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🤖 AI & Agentic AIBeginner LevelEvidence-Based Skill Profile

Hands-on Mastery in AI Agents

Don't just use AI. Build AI agents that can reason, use tools, remember context, and complete real-world tasks. Master autonomous cognitive architectures, reasoning loops, tool calling schemas, sandboxed execution, memory systems, autonomous DAG planning, agentic RAG, multi-agent supervisor-worker teams, safety guardrails, and OpenTelemetry observability with your dedicated in-course AI Agents Mastery Agent coach.

14 Modules • 7 Production Projects
14 Modules
AI FearFilter Faculty

What You Will Learn

Understand the evolution from static generative models to goal-driven autonomous agents capable of independent action.
Master the canonical 6-part agent architecture: Runtime, Model, Tools, Memory, Planner, and Executor.
Implement robust reasoning patterns including ReAct, Plan-and-Solve, and self-reflective critique loops.
Design strict JSON schema tool calling protocols with parameter sanitization and sandboxed execution.
Architect stateful memory systems spanning working scratchpads, dialogue buffers, and long-term vector stores.
Decompose complex, underspecified engineering goals into verifiable Directed Acyclic Graphs (DAG) of subtasks.
Construct knowledge-grounded RAG agents with dynamic query reformulation and citation verification.
Orchestrate multi-agent hierarchies featuring supervisor-worker patterns, consensus voting, and state machine routing.
Deploy defense-in-depth safety guardrails mitigating prompt injection attacks and unauthorized actions.
Instrument comprehensive OpenTelemetry distributed tracing to monitor trajectories and token costs.
Build 7 production portfolio projects and pass the Module 14 Capstone Challenge evaluated by the AI Agents Mastery Agent.

Curriculum & Weekly Roadmap

14 Structured Modules

Module 1 — Introduction to AI Agents

  • From LLMs to Autonomous Agents: The Evolution of Agency
  • The Spectrum of Autonomy: Assisted vs Semi-Autonomous vs Fully Autonomous
  • Real-World Agent Paradigms & Industry Use Cases

Module 2 — How AI Agents Think: Core Architecture

  • The 6-Part Agent Anatomy: Runtime, Model, Tools, Memory, Planner, Executor
  • State Machines, Environment Perception & Decision Loops
  • Agentic Runtime Execution Engines vs Single Prompt-Response Chains

Module 3 — Reasoning and Decision-Making Loops

  • The ReAct Framework: Thought-Action-Observation Step Trajectories
  • Plan-and-Solve, Reflexion & Self-Reflective Critique Loops
  • Preventing Infinite Decision Loops, Deadlocks & Error Cascades

Module 4 — Tool Calling & Function Execution

  • Function Calling Protocols & Strict JSON Schema Definition
  • Tool Registries, Parameter Sanitization & Type Validation
  • Sandboxed Safe Execution, Subprocess Boundaries & Audit Logging

Module 5 — Memory Systems in AI Agents

  • Short-Term vs Long-Term vs Working Scratchpad Memory
  • Episodic, Semantic, and Procedural Memory Structures
  • Vector-Backed Semantic Memory & Context Budgeting Strategies

Module 6 — Context Windows & Dynamic Context Management

  • Context Window Economics & Token Degradation Patterns
  • Dynamic Context Pruning, Summarization & Sliding Message Buffers
  • Hierarchical Working Memory & Active State Compression

Module 7 — Autonomous Planning & Task Decomposition

  • Decomposing Complex Goals into Directed Acyclic Graphs (DAG)
  • Dynamic Replanning upon Step Failures or Unexpected Observations
  • Hierarchical Task Networks & Priority Queue Execution

Module 8 — Agentic RAG & Knowledge Retrieval

  • Beyond Static RAG: Query Routing, Reformulation & Self-Querying
  • Iterative Retrieval Loops & Corrective RAG (CRAG)
  • Grounded Source Citation, Hallucination Scoring & Answer Synthesis

Module 9 — Multi-Agent Systems & Collaboration

  • Multi-Agent Architectures: Centralized Supervisor vs Decentralized Peer Networks
  • Inter-Agent Communication Protocols, Handoffs & Role Specialization
  • Consensus Mechanisms, Debate Voting & Conflict Resolution

Module 10 — Advanced Frameworks: LangGraph, CrewAI & AutoGen

  • LangGraph: Stateful Graph Workflows, Checkpointing & Cycles
  • CrewAI: Role-Based Agent Crews & Delegated Tasks
  • Architectural Trade-offs: When to Use Frameworks vs Custom Runtimes

Module 11 — Evaluation, Benchmarking & Evals for AI Agents

  • Why Unit Tests Fail for Autonomous Agents: Non-Deterministic Testing
  • Trajectory Evaluation: Assessing Action Sequence Correctness
  • Automated Benchmark Suites, LLM-as-a-Judge & Cost-Accuracy Trade-offs

Module 12 — Observability, Tracing & Production Guardrails

  • OpenTelemetry Tracing: Instrumenting Spans, Thought Traces & Tool Calls
  • Deterministic Safety Guardrails, Input Sanitization & Jailbreak Defense
  • Human-in-the-Loop (HITL) Intervention & Safe Action Escalation

Module 13 — Practical Production Projects (7 Projects)

  • Project 1-3: Tool-Using ReAct Agent, Research Agent, Customer Support
  • Project 4-5: Agentic Knowledge RAG & Data Analysis / Code Generation Agent
  • Project 6-7: Multi-Agent Orchestrator & Task Planning Self-Correction Agent

Module 14 — Final Hands-on AI Agents Capstone Challenge

  • Autonomous Multi-Agent System Architecture & Specifications
  • Implementation: Production Agent with Sandboxed Tools, RAG & Guardrails
  • Submission, Multi-Criteria Evaluation & AI Agents Mastery Agent Verification

Who This Course Is For

Software Engineers, AI Engineers, Backend Developers, Full-Stack Developers, Computer Science Students, and Technical Builders aiming to engineer autonomous, tool-using multi-agent systems for production.

Key Skills Developed:

Autonomous Cognitive ArchitecturesReasoning Loops & Decision MakingTool Calling & Sandboxed ExecutionShort-Term, Long-Term & Working MemoryAutonomous Planning & Task DecompositionAgentic RAG & Knowledge RetrievalMulti-Agent Coordination & LangGraphEvaluation, Benchmarking & EvalsObservability, Tracing & GuardrailsProduction Agent DeploymentAutonomous Production Capstone Challenge

Course Faculty & Development

AI FearFilter Faculty

Autonomous Agents & Systems Engineering Team

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