Computer Science

💡 GENAI-001 | Introduction to Generative AI and Education

• Module 1: Basics of Generative AI (~20 mins)
• Module 2: Applications of Generative AI in Education (~50 mins)
• Module 3: Challenges and Ways Forward in the AI Era (~30 mins)

💡 GENAI-002 | Prompt Engineering for Generative AI in Education

• Module 1: ChatGPT101: Foundation and Overview (40 mins)
• Module 2: Strategies for Designing Assessments: A Passive-Participatory Model (50 mins)
• Module 3: Elevating Prompt Design: Advance Techniques (50 mins)

💡 GENAI-003 | AI-Enhanced Assessment: Frameworks and Guidelines for Innovative Design and Practice

• Module 1: Rethinking Assessment Design in the AI-Era (40 mins)
• Module 2: First Steps in Prompting Techniques (30 mins)
• Module 3: The Role of Gen AI in Shaping Dialogic Learning Experiences and Assessments (50 mins)

HKUST members can register through HKUST Engage. Successful applicants will receive an invitation email (with LinkedIn Learning activation link) within 1 working day.

💡 How to Research and Write Using Generative AI Tools (1h 15m)

This course teaches generative AI and prompt engineering for ChatGPT and other chatbots. It covers key considerations and hands-on strategies for research and writing, including summarizing, perspective-taking, building user personas and models, analyzing style, outlining, and generating new content.
 

💡 Introduction to Prompt Engineering for Generative AI (44m)

This course provides an introduction to NLP capabilities and modern NLP APIs. It covers large language models, text generation, ChatGPT, GPT-3, J1, Dall-E, and Midjourney. The instructor also covers advanced concepts like fine-tuning prompts and interacting with language models using an API. 
 

More courses on Generative AI
More courses on AI foundations, machine learning, NLP, etc.

HKUST members can access these courses and get a certificate for free through the Coursera Partner Consortium Program.

💡 Prompt Engineering for ChatGPT (~18h) - by Vanderbilt University

In this course, you will:

• learn the patterns and approaches for writing effective prompts for large language models like ChatGPT
• see examples of how to tap into these generative AI tools' emergent intelligence and reasoning, and how to use them to be more productive day-to-day
• gain insight into how these tools work

💡 ChatGPT Teach-Out (~6h) - by University of Michigan

This course covers topics including: 

• What is ChatGPT and how does it work? 
• What are the benefits and drawbacks of using ChatGPT? 
• What are legal implications of using ChatGPT? 
• How have society, the economy, and education responded to ChatGPT? 
• How might ChatGPT be integrated into society moving forward? 

HKUST members can access O'Reilly through this page. Select "Institution not listed", then type in HKUST email to register an account.

💡 Expert playlist - ChatGPT

The potential applications of ChatGPT are endless, but what's behind this state-of-the-art AI technology? Explore ChatGPT in-depth as you get up to speed on the transformer architecture of GPT models, developments in generative AI, building applications with GPT-based models, and more.
 

💡 Introduction to Transformer Models for NLP: Using BERT, GPT, and More to Solve Modern Natural Language Processing Tasks (11h 19m)

This course provides a practical and comprehensive understanding of transformer architectures, attention, embedding, and tokenization, which are used to create modern NLP pipelines such as BERT and ChatGPT. The course includes real-life case studies and hands-on code examples, and after completion, students will be able to build cutting-edge NLP pipelines using transformers.

📙 Books on Language Models, GPT, Transformers, NLP

These short courses help you learn new skills, tools, and concepts of generative AI efficiently. Available for free for a limited time.

💡 Generative AI for Everyone (3h)

• Learn directly from Andrew Ng about the technology of generative AI, how it works, and what it can (and can’t) do
• Get an overview of AI tools, and learn from real-world examples of generative AI in use today
• Understand the impacts of generative AI on business and society to develop effective AI strategies and approaches

💡 ChatGPT Prompt Engineering for Developers (1h)

This course teaches how to use large language models (LLMs) through the OpenAI API to build powerful applications for tasks such as summarizing, inferring, transforming text, and expanding. The course covers best practices for prompt engineering, two key principles for writing effective prompts, and building a custom chatbot with hands-on experience in a Jupyter notebook environment.
 

💡 Building Systems with the ChatGPT API (1h)

In this course, you will learn how to automate complex workflows using chain calls to a large language model. You will build chains of prompts that interact with prior prompts and Python code, and create a customer service chatbot. The course teaches practical skills for classifying user queries, evaluating user queries for safety, and processing tasks for multi-step reasoning.
 

💡 AI For Everyone (~10h)

This course teaches the meaning behind AI terminology, how to spot opportunities to apply AI, how to build machine learning and data science projects, how to work with an AI team, and how to navigate ethical and societal discussions surrounding AI. It is suitable for non-technical colleagues and engineers who want to learn the business aspects of AI.
 

More courses at DeepLearning.AI site (some paid)
More DeepLearning courses on Coursera (free viewing)

💡 AI for Beginners

Microsoft launched a series of free 12-week course (on GitHub) to learn AI and GenAI related topics.

• AI for Beginners
• Generative AI for Beginners
• Data Science for Beginners

💡 Generative AI learning path

This learning path guides you through a curated collection of content on generative AI products and technologies, from the fundamentals of Large Language Models to how to create and deploy generative AI solutions on Google Cloud.

1. Introduction to Generative AI (22min)
2. Introduction to Large Language Models (15min)
3. Introduction to Responsible AI (9min)
4. Introduction to Image Generation (9min)
5. Encoder-Decoder Architecture (27min)
6. Attention Mechanism (5min)
7. Transformer Models and BERT Model (22min)
8. Create Image Captioning Models (29min)
9. Introduction to Generative AI Studio (15min)