Introduction
The Generative AI and AIoT (GenAIoT) Coding Skills Education for Gifted Students programme aims to equip gifted students with essential knowledge related to AI, GenAI and AIoT technologies, engineering and mathematics, problem solving abilities, as well as other hands-on skills including software and hardware programming.
The programme also aims to nurture positive values and attitudes among gifted students, such as ethics of using AI technology, ability to distinguish between real and fake contents, and perseverance to overcome problems, empowering them to become youth leaders with the right values.
Programme objectives
- To provide gifted students with knowledge of foundation mathematics for use in AI and Python programming for development of relevant AI applications
- To equip students with engineering skills and experiences, through lab sessions, assignments and projects, to develop IoT devices by using advanced hardware and software utilised in the industry
- To develop gifted students’ hands on coding abilities and problem solving skills to carry out AI projects, especially developing their own AI model, and have the ability to evaluate its quality
- To enhance gifted students’ awareness of the applications and development of generative AI, LLM, GPT, etc, and encourage them to explore further to create their own applications
- To inspire gifted students about the role and computation of System on Chip (SoC) and Integrated Circuit (IC) in AI
- To arouse students’ awareness on ethics of using AI in daily life and its security issues, and nurture their ability to distinguish between real and generated fake contents
- To nurture positive values and attitudes among students and foster their perseverance in overcoming problems
Timeline
| Date and Time | Contents |
|---|---|
| 17 May 2024 (Fri) 05:30pm-07:30pm |
Foundational Guest Lecture on Generative AI and AIoT I |
| 24 May 2024 (Fri) 05:30pm-07:30pm |
Getting familiar with the coding environment and GitHub |
| 31 May 2024 (Fri) 05:30pm-07:30pm |
Foundational Guest Lecture on Generative AI and AIoT II |
| 7 Jun 2024 (Fri) 05:30pm-07:30pm |
Python Packages for Machine Learning – NumPy |
| 14 Jun 2024 (Fri) 05:30pm-07:30pm |
Foundational Guest Lecture on Generative AI and AIoT III |
| 21 Jun 2024 (Fri) 05:30pm-07:30pm |
Python Packages for Machine Learning – NumPy (Cont’d) |
| 28 Jun 2024 (Fri) 05:30pm-07:30pm |
Foundational Guest Lecture on Generative AI and AIoT IV |
| 5 Jul 2024 (Fri) 05:30pm-07:30pm |
Python Packages for Machine Learning – Pandas, Scikit-Learn |
| 12 Jul 2024 (Fri) 05:30pm-07:30pm |
Python Packages for Machine Learning – Pandas, Scikit-Learn(Cont’d) |
| 19 Jul 2024 (Fri) 05:30pm-07:30pm |
Definition, Developments and Applications of AI Supervised Learning in Detail |
| 26 Jul 2024 (Fri) 05:30pm-07:30pm |
Different Kinds of Machine Learning Methods: Supervised Learning, Unsupervised Learning, Reinforcement Learning, Generative Adversarial Network (GAN) |
| 2 Aug 2024 (Fri) 05:30pm-07:30pm |
Supervised Learning in Details: Regression vs Classification vs Learning to Rank, Loss Functions |
| 9 Aug 2024 (Fri) 05:30pm-07:30pm |
Introduction to the Fashion MNIST Dataset and Data Pre-processing |
| 16 Aug 2024 (Fri) 05:30pm-07:30pm |
Deep Neural Network Model and Its Training, Python Frameworks for Deep Learning |
| 23 Aug 2024 (Fri) 05:30pm-07:30pm |
Lab Session: Image Recognition with Fashion MNIST Dataset |
| 30 Aug 2024 (Fri) 05:30pm-07:30pm |
Convolutional Neural Network (CNN) |
| 6 Sep 2024 (Fri) 05:30pm-07:30pm |
Overfitting and Regularizations |
| 13 Sep 2024 (Fri) 05:30pm-07:30pm |
Introduction to AI Internet of Things (AIoT) and Edge Computing |
| 20 Sep 2024 (Fri) 05:30pm-07:30pm |
Lecture on AI Processors, Ubuntu Linux Basics and Vim Editor |
| 27 Sep 2024 (Fri) 05:30pm-07:30pm |
PYNQ - Python Productivity for Zynq and the Ultra96V2 Board |
| 4 Oct 2024 (Fri) 05:30pm-07:30pm |
Quantised Neural Network (QNN) |
| 18 Oct 2024 (Fri) 05:30pm-07:30pm |
Lab Session: Implementing QNN on FPGA |
| 25 Oct 2024 (Fri) 05:30pm-07:30pm |
Real Time Object Detection on FPGA with Real Time Streaming Protocol (RTSP) |
| 1 Nov 2024 (Fri) 05:30pm-07:30pm |
AI Research Paper Study - How to Read a Research Paper, AI Open Source Platforms, such as Hugging Face |
| 8 Nov 2024 (Fri) 05:30pm-07:30pm |
Introduction to Language Modeling |
| 15 Nov 2024 (Fri) 05:30pm-07:30pm |
Attention Mechanism, Transformers, and Large Language Models (LLMs) such as Generative Pre-Trained Transformer (GPT) |
| 22 Nov 2024 (Fri) 05:30pm-07:30pm |
Large Language Models (LLMs) |
| 29 Nov 2024 (Fri) 05:30pm-07:30pm |
Ethics of AI: AI Security and Explainable AI (XAI) |
| 6 Dec 2024 (Fri) 05:30pm-07:30pm |
1st Mentorship Meeting |
| 13 Dec 2024 (Fri) 05:30pm-07:30pm |
2nd Mentorship Meeting |
| 20 Dec 2024 (Fri) 05:30pm-07:30pm |
3rd Mentorship Meeting |
| Jan 2025 To be confirmed |
Student Project Presentation, Competition and Exhibition |
Contact Information
Department of Electrical Engineering
City University of Hong Kong
Email: eegefp@cityu.edu.hk
Tel: (852) 3442-7740
Fax: (852) 3442-0562