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DevelopmentIntermediate42 lessons20–25 hours
AI Agents Masterclass
Learn to build, deploy, and manage autonomous AI agents. From simple automation bots to complex multi-agent systems that handle real business tasks.
What You'll Learn
Design agent architectures using tool use, memory, and planning loops
Implement function calling and tool integration with any LLM provider
Build persistent memory systems with vector stores and conversation history
Create planning and reasoning pipelines that break complex tasks into steps
Orchestrate multi-agent systems with delegation and coordination patterns
Deploy agents to production with Docker, cloud functions, and queue systems
Set up monitoring, logging, and observability for autonomous agents
Implement safety guardrails, sandboxing, and human-in-the-loop controls
Outcomes
- Build autonomous agents with tool use, memory, and planning capabilities
- Design and deploy multi-agent systems for real business tasks
- Implement production patterns: error handling, rate limiting, monitoring
- Apply safety guardrails and evaluation frameworks to AI agents
Prerequisites
- -Python or JavaScript fundamentals
- -Basic understanding of AI APIs
Projects You'll Build
- Build a tool-using agent with persistent memory
- Create a multi-agent customer support system
- Deploy an agent with production monitoring
Course Curriculum
Module 1: Agent Fundamentals
- 1.1What makes an AI agent different from a chatbot
- 1.2The agent loop: perceive, reason, plan, act, observe
- 1.3Agent architectures: reactive, deliberative, and hybrid
- 1.4Choosing the right LLM for your agent (cost vs capability)
- 1.5Setting up your agent development environment
- 1.6Building your first agent in 30 minutes
Module 2: Tool Use & Function Calling
- 2.1Why tools are the key to useful agents
- 2.2Defining tool schemas with JSON Schema
- 2.3Implementing tool execution with error handling
- 2.4Building common tools: web search, file I/O, database queries
- 2.5Parallel and sequential tool execution patterns
- 2.6Dynamic tool selection — letting agents choose the right tool
- 2.7Testing and debugging tool integrations
Module 3: Memory & State Management
- 3.1Why agents need memory beyond the context window
- 3.2Short-term memory: sliding windows and summarization
- 3.3Long-term memory with vector databases
- 3.4Episodic memory: learning from past successes and failures
- 3.5Shared state management for multi-session agents
- 3.6Memory retrieval strategies: recency, relevance, importance
- 3.7Implementing memory with Redis, PostgreSQL, and Pinecone
Module 4: Multi-Agent Systems
- 4.1When single agents aren't enough
- 4.2Orchestrator-worker pattern: one agent delegates to many
- 4.3Peer-to-peer agent communication protocols
- 4.4Consensus and voting patterns for agent decisions
- 4.5Shared context and message passing between agents
- 4.6Building a research team: planner, searcher, writer, reviewer
- 4.7Handling conflicts and deadlocks in multi-agent workflows
- 4.8Testing multi-agent coordination end-to-end
Module 5: Deployment & Infrastructure
- 5.1Packaging agents for deployment with Docker
- 5.2Serverless agent deployment on AWS Lambda and Vercel
- 5.3Queue-based architectures for long-running agent tasks
- 5.4Scaling agents: concurrency, rate limits, and cost budgets
- 5.5CI/CD pipelines for agent code and prompt updates
- 5.6Infrastructure as code for agent systems
Module 6: Production Patterns & Safety
- 6.1Input validation and prompt injection defense
- 6.2Output guardrails: content filtering and format validation
- 6.3Sandboxing agent actions: limiting file system and network access
- 6.4Human-in-the-loop: approval workflows for high-risk actions
- 6.5Monitoring agent behavior: anomaly detection and alerting
- 6.6Cost management: token budgets, caching, and model fallbacks
- 6.7Evaluation frameworks: measuring agent accuracy and reliability
- 6.8Incident response: what to do when agents go wrong
AI isn't slowing down.
Neither should you.
Every week you wait, the gap widens. The people who invest in learning AI now will be the ones leading teams, building companies, and staying ahead of the curve. This is your moment — don't let it pass.