Overview
This course teaches participants how to use generative AI tools to solve specific problems within their industry. Through practical examples and hands-on projects, students will learn how to apply generative AI to automate tasks, improve product design, and generate new ideas. This 2-day course aims to equip participants the skillset and knowledge in applying various generative AI tools in their respective industry.
Course Description & Learning Outcomes
In this programme, you will be able to learn/conduct:
• Understand how to harness the power of Commercial LFM.
• Grasp text, image, video, audio, and code generation.
• Apply these APIs adeptly to solve industry problems.
Recommended Prerequisites
Nil
Pre-course instructions
Participants are required to bring and work using their own Windows laptop or MacBook, equipped with a minimum of 16GB RAM, to ensure an optimal learning experience.
Schedule
End Date: 19 Sep 2025, Friday
2-day course: 18 Sep 2025: 9am - 5pm 19 Sep 2025: 9am - 5pm
Location: Blk S, Level 2, S.229/S.230, Nanyang Polytechnic, 180 Ang Mo Kio Ave 8, 569830Agenda
| Day/Time | Agenda Activity/Description |
|---|---|
| (Day 1) 9am - 10am | Introduction to Large Language Model (LLM) |
| (Day 1) 10am - 10.15am | Tea Break (included) |
| (Day 1) 10.15am - 12pm | Prompt Engineering with API + Hands-on Activity 1 |
| (Day 1) 12pm - 1pm | Lunch (NOT included) |
| (Day 1) 1pm - 3pm | Prompt Engineering with Langchain + Hands-on Activity 2 |
| (Day 1) 3pm - 3.15pm | Tea Break (included) |
| (Day 1) 3.15pm - 4.30pm | Building LLM driven Chatbot |
| (Day 1) 4.30pm - 5pm | Knowledge Assessment |
| (Day 2) 9am - 10am | Introduction to Image Generative AI + How Stable Diffusion Model Works? |
| (Day 2) 10am - 10.15am | Tea Break (included) |
| (Day 2) 10.15am - 12pm | Stable Diffusion WebUI and Parameters + Hands-on Activity 1 |
| (Day 2) 12.30pm - 1.30pm | Lunch (NOT included) |
| (Day 2) 1.30pm - 3pm | Image Generation using APIs |
| (Day 2) 3pm - 3.15pm | Tea Break (included) |
| (Day 2) 3.15pm - 3.45pm | Hands-on Activity 2 |
| (Day 2) 3.45pm - 4pm | Introduction to Large Foundation Models |
| (Day 2) 4pm - 5pm | Knowledge Assessment |
Pricing
Course fees: Please refer to the registration link for information on course fees and available funding support
Skills Covered
PROFICIENCY LEVEL GUIDE
Beginner: Introduce the subject matter without the need to have any prerequisites.
Proficient: Requires learners to have prior knowledge of the subject.
Expert: Involves advanced and more complex understanding of the subject.
- Natural Language Processing (NLP) (Proficiency level: Beginner)
Speakers
Trainer's Profile:
Zhao Zhiqiang, Senior Lecturer, NYP-Microsoft Center for Applied AI (C4AI), School of Engineering, Nanyang Polytechnic
Dr. Zhao Zhiqiang is an expert in Artificial Intelligence, serving as the instructor and module leader for "Machine Learning" and "Applied Deep Learning." He has more than 20 year’s teaching experience in Computational Intelligence, Digital Manufacturing and Artificial Intelligence. He has led several AI grant projects as a principal investigator and published numerous papers in prestigious journals and conferences. Dr. Zhao is also an editorial board member of Engineering and Applied Sciences (EAS) and Industrial and Manufacturing Engineering (IME), contributing significantly to the fields of engineering and AI. Dr. Zhao holds a PhD from National University of Singapore, Master in Engineering and Bachelor in Engineering from Xi’an Jiaotong University.
Trainer's Profile:
Christopher Thia, Senior Lecturer, NYP-Microsoft Center for Applied AI (C4AI), School of Engineering, Nanyang Polytechnic
Chris is a senior lecturer in C4AI and instructor for Generative AI Series. He has more than 15 year’s teaching experience in both PET & CET training. He has facilitated workshops on applying Large Language Models (LLM) for question and answering. Chris strives to make complex concepts accessible to others. One notable project under his guidance involved the application of large language models for information retrieval, showcasing a commitment to practical problem-solving. Christopher holds certifications in AWS Academy Cloud Foundations and NVIDIA Deep Learning, Msc from NUS and Bachelor of Engineering from NTU.
