#AI Agent course
1124 related articles
·8 min
LangChain Crash Course: A Complete Roadmap from Zero to Agent Development
A systematic roadmap from LangChain and LangGraph to multi-agent development, covering RAG, Tool Calling, MCP, and more, helping developers break into AI app development.
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·2 min
WhatsApp AI Agent in Action: A Complete Service Pipeline for Online Courses
Learn how to build a full WhatsApp AI Agent pipeline for online courses — from ad-driven lead capture and smart screening to automated service delivery and silent lead re-engagement.
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·3 min
How to Choose an AI Agent Development Course? 5 Practical Screening Criteria to Avoid Common Pitfalls
How to choose a quality AI Agent development course? This guide covers 5 key criteria: complete delivery pipeline, resume-worthy projects, real engineering perspective, update frequency, and mentorship.
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·3 min
How to Choose a Practical LLM/RAG/AI Agent Course: Four Key Criteria
Learn how to pick the best LLM, RAG, and AI Agent courses. Discover 4 key criteria for hands-on AI learning and top resources for developers.
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·2 min
Claude Code Practical Course Breakdown: From AI Programming Methodology to Autonomous Agent Building
Deep dive into a Claude Code AI programming course covering AFK autonomous Agent building, codebase optimization, and multi-stage Kanban management to enable efficient human-AI collaboration.
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·2 min
Andrew Ng's Agent Skills Course Explained: Building Reusable Professional Skills for AI Agents
Deep dive into Andrew Ng's Agent Skills course with Anthropic, covering Skills architecture, progressive loading, MCP integration, and hands-on examples for building reusable AI agent skills.
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Tutorials·3 min
Andrew Ng's Agent AI Course Fully Explained: Why It's Taking the Tech World by Storm
Deep dive into why Andrew Ng's Agent AI course went viral, covering the five-module agent architecture breakdown, course highlights, target audience, and learning tips for developers.
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Tutorials·3 min
Complete Breakdown of Andrew Ng's Agent Course: A Practical Guide to the Five Core Modules of AI Agent Development
Deep dive into Andrew Ng's viral AI Agent course covering five core modules: Reflection, Planning, Tool Use, Multi-Agent Collaboration, and Memory, with practical learning paths for LLM agent development.
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Tutorials·1 min
Andrew Ng's New Course Explained: Agent Memory Engineering from Basics to Practice
Deep dive into Andrew Ng's Agent Memory course with Oracle: covering memory engineering concepts, memory-first architecture design, and building AI agents with persistent memory.
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Deep Dives·1 min
Berkeley CS294 Course: A Complete Guide to Agentic AI Security — Attacks and Defenses
A deep dive into Berkeley CS294-196's agentic AI security lecture, covering prompt injection, indirect injection, AgentPoison backdoor attacks, defense-in-depth, least privilege, and runtime guardrails.
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Tutorials·1 min
AI Agent Open-Source Course: 36 Chapters from ReAct to Claude Code Full-Stack Practical Guide
Open-source GitHub project agent-study offers 36 chapters covering ReAct loops, Claude Code reverse engineering, MCP protocol, RAG, DSPy, and production observability as runnable Python code.
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Product Reviews·5 min
Manus vs Google Deep Research vs Flowith: A Hands-On Comparison of AI Agents for Courseware Generation
Hands-on comparison of Manus, Google Deep Research, and Flowith generating Kafka courseware with the same prompt. Detailed scoring reveals which AI agent delivers the best results.
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Deep Dives·2 min
Hung-yi Lee's 2026 Course Notes: Deep Dive into the Three Core Capabilities of AI Agents
Notes from Hung-yi Lee's 2026 AI Agent course covering AI Agent definition, LLM-driven principles, and three core capabilities: Memory, Function Calling, and Planning with Tree Search.
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Tutorials·3 min
Andrew Ng's 2025 New Course: Core Methodology and Best Practices for Building AI Agents
A deep dive into Andrew Ng's latest Deeplearning.AI course on AI Agents, covering Agentic AI use cases, disciplined development workflows, evaluation frameworks, and error analysis methodology.
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Tutorials·3 min
Andrew Ng's New Course: A Practical Guide to Data Governance for Enterprise AI Agents
Andrew Ng and Databricks launch an AI Agent data governance course covering least privilege principles, Unity Catalog permissions, MLflow tracing, and a complete governance lifecycle from build to deployment. Free to learn.
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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
Cursor vs Claude Code: How to Choose an AI Coding Tool on a $20 Budget
On a $20/month budget, should you choose Cursor or Claude Code? A deep comparison of pricing, quota consumption, and workload matching to help developers decide.
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·3 min
GitHub Daily · August 1: The Rise of SuperAgents and Generative AI's Mass Education Moment
GitHub trending Aug 1: ByteDance's deer-flow SuperAgent, Microsoft's GenAI course, 3D generation, voice cloning, and privacy-first tools shape the AI landscape.
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·5 min
Have AI Doomers Actually Used AI? A Developer Exposes the Gap Between Hype and Reality
AI Doomers warn AI will destroy humanity, but have they actually built AI apps? A developer's sharp critique reveals the vast gap between AI demos and real engineering practice.
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·3 min
AI Costs Out of Control: Inference Expenses Skyrocketing—Who's Footing the Bill?
An in-depth analysis of why AI costs keep rising—inference expenses, premium model pricing, and context bloat—plus practical optimization strategies including model cascading, caching, and self-hosting.
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