Programme Outline
Learning Objectives
By the end of the course, participants should be able to:
- Understand the basics of Artificial Intelligence and Natural Language Processing
- Learn about the development and current trends of Large Language Models
- Gain a deeper understanding of the capabilities and key concepts of GPT technology
- Understand and describe the strengths and limitations of GPT
- Perform interactions with ChatGPT and utilize GPT in their respective domains or daily life
- Identify and discuss potential use cases and industry applications of ChatGPT
Day 1
- Overview of Machine Learning and Neural Network
- Introduction to Natural Language Processing (NLP), Language Model and Self-supervised Learning
- Recurrent Neural Network (RNN) and Transformer
- Intro to Large Language Model (LLM)
- The development of NLP, LLM, and ChatGPT
- Fundamental concepts in ChatGPT
- Capabilities, strengths, risks and limitations of ChatGPT
Day 2
- Getting started with ChatGPT
- Hands-on exercises on Playground and GPT application programming interface (API)
- Prompt Engineering: Intro, Few-Shot vs. Zero-Shot Learning, Chain-of-Thought (CoT)
- Case studies of ChatGPT in real world
- Discussions of industry and business applications
- Advanced topics I : Short-term vs. Long-term Memory, solutions to token limitations
- Advanced topics II: automatic finishing task, function-call, code interpreter, ChatGPT plugins
Day 3
- In-class group project: group assignment and project instruction
- In-class group project: group discussion and decision on project topics
- In-class group project: group work and preparation
- In-class group project: group project and presentation preparation
- Final group project presentation and discussion
- Debrief and closing remarks
Assessment
- In-class final group project and presentation
- Attendance and class participation
- In-class quiz and assignment