#Python tutorial stages
81 related articles
·7 min
Building an AI Agent from Scratch: Implementing Core Conversational Agent Features in Python
Learn AI Agent development from scratch. This tutorial covers LLMs and prompts, then builds a conversational agent in Python using the DeepSeek API with multi-turn dialogue and system prompts.
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·6 min
Python Freelancing Side Hustle in Practice: Platform Channels, Pitfall-Avoidance Guide & Complete Monetization Breakdown
A complete guide to Python tech freelancing: platform comparisons, milestone payment strategies, legal boundaries, delivery management, and building stable client relationships for sustainable side income.
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·3 min
Java AI Framework Comparison: A Selection Guide for Spring AI, LangChain4J, and More
In-depth comparison of four Java AI frameworks — Spring AI, LangChain4J, DJL, and JBot AI — covering features, use cases, and ecosystem compatibility to guide your selection.
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·4 min
AI Agent Development Learning Roadmap: A Complete Four-Stage Plan from Zero to Production
A systematic AI Agent development learning roadmap covering LLM fundamentals, ReAct paradigm, memory & tool calling, and multi-agent collaboration across four stages with project suggestions.
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·2 min
AI LLM Development Career Path: Four Stages from Zero to $60K+/Year
A four-stage learning path for AI LLM application development: from Python basics and RAG architecture to Agent cluster orchestration, helping developers transition into AI roles.
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·3 min
Complete Tutorial: Build a Free AI Code Editor with DeepSeek + VS Code
Step-by-step guide to building a free AI code editor using DeepSeek R1's free API with VS Code and Roo Code plugin. Generate a Snake game with one sentence—the best free Cursor alternative.
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·4 min
VibeCoding Progression Roadmap: 4 Stages, 12 Projects — From Zero to Architect
VibeCoding keeps failing? The core issue is a mismatch between project choice and skill level. A complete 4-stage, 12-project roadmap from zero to architect.
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·3 min
The Complete Guide to OpenAI Codex CLI: From Installation and Configuration to Enterprise-Level Practice
In-depth guide to OpenAI Codex CLI: covering installation, agents.md design, multi-agent collaboration, MCP protocol integration, and a RAG customer service project.
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·3 min
Hermes Agent Practical Tutorial: Architecture Analysis and Three Automation Project Builds
Complete guide to Hermes Agent from basics to practice, covering architecture analysis, Rules.md configuration, MCP service integration, and three hands-on projects: AI news bot, auto blog development, and scheduled code review.
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·4 min
AI Agent Systematic Learning Path: From Zero to Independent Development
A systematic AI Agent learning path covering core principles, Prompt engineering, RAG, multi-Agent collaboration, and hands-on projects for beginners.
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·4 min
AI Agent Development: A Complete 6-Week Systematic Learning Roadmap
A 6-week systematic learning roadmap for AI Agent development, covering core architecture, ReAct principles, multi-agent collaboration, RAG integration, and deployment.
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·4 min
Complete AI Large Language Model Learning Roadmap: From Beginner to Production-Ready
A systematic guide to learning AI large language models, covering Transformer architecture, prompt engineering, RAG, AI Agents, fine-tuning, and enterprise projects from beginner to production-ready.
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·4 min
Getting Started with Huawei Ascend C Operator Programming: Kernel Functions and Hands-On Development Guide
A systematic guide to Huawei Ascend C operator programming covering kernel functions, three-stage pipeline paradigm, API categories, and a hands-on AddCustom operator walkthrough.
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·3 min
Harness AI Engineering Programming: A Detailed Methodology for Enterprise-Level Project Development
Deep dive into Harness AI Engineering Programming methodology, covering SDD, Skill development patterns, and core practices for enterprise-level AI-assisted development.
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·2 min
Getting Started with AI Agent Development: A Three-Stage Learning Roadmap Explained
A complete roadmap for learning AI Agent development from scratch. Covers Python basics, LLM concepts, five core capabilities, mainstream frameworks, and RAG knowledge base projects.
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·4 min
Claude Code Practical Guide: Deep Dive into 7 Core Modules with Learning Path
Deep dive into Claude Code's 7 core modules: project integration, agent construction, multi-agent collaboration, plugin systems, and workflow automation, with learning tips and certification trends.
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·3 min
AI Large Language Model Learning Roadmap for Beginners: A Three-Month Hands-On Guide
A detailed zero-to-hero AI large model learning roadmap covering four phases—fundamentals, RAG, Agents, and engineering deployment—with a practical three-month study plan and career advice.
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·4 min
5 Viable Paths to Making Money Independently with Python
5 proven paths to making money independently with Python: automation scripts, AI app development, quantitative trading, tool/course sales, and full-stack web services, with pricing references and practical tips.
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·3 min
Codex Hooks Explained: The Automation Powerhouse That Hijacks the Entire AI Workflow
Deep dive into Codex Hooks' six lifecycle hook types, covering configuration, local vs global hooks, and practical use cases like security interception and auto-summarization for full AI workflow control.
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Tutorials·2 min
Getting Started with RAG: What Is Retrieval-Augmented Generation and How Does It Solve LLM Hallucination?
RAG (Retrieval-Augmented Generation) is the core solution for LLM hallucination. Learn RAG concepts, how it works, three causes of hallucination, and the complete learning path from basics to Knowledge Graph RAG.
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