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Claude Code in Action

Description

This course teaches developers how to work with Claude Code as a coding agent. How to use it to build features, write tests, refactor code, automate pipelines, and collaborate as a team. The course is specifically designed to allow participants learn how to leverage an AI coding agent effectively working with with the most popular technology stacks.

Indicative Duration: 16 training hours
*Duration is adjusted based on the final scope and the target audience.

Scope

Module 1. Orientation & first delegation Foundation
  • Agent model vs. autocomplete
  • CLI install, authentication
  • Scaffold sample project from scratch
  • Reviewing and verifying output
Module 2. CLAUDE.md at every level Context control
  • Why context resets and how to prevent it
  • Global, project and sub-folder files
  • Author all three for sample project
  • Test how each changes behaviour
Module 3. Prompting patterns
and slash commands Context control
  • Explore, plan, implement, review
  • /init, /memory, /compact, /clear
  • Custom project slash commands
  • Common failure modes
Module 4. Building features
with multi-file generation
Building
  • Scoping a feature prompt effectively
  • Multi-file generation in practice
  • Output review checklist
  • Build assignment, deadlines and notifications
Module 5. Testing and
refactoring Building
  • Coverage gap analysis
  • Impact analysis before a change
  • Propose, review, approve cycle
  • Refactor the task repository layer
Module 6. Debugging Claude Code failures Debugging
  • Hallucination patterns and how to spot them
  • Trust calibration framework
  • Diagnose and fix broken sample project code
  • Steering a stuck agent
Module 7. CI/CD, automation
and team workflows Automation
  • GitHub Action setup and permissions
  • @claude in PRs: review, fix, explain
  • SDK for headless automation
  • Shared CLAUDE.md as a team contract
Capstone: full feature from zero
Capstone
  • Participants write the spec and drive Claude
  • Live debugging and course-correction
  • Course retrospective

Learning Objectives

Upon completion of the course participants will be able to:

  1. Use Claude Code as a primary development tool, delegating tasks by intent
  2. Configure Claude Code for any project using CLAUDE.md so the agent respects team conventions automatically
  3. Apply proven prompt patterns to get consistent, production-quality output from the agent
  4. Generate complete feature slices from a single high-level prompt
  5. Use Claude Code to explore and understand unfamiliar codebases quickly
  6. Generate meaningful test suites and close coverage gaps through agent dialogue
  7. Identify and correct hallucinations and errors in AI-generated Java code
  8. Design lightweight team workflows and shared conventions for AI-assisted development

Target Audience

  • Roles: Backend Developer, Engineering Manager, Full-Stack Developer, Software Architect, Software Developer, Technical Lead, Test Engineer, Data Engineer, Quality Assurance Engineer
  • Seniority: Mid-Level to Senior Professionals

Prerequisite Knowledge

  • Comfortable writing code in any modern technology stack, ideally having hands-on experience
  • Basic Git workflow (commit, branch, pull request)
  • No prior experience with AI coding tools or prompt engineering required

Delivery Method

Sessions can be delivered via the following formats:

  • Live Online – Interactive virtual sessions via video conferencing
  • On-Site – At your organization’s premises
  • In-Person – At Code.Hub’s training center
  • Hybrid – A combination of online and in-person sessions
Tags:

Date

On Demand

Labels

AI-Native
Category

Organizer

Code.Hub
Email
[email protected]

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