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Entry Level Artificial Intelligence Course
Learn the basics of artificial intelligence, including machine learning, neural networks, and natural language processing.
Introduction 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)
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
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
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
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.
Prompt Engineering Advanced Guide
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
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.
HKU | China’s Ethnic Groups: Pluralism and Assimilation
Explore the diverse ethnic groups of China, their cultures, and the dynamics of pluralism and assimilation
PolyU | Artificial Intelligence Concepts
This comprehensive course provides a rigorous yet accessible introduction to Artificial Intelligence, designed for postgraduate students and professionals. Bridging the gap between historical foundations and cutting-edge innovations, the curriculum progresses from symbolic AI and search algorithms to modern Deep Learning and Generative AI. Students will explore essential topics such as knowledge representation, probabilistic reasoning, and classical machine learning before diving deep into neural networks, Transformers, and Large Language Models (LLMs). Emphasizing both theory and practice, the course utilizes Python and industry-standard frameworks like PyTorch to implement algorithms, interact with modern APIs, and address critical issues in AI ethics and safety.
PolyU | Introduction to Data Analytics
This is a foundational undergraduate course offered in Spring 2026 at PolyU that introduces students to the core concepts, methods, and tools of data analytics. The course builds a solid analytical foundation by integrating essential mathematics (linear algebra and calculus) with practical skills in R programming, data manipulation, and data visualization, and progresses to key analytical techniques such as Monte Carlo simulation, linear regression, and time-series analysis. Through a balanced mix of theory and hands-on practice, students learn how to analyze and interpret data systematically, with learning assessed through quizzes, assignments, a midterm test, and a final examination.
PolyU | Data Structures and Algorithms
Learn the fundamentals of data structures and algorithms, including arrays, linked lists, trees, sorting, and searching techniques.
Visual English Grammar - Welcome
Learn the basics of English grammar, vocabulary, and conversation skills.
Visual English Grammar - The Basics
Learn the basics of English grammar, vocabulary, and conversation skills.
Visual English Grammar - Intermediate Level
Learn the basics of English grammar, vocabulary, and conversation skills.
Visual English Grammar - Advanced Level
Learn the basics of English grammar, vocabulary, and conversation skills.
Visual English Grammar - English Tenses Mastery
Learn the basics of English grammar, vocabulary, and conversation skills.
Lighthouse for Hong Kong: Book 9
A comprehensive English language practice book designed for upper primary students in Hong Kong. It covers diverse themes including global cuisine, future technology, social events, detective mysteries, and classical fairy tales, focusing on reading comprehension, thematic vocabulary, and essential grammar structures.
【人教版】初中英语 七年级上册
本教材为2024年秋季启用的新版七年级英语教材。全书包含三个过渡单元（Starter Units）和七个正式单元，内容涵盖自我介绍、家庭成员、校园环境、学科喜好、学校社团、日常生活及生日庆祝等主题。旨在通过Section A和Section B的多维度活动，夯实学生的语言基础，培养跨文化交际能力。
SUSTech | Introduction to Sociology of Education
This General Education (GE) elective course offers a comprehensive introduction to the fundamental theories and frontier issues within the sociology of education. Designed to cultivate strong critical thinking and interdisciplinary analysis, particularly benefiting STEM students, the course equips learners to use sociological frameworks to objectively analyze contemporary social challenges and educational reforms. The small class size (maximum 32 students) fosters a highly interactive learning environment, supported by weekly readings of classic sociological texts. Key assignments include a group mid-term research design summary and an individual final presentation (30% of the final grade). No prerequisites are required.