Advanced Claude Code & AI Agents: Build Apps, Automations and Developer Workflows (Kurs)

ADVANCED CLAUDE CODE & AI AGENTS: BUILD APPS, AUTOMATIONS AND DEVELOPER WORKFLOWS Build Apps, Automations, AI Agents, Developer Workflows, and Freelance Services with Claude Code INTRODUCTION The Advanced Claude Code & AI Agents course is designed for developers, programmers, technical learners, automation builders, freelancers, agency owners, and creators who want to move beyond casual AI use and build professional AI-powered development workflows. This course introduces Claude Code as an agentic coding tool for real developer environments. Instead of using AI only to generate isolated code snippets, learners explore how Claude Code can support repo-level development, codebase analysis, feature planning, debugging, refactoring, testing, documentation, automation, and structured delivery. The course begins with expert setup, mindset, and workspace preparation. Learners work with a terminal, code editor, Git, GitHub, a safe practice repository, and project-level instructions. They learn why professional AI coding requires control, planning, review, and verification rather than blindly accepting AI-generated changes. A major focus is agentic coding. Students learn a practical workflow: Define the task → Inspect the project → Plan the change → Make controlled edits → Test the result → Review the final output This human-in-the-loop approach keeps the learner responsible for direction, quality, security, and correctness. The course also introduces project instruction files such as CLAUDE.md, where project context, coding standards, testing requirements, security rules, documentation expectations, and “do not change” boundaries can be defined. Learners discover how reusable instructions improve consistency and reduce unnecessary errors. Safe terminal use is another important part of the course. Students learn to review commands before running them, understand which files or systems may be affected, use Git as a safety net, create branches, commit before major changes, review diffs, and avoid unprotected work on production projects. Repo-level analysis is taught as a professional first step before editing. Learners practise asking Claude Code to explain project purpose, folder structure, key files, architecture, data flow, APIs, components, configuration, risks, and recommended next steps without immediately changing files. Students also learn how to turn broad ideas into clear developer tasks using goals, user stories, acceptance criteria, constraints, testing requirements, and output expectations. Expert prompt patterns such as plan-first, diff-first, test-first, explain-before-edit, and final-review prompts are introduced to improve safety and quality. The first section concludes with a practical workspace project in which learners prepare a practice repository, create a safe Git branch, write project instructions, perform repo analysis, save a safety checklist, and select a feature for later development. The wider course roadmap also introduces app and feature development, developer automation and GitHub workflows, AI agents, subagents, MCP and SDK workflows, and ways to package these skills into freelance, business, and content-creation services. BENEFITS

1. Build a Professional Claude Code Foundation

Learn how Claude Code fits into real developer workflows instead of treating it as a simple chatbot.

1. Work at Repository Level

Understand how to analyze project structure, key files, dependencies, architecture, APIs, components, and configuration before making changes.

1. Learn Agentic Coding

Use a structured process of understanding, planning, editing, testing, and reviewing rather than relying on one-shot code generation.

1. Improve Development Safety

Use branches, commits, diffs, test repositories, command reviews, and approval checkpoints to reduce risky changes.

1. Create Reusable Project Instructions

Learn how project-level guidance can communicate coding rules, testing expectations, security limits, documentation standards, and project boundaries.

1. Write Stronger Instructions for Coding Agents

Replace vague requests with clear scope, goals, limitations, approval requirements, and expected output formats.

1. Use Expert Prompt Patterns

Apply plan-first, diff-first, test-first, explain-before-edit, and review prompts to keep AI-assisted coding controlled and professional.

1. Turn Ideas into Developer-Ready Tasks

Convert broad ideas into user stories, acceptance criteria, constraints, files to inspect, testing requirements, and clear deliverables.

1. Improve Repo Onboarding and Analysis

Use Claude Code to understand unfamiliar projects, identify risks, locate important files, and create improvement roadmaps.

1. Strengthen Debugging and Review Habits

Ask for root-cause explanations, possible fixes, security checks, edge cases, and missing tests before finalizing changes.

1. Reduce Context Switching

Learn terminal-first workflows that connect AI support more naturally with files, Git, scripts, editors, and developer tools.

1. Prepare for AI Agent Workflows

Build the foundation needed for later work with agents, subagents, automation systems, MCP, and SDK-based workflows.

1. Build Practical Project Experience

Complete a real section project by preparing a reusable AI coding workspace rather than only studying theory.

1. Support Freelance and Business Opportunities

Develop skills that can later be packaged into AI-assisted development, automation, repo analysis, documentation, and workflow services. WHY CHOOSE THIS COURSE? This course is designed for learners who want a more serious and structured approach to AI-assisted software development. It goes beyond asking an AI tool to simply “write code.” Instead, it teaches how to supervise AI inside a professional workflow. You learn to inspect before editing, plan before changing code, define boundaries, review commands, test changes, and verify final results. These habits are especially important when working with repositories, client projects, business systems, or any environment where an incorrect command or uncontrolled edit could create problems. The course also emphasizes human-in-the-loop control. Claude Code can assist with analysis, planning, coding, testing, documentation, and automation, but the developer remains responsible for approving the direction and verifying the result. Another reason to choose this course is its focus on reusable systems. Project instructions, task templates, safety checklists, analysis prompts, and expert coding-agent patterns can be saved and reused across projects. The course is practical. Learners are encouraged to keep a terminal open, prepare a test repository, practise every workflow, save useful instructions and prompts, and build the final project step by step. The course roadmap also connects technical skills with real delivery. Later sections move into app development, automation, AI agents, developer workflows, and freelance or business applications. WHO THIS COURSE IS FOR Developers and Programmers Professionals who want to integrate Claude Code into real coding workflows. Technical Learners and Students Learners who already understand basic technology and want to progress into AI-powered software-development workflows. Automation Builders People who want to create more structured developer automations and agent-based workflows. Freelancers Freelancers who want to use AI to support repo analysis, coding, testing, documentation, automation, and client delivery. Agency Owners Technical service providers who want to understand how AI coding workflows can improve development and delivery. Git and GitHub Users Developers who want safer AI-assisted repository workflows using branches, commits, diffs, and testing. AI Agent Learners People interested in agents, subagents, MCP, SDK workflows, and advanced developer automation. Technical Content Creators Creators working with coding, AI-development, and automation workflows. Advanced AI Users Anyone who wants to move beyond simple AI code generation and learn a controlled, professional, human-reviewed Claude Code workflow. BUY NOW / ENROLL NOW Take the next step from ordinary AI assistance to professional AI-powered development workflows. In this course, you will learn how to prepare a safe Claude Code workspace, work with a terminal and repository, analyze codebases, define project instructions, create developer-ready tasks, apply expert prompt patterns, review commands, use Git as a safety net, and keep human approval at the center of every important change. You will practise with real workflows rather than only watching demonstrations. By completing the section project, you will create a reusable AI coding setup with a practice repository, Git branch, project instructions, repo analysis, safety checklist, and next feature idea. The course also prepares you for later topics including app development, developer automation, GitHub workflows, AI agents, subagents, MCP, SDK workflows, and freelance or business applications. If you already understand basic technology and want to use Claude Code as a serious development partner rather than a casual chatbot, this course provides a structured path forward. Enroll now and start building safer, smarter, more professional AI coding workflows with Claude Code.