About the course | Learning Outcome

The main objective of the course is to share the practical hands-on and knowhow on LLM solution deployment in different industries.

After the course the students are able to understand:

• How to develop the AI chatbot system and the corresponding monitoring workflow with high accuracy and performance
• How to deploy local and private LLM solution in Cloud platforms such as AWS and Azure
• How to deploy AI agents for business automation with Langchain framework and local LLM
• How to improve the accuracy of the LLM solution with RAG and fine tuning techniques

Dive into “Business Automation with LLM”—where you will explore the basic and advanced concepts of AI agents and LLMs, their architectures, and practical applications. Transform your understanding and skills to lead in the AI revolution.

This course is perfect for developers, data scientists, AI enthusiasts, and anyone wanting to be at the forefront of AI agent and LLM technology. Whether you want to create AI agents, perfect their automation, or sell tailored solutions, this course provides you with the comprehensive knowledge and practical skills you need.

Students who have participated the course with good learning achievement will be offered part time development exposure in real life AI projects.

What you’ll learn

1. Overview of Al solutions

– Overview of Al/ML

– Use cases of Al solutions in different industries

– Setup of tools

2. Prompt engineering

– Setup and use of ChatGPT or PoE

– Prompt engineering

– Exercises of prompt engineering

3. Use of Azure Openai API with Python

– Python basic

– Use of Azure openai API

4. Case study: Deploy AI Chatbot with Azure openai and Telegram

– Setup telegram bot

– Deploy Al chatbot with Telegram

5. Document searching and data analyze engine with Langchain and local LLM

– Langchain and Llamaindex

– Ollama

6. Multiple data sources query and analyze engine with Langchain and local LLM

– Langchain

– Ollama

– SQL DB

7. Deployment of web interface with Python

– Deploy web interface with flask and python

8. Deploy LLM solution in Cloud solutions

– AWS Could solutions

9. Fine tuning of LLM solution

– Fine tuning technqiues

10. Evaluation of LLM solution

– How to evaluate the accuracy of LLM solutions

– Security measure of LLM solutions

This course includes

Date: 2025/04/23 – 2025/06/25

Time: 19:00-22:00 (Subject to confirm before the course)

Location: Hong Kong (Subject to confirm before the course)

Total: 30 hours – offline face to face teaching

Learning Materials: Hands-on articles,  downloadable resources

Certificate of completion

Requirements