Course materials

MIT's latest report, The Generative AI Divide: the State of Business AI in 2025, reveals the core of the generative AI (GenAI) adoption process that companies are experiencing through in-depth research of more than 300 AI projects, interviews with 52 organizations, and a survey of 153 executives...

Introduction This course will cover: How to effectively plan for the deployment of AI Agent to a production environment. Common mistakes and problems you may encounter when deploying AI Agent to a production environment. How to manage costs while maintaining AI Agent performance. ...

When you start working on a project that involves multiple intelligences, you need to consider the Multi-Intelligence Design Pattern. However, it may not be obvious when to move to multi-intelligents and what the advantages are. Introduction In this course, Microsoft attempts to answer the following questions: What scenarios are applicable to the Multi-Intelligent...

This course provides a comprehensive overview of Agentic Retrieval-Augmented Generation (Agentic RAG), an emerging AI paradigm in which Large Language Models (LLMs) are used to obtain information from external sources in...

Welcome to the Getting Started with AI Agents course! This course provides you with the basics and sample applications for building AI Agents. Join the Azure AI Discord community to meet other learners, AI Agent builders...

INTRODUCTION This paper will cover the following: Define clear overarching goals and break down complex tasks into manageable subtasks. Leverage structured output for more reliable and machine-readable responses. Applying an event-driven approach to dynamic tasks and unexpected inputs. Learning Objectives At the completion of this article...

ChatGPT Tip Engineering for Developers is a joint DeepLearning.AI and OpenAI course designed for developers, featuring Isa Fulford, Andrew Ng to teach how to use Large Language Models (LLMs...

LangChain for LLM Application Development is an online course presented by DeepLearning.AI, featuring LangChain founder Harrison Chase and Andrew Ng.

Introduction Welcome to the course on Metacognition in AI Agent! This chapter is designed for beginners interested in how AI Agents think about their own thought processes. By the end of this course, you will understand the key concepts and have mastered applying metacognition in AI Agent design...

10 Lessons That Teach Everything You Need to Get Started Building an AI Agent This 10-lesson course covers the basics of building an AI Agent. Each lesson covers a separate topic, so you can start anywhere you like! If this is something you...

As AI begins to have a substantial impact on more and more businesses, it is becoming not only a personal assistant for every employee, but also a catalyst for transformation in every organization. Across different functional roles, employees are gradually discovering that AI can help them perform their daily tasks more efficiently and provide many innovative solutions...

AI Agent frameworks are software platforms designed to simplify the creation, deployment, and management of AI Agents. These frameworks provide developers with pre-built components, abstractions, and tools to simplify the development of complex AI systems. These frameworks simplify the development of complex AI systems by providing AI Agent...

Tools are interesting because they allow AI intelligences to have a wider range of capabilities. By adding tools, the intelligence is no longer limited to the limited set of operations it can perform, but can perform a wide variety of operations. In this chapter, we will explore the Tool Usage Design Pattern, which describes A...

Introduction This course will cover: How to build and deploy secure and effective AI Agents Important security considerations when developing AI Agents. How to maintain data and user privacy when developing AI Agents. Learning Objectives After completing this course...

INTRODUCTION There are many ways to build AI Agentic systems. Given that ambiguity is a feature, not a flaw, of generative AI design, it is sometimes difficult for engineers to determine where to start. We have created a set of human-centered user experience design principles that enable developers to build customer-centered...

Transformer LLMs work on the principle that DeepLearning.AI and Jay Alammar and Maarten Grootend, authors of Hands-On Large Language Models...

Hands-On Learning AI: Artificial Intelligence General Knowledge and Practice" of AliCloud, in conjunction with Superstar Erlang, is a systematic learning course on AI for learners of different professional backgrounds. The course is taught by master teachers from five top universities, with comprehensive content, from the development history of AI, core technology to ethical security, etc., to build a complete body of knowledge...

Agentic AI is the newest course on intelligent bodies launched by Ernest Ng.The course focuses on the design and construction of intelligent bodies, covering the four major design patterns of reflection, tool use, planning, and multi-intelligent body collaboration. Learners will master how to make intelligent bodies check outputs, autonomously adjust through theoretical explanations and code practice...

Fundamentals of Large Models provides an in-depth analysis of the core technologies and practical paths of Large Language Models (LLMs). Starting from the fundamental theory of language modeling, it systematically explains the principles of model design based on statistics, recurrent neural networks (RNN), and Transformer architecture, focusing on the three major big language model...

Staying ahead in the age of AI is an AI leadership guide from OpenAI that helps business leaders maintain a competitive edge in the age of AI. The guide points to the rapid growth of AI, with faster model releases, lower costs, and faster enterprise adoption...