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AI Agent Development System in Practice: Learn LLM Fundamentals, Master Architecture Design, Implement Enterprise-Grade Agent System Development
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Game Gold-Farming Money-Making Plan: Earn 1k+ Daily, a Stable 3-Year Project Anyone Can Do in Spare Time [Revealed]
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Hot-game fully-automated earning: 500+ a day, no experience, simple operation - the steadiest long-term game-earning side hustle (revealed)
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FlyingMouse earns merit this time! Don't panic at Windows format problems — the open-source FlyingMouse format conversion tool helps, a popular GitHub gem
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Douyin Product-Selling Coaching Bootcamp: No On-Camera Appearance Needed, Newbies Can Produce Selling Short Videos by Following the Steps
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First-release game gold-farming money plan: 1K+ a day, ordinary people in spare time
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FlyingMouse earns merit this time! Don't panic at Windows format problems — the open-source FlyingMouse format conversion tool helps, a popular GitHub gem
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LuDaShi v6.1024.4105.1121 Slim Single File
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2D Cartoon Animation Software Moho Pro v14.3
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Video Editor Aiseesoft Filmai v1.0.18
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To-Do Microsoft To Do v2.147 Free
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PR/AE/DaVinci/FCPX video Plugin Nobe OmniScope Win1.11.15 / Mac1.10.138
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Course Intro:
This AI Agent application development system course fully covers the entire chain from LLM fundamentals to production-grade Agent system development. It teaches LLM underlying principles, tokens, hallucination, and prompt engineering; deeply analyzes Agent architecture, planning, memory systems, tool calling, and RAG retrieval augmentation; explains mainstream frameworks such as LangChain and CrewAI in detail; teaches workflow orchestration and multi-Agent collaboration; covers enterprise-grade system design, high concurrency, performance and cost optimization, Agent quality evaluation, and security risk protection; paired with multi-industry Agent practical cases, it analyzes technical bottlenecks and future directions. Suitable for developers and AI practitioners who want to learn to build production-ready agent systems.
Course Catalog:
1.01_What is an AI Agent and how is it different from traditional AI
10.10_Why does an Agent need memory_
100.06_What is CrewAI; what's its design philosophy
101.07_What core features does OpenAI Assistants API have
102.08_How to pick an Agent framework that fits your project
103.09_Open-source framework vs self-built Agent framework
104.10_How to design an Agent's workflow
105.11_How to choose between DAG and loop flow in Agent workflows
106.12_What's the core challenge of multi-Agent orchestration
107.13_How to build an AgentPipeline
108.14_How to implement Agent Observability
11.11_What is an inference engine_
110.01
Supporting Study Materials
This course comes with a materials pack. Members receive the access link by email after requesting the course.
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