#Python AI Agent tutorial
263 related articles
·2 min
Hands-On Tutorial: Build an AI Agent from Scratch with 200 Lines of Python
Build an AI Agent from scratch with 200 lines of Python, covering prompts, memory, tool calling, RAG, and Skills — a practical guide for developers.
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·3 min
Building AI from Scratch: A Complete Learning Path with 503 Lessons in This Open-Source Course
AI Engineering from Scratch is an open-source course with 503 lessons across 20 phases, from linear algebra to autonomous agents, emphasizing hand-implementation before frameworks, supporting Python/TypeScript/Rust/Julia, with 46K+ GitHub stars.
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·3 min
The Complete Machine Learning Learning Roadmap: From Anxiety to Clarity
Overwhelmed by machine learning? This practical ML roadmap breaks the journey into three phases—math basics, classical ML, and deep learning—with mindset tips and project strategies for engineers.
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·4 min
AI Engineer Growth Roadmap: From Programming Fundamentals to RAG and MCP Agent Development
A systematic AI engineer learning roadmap covering programming, math, ML, and data engineering foundations, plus frontier AI technologies like LLM, RAG, Agents, and MCP with free open-source resources.
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·3 min
Which ML Projects Will Actually Help You Land a Job Offer?
Ditch overused tutorial projects. Learn what hiring managers actually look for in ML portfolios: LLM apps, Agent systems, MLOps practices, and real-world solutions.
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·3 min
GitHub Daily · August 2: The Dual Explosion of Agent Web Access and the DeepSeek Ecosystem
GitHub Trending Aug 2: Agent-Reach enables zero-cost web access for AI Agents, while DeepSeek ecosystem explodes with ds4 inference engine and Reasonix coding Agent.
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·3 min
Getting Started with MARL (Multi-Agent Reinforcement Learning): A Complete Path from Theory to Code
A systematic guide to learning MARL from theory to code, covering CleanRL, PettingZoo, PyMARL tools, IQL/VDN/QMIX/MADDPG algorithm progression, and practical tips for bridging theory and implementation.
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·3 min
Jina v3 Matryoshka Embeddings in Practice: Cut Vector Storage Costs by 75%
Use Jina v3 Matryoshka embeddings to truncate 1024-dim vectors to 256-dim, cutting Pinecone storage costs by 75% while maintaining retrieval quality with task-specific LoRA adapters and circuit breakers.
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·3 min
Jina v3 Matryoshka Embeddings in Practice: Cut Vector Storage Costs by 75%
Use Jina v3's Matryoshka embeddings to truncate 1024-dim vectors to 256-dim, cutting Pinecone storage costs by 75%. Covers dimension truncation, task-specific LoRA adapters, and circuit breakers for reliable RAG systems.
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·3 min
From Linear Pipelines to State Machines: A Practical Guide to Advanced Agent Architecture
Learn how to advance from linear pipeline to state machine Agent architecture through a YouTube script-to-storyboard case study, covering fault tolerance, LLM evaluation frameworks, and LangGraph vs AutoGen selection.
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·3 min
GitHub Daily · July 28: From Claude Code Skill-ification to AI Agent Governance, the Toolchain Matures
GitHub Trending July 28: Microsoft's agent-governance-toolkit covers OWASP Agentic Top 10, book-to-skill gains 366 stars showing Claude Code skill ecosystem potential, plus browser-based 3D and GIS tools.
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·3 min
Practical Guide to Agent Development: The Complete Path from Zero to Commercial Deployment
A systematic guide to AI Agent development from beginner to deployment, covering task planning, tool calling, memory management, learning paths, and realistic commercial monetization considerations.
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·5 min
Learn AI Agent Development from Scratch: A 3-Step Practical Path to Get Started Quickly
How to learn AI Agent development from scratch? This article outlines a clear 3-step path: Python crash course, LLM theory & practice, and LangChain framework project implementation.
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·3 min
OpenAI Academy's European Tour: How SMEs Can Break Through with AI
OpenAI Academy visits six European nations with its SME AI Accelerator and multilingual workshops, helping small businesses overcome AI adoption barriers through real-world training and hands-on use.
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·3 min
A Beginner's Guide to AI Agents: Two Learning Paths for Developers and Practitioners
How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.
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·3 min
Getting Started with Codex: A Complete Guide to AI Agent Programming Tools
Compare Codex and Claude Code AI agent programming tools. Learn AI Agent concepts, tool selection, cost analysis, and GPT account setup in this complete beginner's guide.
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·3 min
Codex Beginner's Guide: Hands-On Review of OpenAI's Programming Assistant with Practical Tips
A detailed guide to OpenAI Codex's core features, real-world usage, comparison with Claude Code, and DeepSeek configuration tips for developers choosing AI programming tools.
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·3 min
Getting Started with Codex: A Beginner's Guide to AI Agentic Coding Tools
A detailed guide to getting started with Codex and Claude Code AI agentic coding tools, from environment setup to hands-on practice, helping beginners master AI programming assistants.
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·3 min
Getting Started with Codex: A Zero-to-Hero Guide to AI Agentic Coding Tools
A detailed guide to getting started with Codex and Claude Code—two leading AI agentic coding tools. From environment setup to hands-on practice, even beginners with no coding experience can master AI programming assistants.
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·3 min
claude-video: An Open-Source Tool That Teaches Claude to "See" Videos
claude-video is a trending open-source tool that enables Claude to analyze videos via frame extraction and audio transcription. Learn how it works and its use cases.
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