Trainings/ Agentic AI with Claude
Course – AI & Agentic AI Engineering

Agentic AI with Claude — Building Autonomous Workflows & AI Agents

2 Days / 14 Hrs Advanced Classroom / Live Virtual
Duration
2 Days / 14 hrs
Level
Advanced
Format
Classroom / Live Virtual
Domain
AI · Agentic AI
Training Methodology

Learning by Doing

Every session in this program is built around hands-on execution, not passive slides — you leave having built something, not just watched a demo.

01

Explore

Hands-on labs from Day 1 — real or sandboxed environments, not slide decks.

02

Experiment

Work against scenarios that mirror your actual stack.

03

Engage

Solve real business problems in every session, not toy examples.

04

Apply

Capstone exercises tied to your team’s actual workflows.

Who This Is For

Developers & Architects Technical Teams Exploring Agentic AI AI/ML Practitioners

What You’ll Be Able to Do

  • A working mental model for agent architecture (plan, act, observe, correct)
  • Hands-on experience building tool-using agents
  • Practical use of MCP for connecting agents to real systems
  • Techniques for evaluating and guardrailing agent behavior

Prerequisites

  • Programming experience (Python or JavaScript preferred)
  • Basic familiarity with the Anthropic API or similar LLM APIs

Curriculum

Module 1
What Makes an Agent
  • Agents vs chatbots vs simple automations
  • The plan-act-observe loop
  • When to use an agent (and when not to)
Module 2
Tool Use & Function Calling
  • Designing tools an agent can call
  • Structured outputs and error handling
  • Chaining multiple tool calls
Module 3
MCP for Agent Integrations
  • MCP architecture recap
  • Connecting agents to internal tools and data sources
  • Building and testing a custom MCP server
Module 4
Multi-Step & Multi-Agent Workflows
  • Breaking a task into sub-agents
  • Coordinating and handing off between agents
  • Long-running and asynchronous workflows
Module 5
Guardrails, Evaluation & Safety
  • Confirmation steps for high-risk actions
  • Evaluating agent output quality
  • Handling failures and unexpected inputs
Module 6
Capstone — Build Your Own Agent
  • Participants design and build a working agent for a real business scenario

Delivery Details

  • Delivered as classroom or live virtual instructor-led — scheduled around your team
  • Labs are illustrative and may vary by trainer approach, participant profile, and Claude/Anthropic API access
  • Hands-on labs throughout — not slide-only theory

Request This Program

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