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Professional Certificate

Professional Certificate in Enterprise Deployments and Applications for Large Language Models

Programme Structure


Programme NameProgramme ScheduleMode of DeliveryProgramme Code
Large Language Models Overview and Applications26 Aug, 27 Aug 2024 | 9am-5.30pmClassroom LearningTGS-2024044131
Advanced Large Language Models Approaches9 Sep, 11 Sep, 12 Sep 2024 | 9am-5.30pmClassroom LearningTGS-2024044129
Large Language Models in Production19 Sep, 20 Sep 2024 | 9am - 5.30pmClassroom LearningTGS-2024043312
Duration 7 days

Programme Overview

The Professional Certificate programme equips participants with the knowledge and skills to navigate the enterprise deployments and applications for Large Language Models (LLMs). Through exploration of LLMs like GPT, participants gain a comprehensive understanding of their capabilities, design considerations, and potential applications. The programme focuses on the practical use of these LLMs and seamless integration into production workflows using techniques like Retrieval Augmented Generation (RAG). Additionally, the programme fosters awareness of the strengths, limitations, and potential risks associated with implementing LLMs in real-world scenarios.

Programme Objectives

This Professional Certificate will equip learners with the following competencies:

  • Understand Large Language Models (LLMs) and popular models like ChatGPT/GPT3.5/4.0, LlaMa2 in terms of their architecture, key functionalities, and design considerations
  • Utilise ChatGPT/GPT4.0 and other LLMs-based services to improve individual knowledge work productivity in terms of analysis, summarisation, recommendations, brainstorming, fine-tuning of ideas, and role-playing.
  • Utilise ChatGPT/GPT4.0 and other LLMs-based services as a Coach, Critique, Copilot, Customer Success / Self Service, Companion, or “Cat” (aka conceivably cute characters) via good prompt engineering.
  • 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 a LLM setup to provide access to business-specific data
  • Gain knowledge of emerging architecture and design patterns of incorporating LLMs into production, eg. Retrieval Augmented Generation (RAG) using orchestration frameworks like Langchain
  • Appreciate the strengths, weaknesses, risks, constraints, ethics, safety, privacy, and governance considerations of ChatGPT/GPT4.0 and other LLMs

Job Role Readiness

It will prepare learners in the following job roles to perform their responsibilities more effectively. It will also prepare learners for the following job roles:

  • Technology Executives
  • Managers
  • Developers
  • Programmers

Who Should Attend

This programme is designed for professionals and mid-career PMETs.

Prerequisites

Minimum of a diploma with basic ICT and programming knowledge.

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Contact Us  

Types of Available Fundings

  • SkillsFuture Credit

    • Instructors


    Dr Yeo Wee Kiang

    Dr Yeo Wee Kiang

    Dr Yeo Wee Kiang is a Senior Lecturer at the Department of Information Systems and Analytics in the NUS School of Computing, where he is dedicated to researching the use of technologies like Adaptive Learning and Large Language Models (LLMs) to create personalized and engaging computing education experiences. With a PhD from NUS focused on machine learning and data mining for pharmaceutical drug discovery, Dr Yeo brings practical industry experience as the former Director of Data Science at a food tech startup, where he led a team applying AI and machine learning to enhance nutritional value. His diverse background includes being an Adjunct Lecturer in the Department of Economics at NUS Faculty of Arts and Social Sciences, helming the Big Data Analytics module in the Master of Economics programme from 2019 to 2023, and teaching Python programming and data analytics at Nanyang Business School. Prior to his academic appointments, Dr Yeo was the Lead Instructor for Data Science at a New York-based commercial Continuing Education and Training (CET) provider, teaching aspiring adult learners in Hong Kong, Sydney, and Singapore. He also holds the WSQ Advanced Certificate in Training and Assessment (ACTA) from the Institute for Adult Learning Singapore. As part of the NUS ACE (Advanced Computing for Executives) teaching team, Dr Yeo specializes in technical training and practical computing education focused on data analytics, machine learning, and Python, aiming to equip professionals with in-demand Data Science skills.

    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.

    Tomithy Too

    Tomithy Too

    Tomithy invests with ST Telemedia – a global VC/PE fund which invests in Telcos, Data Centres, growth stage tech companies in the Artificial Intelligence, Cybersecurity and Cloud IT. As the technology investor, Tomithy actively works with target and existing portfolio companies on technical diligence, business strategy and commercial evaluation via their CTO, product & engineering teams. He is knowledgeable about enterprise software technology, trends and market dynamics in the US, China and Israel.

    He has a deep interest in governance and reliability of AI systems, generative AI, multi-agent AI systems, evolutionary algorithms and synthetic biology. Tomithy holds a degree in Computational Biology (Hons) from NUS, Masters in AI (SMU) and is currently pursuing a part-time PhD in AI Governance at SMU.

    Programme Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old or younger 40 years old or older
    S$2,174.55 S$844.55 S$2,174.55 S$844.55 S$7,248.50
    1. Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
    2. Participants must fulfill at least 75% attendance and pass all assessment components for all short courses within a professional certificate in order to be eligible for SSG funding.
    3. GST shall apply at prevailing rates.

    Connect with us

    11 Research Link
    COM 3, #B1-07
    Singapore 119391
    Telephone: +65 6516 5523
    Email: soc-ace@nus.edu.sg

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