135 related articles

Andrew Ng launches LearnVector, using generative AI to deliver one-on-one personalized learning. Explore its core vision, potential capabilities, challenges, and how LLMs can solve education's scalability problem.

Andrew Ng launches LearnVector, leveraging generative AI to create one-on-one personalized learning experiences. Explore its core vision, potential capabilities, challenges, and how LLMs could solve education's scalability problem.
aisuite: Andrew Ng's Open-Source Unifi…
aisuite, open-sourced by Andrew Ng's team, provides a unified interface for calling OpenAI, Anthropic, Google, and other major LLMs. Switch providers seamlessly by just changing the model parameter. 15,000+ GitHub stars.

Andrew Ng's DeepLearning.ai teams up with Anthropic to teach Agent Skills: file structure, progressive disclosure, MCP integration, and the full path from Claude.ai to the Agent SDK.

Andrew Ng's AI prompting course: 4 key differences between beginners and power users — from context input to iterative writing workflows and beating sycophancy.

Andrew Ng and Anthropic's Claude Code course covers RAG development, data analysis, and Figma-to-frontend projects, with deep dives into context management, MCP tools, and CLAUDE.md architecture.

Andrew Ng's AI for Everyone course explained: understand ANI vs. AGI, cut through AI hype and fear, and see how deep learning is transforming every industry.

Andrew Ng partners with JetBrains to launch a Spec-Driven Development course, teaching how to direct AI coding agents via spec files to boost intent fidelity and build maintainable production apps.

Andrew Ng partners with Anthropic to launch a hands-on Claude Code course, revealing its simple architecture, local security edge, and core context methodology across three cases: RAG chatbot, Jupyter analysis, and Figma-to-frontend.

An in-depth analysis of the essentials of Andrew Ng and OpenAI's ChatGPT Prompt Engineering course. Covers the difference between base and instruction-tuned models, two core prompting principles, and how to wield LLM APIs to build apps.

Andrew Ng partners with JetBrains on a new course systematically teaching Spec-Driven Development. By writing high-quality specs, developers can precisely control AI coding agents, eliminate context decay, and boost intent fidelity.

Andrew Ng explains the AI Agent Planning Design Pattern: how LLMs autonomously create step-by-step execution plans using tools, with real-world examples and current limitations.

Andrew Ng and LangChain CEO Harrison Chase present AI Agents in LangGraph, covering five core agent design patterns and LangGraph's graph-based framework for building cyclical agentic workflows.

Andrew Ng and LangChain CEO Harrison Chase's AI Agents in LangGraph course covers five agent design patterns and LangGraph's graph-based framework for building cyclical AI workflows.

DeepLearning.AI and Anthropic launch an Agent Skills course. Learn how Skills work, progressive disclosure, MCP integration, and subagent patterns for AI agent development.

Andrew Ng and Anthropic launch a Claude Code course covering RAG chatbots, data dashboards, and Figma-to-frontend projects, with Git Worktrees and MCP server orchestration.

A systematic overview of Andrew Ng's ChatGPT Prompt Engineering for Developers course: base vs. instruction-tuned models, API best practices, and two core prompting principles.

Andrew Ng's AI Prompting for Everyone course reveals four key gaps between AI beginners and power users: deep thinking tasks, context, neutral prompting, and iterative workflows.

Andrew Ng partners with Anthropic on a Claude Code course covering context configuration, MCP server collaboration, multi-instance workflows, and a RAG chatbot hands-on project.

Deep dive into Andrew Ng's ChatGPT Prompt Engineering course: Base vs. Instruction Tuned LLMs, two core prompting principles, and practical developer methodologies.