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Claude Code Beginner Crash Course: Claude Code In a Day

This course is designed for developers, AI engineers, and data scientists who want to go beyond basic AI chat usage and build real, production-ready AI coding systems using Claude Code. With my experience in software engineering and AI-assisted development, I guide students step-by-step through real-world workflows, focusing on practical problem-solving: debugging AI-generated code, structuring multi-agent systems, and optimizing context for better performance. You will not just learn theory — you will build systems. From setting up Claude Code in your development environment to creating advanced agent workflows using MCP, sub-agents, and hooks, this course teaches you how to transform your development process with AI. By the end of the course, you will be able to design intelligent, automated, and context-aware coding systems that significantly improve productivity and code quality.

1명 이 수강하고 있어요.

난이도 초급

수강기한 무제한

  • snowflake
claudecode
claudecode
multi-agentsystems
multi-agentsystems
aiautomation
aiautomation
contextengineering
contextengineering
mcp
mcp
claudecode
claudecode
multi-agentsystems
multi-agentsystems
aiautomation
aiautomation
contextengineering
contextengineering
mcp
mcp

수강 후 이런걸 얻을 수 있어요

  • Build and manage AI-powered coding workflows using Claude Code (commands, memory, hooks)

  • Design and orchestrate multi-agent systems using sub-agents and MCP architecture

  • Apply advanced context engineering techniques to improve AI performance and accuracy

  • Automate development tasks (debugging, refactoring, testing) with AI agents

  • Integrate Claude Code with tools like GitHub, IDEs (Cursor), and local environments

Claude Code Mastery: Build AI Agents & Multi-Agent Coding Systems

👉 Learn how to design intelligent AI development workflows used in:

  • Software Engineering

  • AI Engineering

  • Automation Systems

  • Modern DevOps & AI-powered coding

This course takes you from simple AI usage to building real multi-agent systems that automate coding, debugging, and development workflows.

💡 Why this course?
As a developer working with AI tools, I noticed that most engineers struggle with inconsistent results, poor prompts, and lack of structure. This course was created to solve that — by teaching system-level AI usage, not just prompting

What You’ll Learn

Section (1): Core Keywords — Context Engineering & Claude Code Foundations

In this section, you will master the foundation of AI-powered development systems:

  • Understand Context Engineering (the most important skill in AI coding)

  • Control AI behavior using Slash Commands

  • Build persistent AI memory using .md systems

  • Optimize AI performance with:

    • /clear

    • /compact

    • structured prompts

  • Learn how Claude Code works internally (architecture & workflow)

✅ Outcome:
You will be able to control AI like a system, not just chat with it

Section (2): Core Keywords — Multi-Agent Systems, MCP & Automation

This section focuses on advanced, real-world AI systems:

  • Build multi-agent systems using Subagents

  • Understand and use MCP (Model Context Protocol)

  • Automate workflows with:

    • Hooks

    • GitHub integration

    • IDE (Cursor) integration

  • Create specialized AI agents for:

    • Debugging

    • Code review

    • Security analysis

  • Design scalable AI architectures

✅ Outcome:
You will be able to build autonomous AI coding systems that work like a team

Before You Enroll

Practice Environment

💻 Operating System

  • Windows / macOS / Linux (Ubuntu recommended for advanced users)

🛠 Required Tools

  • Node.js (latest LTS version)

  • Cursor IDE (or VS Code with extensions)

  • Claude Code (Anthropic API or Claude Pro plan)

  • Git & GitHub

  • Terminal / CLI usage

⚠️ No virtual machine required, but basic CLI knowledge is important.


⚙️ Recommended PC Specs

  • CPU: Intel i5 / Ryzen 5 or higher

  • RAM: 8GB minimum (16GB recommended)

  • Storage: 10GB+ free space

  • GPU: Not required

Prerequisites & Notices

📚 Required Knowledge

  • Basic to intermediate software development experience

  • Familiarity with:

    • JavaScript (Node.js) or Python

    • APIs / Generative AI basics

  • Understanding of coding workflows (Git, debugging)

이런 분들께
추천드려요

학습 대상은
누구일까요?

  • Developers struggling with inefficient AI usage (copy-paste prompts, inconsistent results) and wanting a structured, scalable workflow

  • AI engineers and data scientists who want to build real agent systems instead of simple chat-based tools

  • Software engineers who want to automate repetitive coding tasks and improve productivity

  • Advanced GenAI users who want to move into agentic systems and multi-agent architectures

선수 지식,
필요할까요?

  • Basic to intermediate experience in software engineering

  • Familiarity with JavaScript/Node.js or Python

  • Understanding of Generative AI concepts (LLMs, prompts, APIs)

  • Experience using a code editor (VS Code, Cursor, etc.)

안녕하세요
입니다.

Snowflake AI Data Cloud 분야의 세계적인 전문가로, 데이터 엔지니어링, 클라우드 플랫폼 및 현대적인 분석 시스템 분야에서 광범위한 경험을 보유하고 있습니다.

전직 Snowflake “Data Superhero”이자 SnowPro 자격증 내용 전문가(SME)로, 8개의 SnowPro 자격증을 보유하고 있으며 모두 첫 시도에 합격했습니다.

지난 몇 년 동안 저는 AWS, Azure, GCP, 데이터 과학 및 머신러닝을 포함한 주요 기술 분야에서 40개 이상의 감독관 관리 인증 시험에 응시하여 모두 단 한 번만에 합격했습니다.

소프트웨어 산업에서 30년 이상의 경력을 쌓아오며, 저는 실무 데이터 아키텍트, 솔루션 아키텍트, 기술 매니저, 팀 리드, 그리고 소프트웨어/데이터 엔지니어로 활동해 왔습니다.

저는 또한 성공적인 기업가이자 독립 컨설턴트로서, 수많은 고객과 함께 실무 데이터 과제를 해결해 왔습니다.

이전에는 마이크로소프트에서 근무하며 제가 작성한 코드의 일부가 여전히 Microsoft SQL Server 및 Windows의 일부로 남아 있는 시스템에 기여했습니다.

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