Claude Code & Agentic AI Training

Claude Code & Agentic AI Training

Claude Code, from setup to production agents- skills, sub-agents, MCP, hooks

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Programm

About the Claude Code & Agentic AI Training

From first install to production-grade AI agents

Our Claude Code training is designed for teams that want to move beyond chat assistants and build real agentic workflows: AI that reads your files, runs your tools, remembers your conventions, and ships verified work.

In practice, participants learn to:

  • install and configure Claude Code on Windows, macOS or a server,
  • structure project memory with CLAUDE.md, MEMORY.md and lessons files,
  • enforce guardrails with permissions and hooks,
  • extend the agent with skills, sub-agents and MCP servers,
  • integrate Git and GitHub for safe, traceable automation.

eaQbe methodology: built on a real production system

This training is not a slideware tour. It is distilled from eaQbe's own production platform: an agentic system that runs daily on a server, orchestrated end-to-end by Claude Code. Every pattern taught in the room (memory, hooks, verification, autonomous loops) has been battle-tested in production.

Our approach follows the same progressive logic as all eaQbe trainings:

  • Understand before you build
  • Use before you implement
  • See the end goal before diving into technical details

Learning path

1) Use Claude Code like a power user

Participants start by driving Claude Code on a real project: sessions, context management, plan mode, slash commands. The goal is to understand what a well-configured agent can do before configuring one.

2) Memory & configuration

The three-file memory pattern (CLAUDE.md, MEMORY.md, lessons), settings and permissions, and the hook system that turns team conventions into enforced rules.

3) Skills, sub-agents & MCP

Write a custom skill, dispatch sub-agents for parallel work, and connect MCP servers (persistent memory, databases, browsers) to give the agent real capabilities.

4) Production patterns

Git integration, headless automation, verification discipline, and a ready-to-copy configuration standard distilled from our production system.

Practical details

  • Format: 1-day intensive workshop (hands-on & scenario-based)
  • Group size: 5–10 participants (small groups for personalized coaching)
  • Prerequisites: none, comfort with a terminal helps
  • Follow-up: evaluation + post-training anchoring exercises

Foundations & first agent

1.1 Agentic AI foundations

From chat assistant to autonomous agent:

  • What Claude Code is and how the agent loop works
  • Where agentic AI fits in a data and automation strategy
  • Platforms: Windows, macOS, server (VPS)
1.2 Install & first configuration

Getting a working, safe setup:

  • Installation and authentication
  • Project memory: CLAUDE.md, MEMORY.md, lessons files
  • First real session on a sample project
1.3 Driving the agent

Working effectively with an agent:

  • Context management and @ mentions
  • Plan mode, thinking mode, slash commands
  • Reviewing and steering the agent's work

Extending & industrializing

2.1 Configuration & guardrails
  • settings.json and the permission model
  • The hook system: session start checks, pre/post tool-use guards, lint on save
2.2 Skills & sub-agents
  • The SKILL.md format and when skills beat prompts
  • Writing a custom skill for a recurring workflow
  • Dispatching sub-agents and parallel work
2.3 MCP & persistent memory
  • Model Context Protocol: connecting databases, browsers and files
  • Persistent memory across sessions
2.4 Git, GitHub & automation
  • Safe commit workflows and traceability
  • Headless mode and scheduled agents
2.5 Production standard
  • Verification discipline: never claim done without proof
  • A ready-to-copy project template, governance and cost control

Build capability, not dependency

Richard Feynman nailed it: “If you can’t explain it simply, you don’t understand it well enough.”

That’s eaQbe’s DNA. We don’t just train your team on data  tools. We build experts who can explain, apply, and amplify what they’ve learned.

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What makes eaQbe's trainings right for your team ?

Scenario-based learning

Our training bridges the gap between concepts and reality. We immerse participants in realistic business scenarios, ensuring skills are directly applicable to your specific challenges.

Trainings led by experts

Our trainers are data science specialists with solid teaching experience. They make complex topics accessible through a clear, structured approach focused on practical application

Progressive autonomy & mastery

Each participant is guided step by step in their learning journey: from theory and demonstrations to guided exercises, leading to full autonomy.