Explore Courses
Browse our full catalogue of AI-powered learning experiences across every discipline.
Results 144
My Little AI Agent
AI000My Little AI Agent
Designed for preschool learners, this course transforms complex computer science concepts—such as Agents, evolutionary learning, prompting, and even negative entropy—into concrete, playful, and age-appropriate experiences. Across five lessons, children build foundational AI literacy: understanding what AI is and how it helps people, learning to give clear instructions (prompting), exploring specialized AI "helpers" (agents) and teamwork, discovering how AI learns from data and mistakes, and finally engaging in a guided human–AI co-creation project that promotes creativity, responsibility, and technology-for-good values.
Introduction to Python Programming
AI001Introduction to Python Programming
Learn Python, a popular programming language, covering core concepts for everything from web and software development to data science and quality assurance. Skills gained include writing Python 3 programs and simplifying code.
Applied Deep Learning with PyTorch (Zero to Mastery)
AI002Applied Deep Learning with PyTorch (Zero to Mastery)
This course provides a comprehensive introduction to Deep Learning using PyTorch, the most popular framework for machine learning research. Starting from tensor fundamentals, students will progress through the complete ML workflow, computer vision, modular software engineering, transfer learning, and model deployment. The curriculum is "code-first," emphasizing hands-on implementation and experimentation.
Introduction to Deep Learning
AI003Introduction to Deep Learning
Deep learning is a sub-field of machine learning that focuses on learning complex, hierarchical feature representations from raw data using artificial neural networks. The course covers fundamental principles, underlying mathematics, optimization concepts (gradient descent, backpropagation), network modules (linear, convolution, pooling layers), and common architectures (CNNs, RNNs). Applications demonstrated include computer vision, natural language processing, and reinforcement learning. Students will use the PyTorch deep learning library for implementation and complete a final project on a real-world scenario.
AI Magic Lab
AI004AI Magic Lab
A rigorous course structure integrating four major sections: AI Fundamentals, Large Model Generation (GenAI & LLM), Agents and Evolutionary Computation (highlighted as a PolyU Feature), and Ethics. The course logic progresses sequentially through Perception & Data (L1-3), Cognition & Generation (L4-6), Agents & Evolution (L7-9), and concludes with Ethics & Future (L10).
AI Mastery Bootcamp: From Zero to Agent Architect
AI005AI Mastery Bootcamp: From Zero to Agent Architect
A 5-session intensive bootcamp designed to transform beginners into AI Agent Architects. The curriculum covers the 'BRIC' framework for prompt engineering, content acceleration for reading and viral copywriting, workplace automation for Excel and PowerPoint, building a 'Second Brain' using RAG (Retrieval-Augmented Generation), and creating autonomous digital employees.
Advanced Guide to Prompt Engineering for Large Language Models
AI006Advanced Guide to Prompt Engineering for Large Language Models
A comprehensive advanced guide to mastering AI through structured logic and precise instruction. The course covers structural frameworks (CO-STAR), Few-Shot learning, Chain of Thought reasoning, output format constraints (JSON/Markdown), and prompt system management to resolve issues such as AI hallucinations and poor logical output.
OpenClaw: Architecture, Dev & Security for Local AI Agents
AI007OpenClaw: Architecture, Dev & Security for Local AI Agents
This course provides an in-depth analysis of OpenClaw, a groundbreaking open-source framework for autonomous AI agents. It systematically deconstructs the framework's layered system architecture, local-first RAG memory mechanisms, browser automation protocols, and highly scalable skill ecosystem. The curriculum covers practical orchestration of complex workflows, including PIV automation flows and multi-agent committee patterns. Furthermore, it critically analyzes hardware trade-offs in production-grade deployment paradigms and presents defense-in-depth strategies against core security threats such as RCE vulnerabilities and prompt injection. The course aims to empower senior developers and architects to build AI agent systems that possess high autonomy while remaining secure and controllable.
Large Language Models for Everyone: From Basics to Practical Use (2026 Edition)
AI008Large Language Models for Everyone: From Basics to Practical Use (2026 Edition)
This course is a beginner-friendly, practical introduction to Large Language Models (LLMs) such as ChatGPT and Gemini. Designed for learners from any background, it explains how LLMs work at a high level, what they can and cannot do, and how to use them effectively in study, work, and everyday life. Through hands-on demonstrations and guided exercises, you will learn prompt techniques, how to evaluate outputs critically, how to handle hallucinations and bias, and how to use common tools (e.g., documents, summaries, translation, data tasks) safely and responsibly. By the end of the course, you will be able to build a personal “LLM workflow” for real tasks—writing, research, planning, and productivity—without needing advanced coding skills.
《神经和形态发育系统的演化计算及应用——通向通用人工智能的新途径》（15节课）
AI009L《神经和形态发育系统的演化计算及应用——通向通用人工智能的新途径》（15节课）
本书从计算建模的角度研究神经系统与形态（身体）的协同演化与发育。内容涵盖演化算法、基因调控网络、多细胞生长模型、神经可塑性规则以及脑-体协同演化等，旨在为通向通用人工智能（AGI）提供一种基于生物自适应机制的新途径。
Introduction to LLMs for Developers
AI010Introduction to LLMs for Developers
This course is a Chinese-adapted version of the three-course large language model series jointly launched by Andrew Ng and OpenAI. It covers Prompt Engineering, building systems with the ChatGPT API, LangChain application development, and using LangChain to access private data. The course provides a clear and accessible introduction to how to leverage the capabilities of large language models to build applications with summarization, inference, transformation, expansion, and chat functions.
Generative AI for Beginners
AI011Generative AI for Beginners
A comprehensive curriculum exploring the fundamentals of Generative AI, Large Language Models, prompt engineering, and the development of AI-powered applications using tools like Azure OpenAI and the Power Platform.
Deep Dive into Large Language Models
AI012Deep Dive into Large Language Models
This course provides a comprehensive and in-depth introduction to the development history of large language models (LLMs), their core technical architectures, training paradigms (pretraining, fine-tuning, and alignment), multimodal extensions, prompt engineering, chain-of-thought reasoning, agents, as well as frontier topics such as model safety and privacy protection.
Modern C++ Tutorial
AI013Modern C++ Tutorial
This tutorial aims to provide experienced developers with a quick reference to the new features of C++11/14/17/20. It covers language usability enhancements, runtime improvements, new containers, smart pointers and memory management, regular expressions, concurrent programming, and a preview of C++20.
An Introduction to R Programming
AI014An Introduction to R Programming
This course is a comprehensive introduction to the R language environment, covering core topics from basic numeric vector operations, object attributes, array and matrix processing, list and data frame management, to statistical modeling and high-quality graphics production. It is highly suitable as an introductory text for statistical analysis and data science.
Introduction to Julia Programming
AI015Introduction to Julia Programming
A comprehensive guide to the Julia programming language, a high-performance, general-purpose dynamic language well-suited for scientific and numerical computing. The course covers everything from basic syntax and data types to advanced topics like metaprogramming, data frames, networking, and database interfacing.
Ry's Git Tutorial
AI016Ry's Git Tutorial
A comprehensive guide to Git version control, moving from basic workflows like staging and committing to advanced topics like interactive rebasing, remote collaboration, and the internal plumbing of Git's object database.
Get Programming with Go
AI017Get Programming with Go
A beginner-friendly, hands-on introduction to the Go programming language. The course is structured into small, manageable lessons with a space-exploration theme, covering imperative programming, types, functions, methods, collections, state, and concurrency.
NumPy User Guide
AI018NumPy User Guide
A comprehensive introductory overview and technical guide to NumPy, covering installation, array manipulation, indexing, broadcasting, and integration with C/C++.
Programming Elixir
AI019Programming Elixir
A comprehensive guide to functional and concurrent programming using Elixir. It covers the transition from object-oriented to functional thinking, pattern matching, immutability, the actor model for concurrency, and building robust distributed systems with OTP.
Eloquent JavaScript: A Modern Introduction to Programming
AI020Eloquent JavaScript: A Modern Introduction to Programming
A comprehensive guide to modern programming using JavaScript. The course covers fundamental programming principles, the JavaScript language specification, web browser integration, and server-side development with Node.js, including five real-world project applications.
CUDA Programming Guide
AI021CUDA Programming Guide
The official, comprehensive resource for developers to learn the CUDA programming model and how to write high-performance code that executes on NVIDIA GPUs. This guide covers the platform architecture, programming interface, advanced hardware features, and technical specifications.
AMD HIP Programming Guide
AI022AMD HIP Programming Guide
A comprehensive technical manual for the Heterogeneous-compute Interface for Portability (HIP). It provides a C++ Runtime API and kernel language that allows developers to create portable applications for AMD and NVIDIA GPUs from a single source code. The guide covers installation, environment configuration, programming models, memory allocation, and tools for porting CUDA code to HIP.
Introduction to Triton Programming: A Practical Tutorial
AI023Introduction to Triton Programming: A Practical Tutorial
A comprehensive scientific tutorial designed to provide a full learning path for Triton, a Python-based language and compiler for writing custom GPU kernels. The course covers programming models, language semantics, numerical behavior, and performance optimization, moving from basic vector addition to fused and tiled operators used in modern deep learning systems.
Introduction to ROCm and HIP Programming: A Practical Tutorial
AI024Introduction to ROCm and HIP Programming: A Practical Tutorial
A practical, modern guide to AMD GPU programming with ROCm and HIP. It covers the full software stack, installation, build workflows, kernel programming, memory management, performance engineering, library usage, CUDA porting, and production debugging practices.
Practical RAG Systems: From Knowledge Bases to Retrieval-Augmented Generation
AI025Practical RAG Systems: From Knowledge Bases to Retrieval-Augmented Generation
These student lecture notes provide a systems-level view of building usable Retrieval-Augmented Generation (RAG) systems. The course covers the entire pipeline including data ingestion, chunking strategies, embedding mapping, vector storage, hybrid retrieval, reranking, and evaluation for trustworthy AI applications.
Python Data Structures and Algorithm Analysis (2nd Edition)
AI028Python Data Structures and Algorithm Analysis (2nd Edition)
This book is a classic textbook on data structures and algorithms using Python. It covers Python basics review, algorithm analysis (Big O notation), fundamental data structures (stacks, queues, lists), recursion, searching and sorting, tree and graph algorithms. Through practical code listings, it helps readers understand how to efficiently implement various abstract data types using Python.
Reinforcement Learning: An Introduction
AI029Reinforcement Learning: An Introduction
A comprehensive foundational textbook on reinforcement learning, covering key algorithms such as Q-learning, Sarsa, and TD-learning, while bridging the gap between tabular methods and function approximation.
Generative AI Foundations in Python
AI030Generative AI Foundations in Python
A comprehensive guide to understanding and implementing Generative AI and Large Language Models (LLMs). This course covers the transition from theoretical foundations to practical Python-based development, including GANs, diffusion models, transformers, fine-tuning, and production deployment.
Computer Systems: A Programmer's Perspective (Global Edition)
AI031Computer Systems: A Programmer's Perspective (Global Edition)
A comprehensive deep-dive into how computer systems execute programs and store information. This course bridges the gap between high-level programming and the underlying hardware, covering machine-level representation, processor architecture, memory hierarchy, and concurrent programming.