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 – OpenCV |
| 12 Jul 2024 (Fri) 05:30pm-07:30pm |
Python Packages for Machine Learning – Pandas, Scikit-Learn |
| 19 Jul 2024 (Fri) 05:30pm-07:30pm |
Definition, Developments and Applications of AI |
| 26 Jul 2024 (Fri) 05:30pm-07:30pm |
Different Kinds of Machine Learning Methods: Supervised Learning, Unsupervised Learning, Reinforcement Learning, Generative Adversarial Network (GAN); Supervised Learning in Detail: Regression vs Classification vs Learning to Rank, Loss Functions |
| 2 Aug 2024 (Fri) 05:30pm-07:30pm |
Data Pre-processing (e.g. Fashion MNIST & CIFAR10 Datasets); Overview of Deep Neural Network, its Training, and Inference |
| 9 Aug 2024 (Fri) 05:30pm-07:30pm |
Lab Session: Image Recognition with Fashion MNIST Dataset; Convolutional Neural Network (CNN) |
| 16 Aug 2024 (Fri) 05:30pm-07:30pm |
Convolutional Neural Network (CNN) (Cont’d); Lab Session: Improve Prediction Accuracy with CNN |
| 23 Aug 2024 (Fri) 05:30pm-07:30pm |
Overfitting, Regularizations; Lab Session: Avoid Overfitting and Further Improve Prediction Accuracy with Regularization Techniques, Object Detection |
| 30 Aug 2024 (Fri) 05:30pm-07:30pm |
Machine Learning Dataset Acquisitionl; Object Detection on Jetson Nano |
| 6 Sep 2024 (Fri) 05:30pm-07:30pm |
Introduction to AI Internet of Things (AIoT) and Edge Computing |
| 13 Sep 2024 (Fri) 05:30pm-07:30pm |
AI Processors, Ubuntu Linux Basics and Vim Editor |
| 20 Sep 2024 (Fri) 05:30pm-07:30pm |
Embedded Edge AI on Edge GPU Platform (Nvidia Jetson GPU) |
| 27 Sep 2024 (Fri) 05:30pm-07:30pm |
Lab Session: Yolov8 Object detection and counting on Jetson AGX Orin |
| 4 Oct 2024 (Fri) 05:30pm-07:30pm |
PYNQ - Python Productivity for Zynq and the Ultra96-V2 Board |
| 18 Oct 2024 (Fri) 05:30pm-07:30pm |
Quantised Neural Network (QNN) and Model Compilation for the Inference on FPGA |
| 25 Oct 2024 (Fri) 05:30pm-07:30pm |
Lab Session: Implementing the Deep Learning Processor on FPGA and Performing te Inference; 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; Mentorship Meeting |
| 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 |
Text to Image Generation using LLM |
| 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 |
Mentorship Meeting |
| 13 Dec 2024 (Fri) 05:30pm-07:30pm |
Mentorship Meeting |
| 25 Jan 2025 (Sat) | 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