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AI001

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.

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.