Autonomous AI Agents & LLM Tool Orchestration
Build production-ready autonomous agents, ReAct loops, tool execution, memory, and multi-agent systems.
The assessment unlocks once you have worked through the lessons.
Independent provider. Not an accredited awarding body. Not a regulated qualification.
What You Will Master
- Design ReAct (Reason + Act) autonomous decision-making loops
- Implement structured tool declarations and function calling protocols
- Manage episodic, semantic, and working memory for stateful agents
- Build human-in-the-loop approval workflows for critical tool executions
- Orchestrate hierarchical and peer-to-peer Multi-Agent teams
Skills Acquired
Prerequisites
- Familiarity with Prompt Engineering and API requests (Python or TypeScript)
- Basic knowledge of asynchronous execution and JSON data interchange
Curriculum Syllabus
4 modules · 4 lessons · 6 min · one assessment
Module 1: The Core Architecture of AI Agents
Dissect the anatomy of an agent: Planning, Memory, Tools, and the Autonomous Loop.
Module 2: Tool Declaration & Function Calling Protocol
Declaring type-safe tools, handling validation errors, and multi-tool parallel calls.
Module 3: Memory Systems for Stateful Agents
Architecting Working Memory, Episodic Memory, and Semantic Vector Recall.
Module 4: Multi-Agent Systems & Swarms
Hierarchical supervisor models, specialized worker agents, and consensus protocols.
Md. Rajib Hawlader
Principal AI Research Scientist, NeuroLearn AI Labs
Writes and maintains the NeuroLearn AI curriculum.
Ready to Begin Autonomous AI Agents & LLM Tool Orchestration?
Self-paced curriculum with free instant certificate issuance upon passing the evaluation.
Start First Lesson