\n\nAI 202 Advanced Agentic AI we cover chapters: 06, 7a, 8, 8a, 9, 9a, 10, 10a, 11, and 12\n\nReady to engineer truly sophisticated AI agent systems?  AI-202 builds upon your AI-201 foundation to propel you into advanced Agentic AI engineering.  You'll master powerful frameworks like Microsoft AutoGen to construct complex agents for intricate tasks and advanced decision-making.  Focusing on Agent-to-Agent communication and orchestration, you'll develop enterprise-ready multi-agent solutions.  You'll build robust Model Context Protocol (MCP) servers, and then craft dynamic, user-centric agentic frontends with Next.js and TypeScript.  The course culminates in a professional project where you'll design and deploy a complete enterprise-grade agentic solution, showcasing your mastery of cutting-edge AI technologies and your readiness for the forefront of the field.\n\n\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpanaversity%2Flearn-agentic-ai","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpanaversity%2Flearn-agentic-ai","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpanaversity%2Flearn-agentic-ai/lists"}