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資訊科技與軟體/其他 IT 和軟體/AI 代理和代理 AI

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

Master Claude Code for repo-level development, safe terminal workflows, AI agents, automation, testing, Git, project instructions, and professional developer workflows.

所有級別 • 5 講座 • 終身訪問
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Advanced Claude Code & AI Agents: Build Apps, Automations and Developer Workflows
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活躍的學生
美国英语
99 種語言字幕
4小時 16分
總內容

你將學到什麼

Understand the professional role of Claude Code in developer workflows
Understand the difference between chatbot assistance and agentic coding
Prepare a safe Claude Code development workspace

課程內容

5 部分 • 5 講座 • 04:16:35 總長度

Course Welcome and Expert Roadmap

43:19

This section teaches learners how to set up Claude Code professionally, work safely with terminals and Git, analyze repositories, create strong project instructions, use expert coding-agent prompt patterns, and prepare a reusable AI coding workspace.

Planning an App Before Coding

54:42

This section teaches learners how to plan apps, structure projects, build frontend and backend features, work with databases, debug and refactor code, generate tests and documentation, and complete a professional mini app with Claude Code.

Developer Automation Mindset

49:10

This section teaches learners how to build safe developer automations, terminal workflows, reusable commands, Git and GitHub systems, release documentation, log analysis, and external tool integrations with Claude Code.

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規劃您的學習之旅
AI根據您的可用時間生成個人化時間表

要求

Basic understanding of computers and software development

Basic programming or technical knowledge

A small practice repository

目標受眾

Software-development professionals

Technical content creators

Anyone seeking advanced AI-powered developer workflows

關於本課程

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

職業發展機會與目標職位

掌握前沿實務技能,勝任全球高薪核心職務

就業就緒型課程
可應徵的目標職位

AI Solutions Engineer

Applied Generative AI Specialist

LLM & Prompt Architecture Consultant

AI Automation & Workflow Lead

預估年薪範圍
$105,000 – $165,000 / yr
全球產業需求

Fastest Growing Worldwide (#1)

掌握的核心關鍵技能
Applied Generative AI Architecture
Model Fine-Tuning & Evaluation
Vector Databases & RAG Workflows
Autonomous AI Agent Orchestration
* 估算數據基於全球科技產業薪酬指標與市場招聘報告。
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