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Short Course

Advanced Large Language Models Approaches

Programme ScheduleDuration (days)Mode of DeliveryProgramme Code
To be advised3Classroom LearningTGS-2024044129

Course Overview

This course offers a deeper understanding of Large Language Models (LLMs) and their significance in industry transformation. Engage with renowned models like GPT3.5/GPT4.0/LlaMa2, and discover their core applications.

Learn to tailor these LLMs to business needs and industry context. Additionally, grasp the nuances of orchestrating multiple LLMs using LangChain and integrating Embedding Databases to incorporate
business-specific data.

This course targets professionals, business analysts, and forwardthinking executives keen on applying LLMs-specific business contexts, and seamlessly integrating Embedding Databases for enhanced datadriven decision-making. Ideal for those looking to stay at the forefront of AI-driven business solutions.

Course Objectives

At the end of the course, participants will be able to:

  • Understand Large Language Models (“LLMs”) and popular models like ChatGPT/GPT3.5, LlaMa2 in terms of their architecture, key functionalities, and design considerations
  • Customise and fine-tune ChatGPT/GPT4.0 and other LLMs for different business objectives and industrial context
  • Gain insights into the functionality of an Embedding Database and integrate it into an LLM setup to provide access to business-specific data
  • Understand architecture patterns for deploying LLMs-based services.

Prerequisites

Minimum diploma with basic ICT knowledge and basic programming knowledge.

You are recommended to take Python Programming to fulfil the prerequisite.

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This programme is part of

  • Professional Certificate in Enterprise Deployments and Applications for Large Language Models

    • Types of Available Fundings

  • SkillsFuture Funding
  • SkillsFuture Credit
  • Enhanced Training Support
  • SFEC

    • Instructors


    Dr Ai Xin

    Dr Ai Xin

    Dr Ai Xin is currently a Lecturer with the School of Computing at the National University of Singapore (NUS). She has many years’ experience teaching Artificial Intelligence and Data Science courses such as machine learning, deep learning and data mining. She graduated from NUS with a PhD degree in Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks. She worked at BHP Billiton Marketing Asia for eight years, gaining extensive industry experience in various functions such as risk management, supply chain management, and sales and marketing planning.

    Programme Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old
    or younger    		 40 years old
    or older
    Full Programme Fee S$2,850.00 S$2,850.00 S$2,850.00 S$2,850.00 S$2,850.00
    Less: SSG Grant Amount S$1,995.00 S$1,995.00 S$1,995.00 S$1,995.00 -
    Nett Programme Fee S$855.00 S$855.00 S$855.00 S$855.00 S$2,850.00
    9% GST on Nett Programme Fee S$76.95 S$76.95 S$76.95 S$76.95 S$256.50
    Total Nett Programme Fee Payable, Including GST S$931.95 S$931.95 S$931.95 S$931.95 S$3,106.50
    Less Additional Funding - S$570.00 - S$570.00 -
    Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes S$931.95 S$361.95 S$931.95 S$361.95 S$3,106.50
    1. Total Nett Programme Fee Payable, including GST, after additional funding from various funding schemes.
    2. Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
    3. The applicable funding is for Singaporeans and Singapore PRs. This is subject to change and in accordance with SSG funding guidelines as of course commencement.

    NUS Computing, Advanced Computing for Executives (ACE)

    11 Research Link
    COM 3, #B1-07
    Singapore 119391

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