Course Overview

Domain
Business, Communication and Design
Infocomm Technology
Format
Short Course
Duration
2 days
Fee Subsidy
Up to 90% SF Funding
Professional Development Units

CPD (CPA) – Pending approval

Artificial Intelligence (AI) and Machine Learning (ML) are reshaping accounting and finance by automating complex tasks and enhancing data insights. This course explores their applications in financial analysis, reporting, and forecasting.

The first day of the course covers the fundamental AL and ML concepts specific to accounting and finance, focusing on their relevance and potential applications, as well as their benefits and challenges. Learners will be introduced to Python and key machine learning algorithms, including regression, classification, clustering, and text analysis.

The second day focuses on prompt engineering, where learners will be trained to design and refine specific text prompts to guide Large Language Models (LLMs) such as Dify.AI, POA, ChatGPT and Google Bard. This expertise will allow accountants to effectively use AI tools for financial analysis, forecasting and reporting. Learners will gain hands-on experience in Python, generating code through prompt engineering to implement effective machine learning models in their accounting work.

In this 2-day course, learners will acquire practical skills in prompt engineering and machine learning algorithms for accounting applications. They will learn to integrate these concepts into their AI and ML projects, optimising model performance to achieve more accurate and relevant outcomes in their financial tasks.

Programme Partner

This course is supported and endorsed by CPA Australia.

CPA Australia

Who Should Attend

  • Professionals in the fields of accounting, audit and finance
Prerequisites
  • Basic accounting or finance knowledge
  • No prior coding knowledge and experience is required

What You Will Learn

  • Fundamental concepts of Artificial Intelligence (AI) and Machine Learning (ML) and their applications in accounting and finance
  • Benefits and challenges of implementing AI and ML technologies in financial contexts
  • Hands-on experience with Python programming for data manipulation and visualisation
  • Practical application of Python in financial scenarios, including stock price predictions and profitability analysis
  • Introduction to prompt engineering techniques to guide Generative AI (GenAI) outputs effectively
  • Application of AI and ML techniques for cash flow analysis, forecasting, and internal control evaluations

Teaching Team

Chu Mui Kim
Chu Mui Kim

Associate Professor, Business, Communication and Design, Singapore Institute of Technology

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Arif Perdana
Arif Perdana

Associate Professor, Monash University

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Phoebe Gao
Phoebe Gao

Assistant Professor, Business, Communication and Design, Singapore Institute of Technology

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Schedule

Course Run Dates Time
July 2025 run TBC 9:00 am – 6:00 pm
    Time Topics
    9:00 am - 6:00 pm

    Introduction to Artificial Intelligence (AI) and Machine Learning (ML)
    This session will introduce learners to the fundamental concepts of AI, including generative AI and ML, and their applications in accounting. Learners will explore how these technologies automate routine tasks, identify patterns in data sets, make predictions and generate insights while discussing the associated benefits and challenges.

    Introduction to Python
    Learners will gain practical skills in Python programming, a widely used programming language in machine learning. They will have hands-on practice with Python, to perform data crunching and visualisation.

    Applying Python in accounting and finance
    This session will delve into financial market data, learn about data structure and explore basic and nonlinear Python models such as linear regression and panel regression.  Learners will understand the latest trends in financial modelling and interpretation of machine learning research results. They will also apply Python in accounting and finance scenarios such as stock price and return prediction, ratios and profitability analysis.

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    Time Topics
    9:00 am - 6:00 pm

    Prompt engineering
    Prompt engineering involves designing text prompts to guide GenAI in generating coherent, relevant, and accurate outputs. In this session, learners will explore the fundamentals of GenAI, learn to apply prompt engineering techniques, and understand the ethical concerns and importance of responsible usage.

    Hands-on practice in generating Python codes from prompt engineering
    In this session, learners will use prompt engineering to generate Python code for data visualisations and analysis. Learn to work with popular machine learning algorithms such as regression, classification, and clustering to address accounting related tasks.

    Applying Python and prompt engineering in accounting and finance
    Learners will explore how to design clear, concise, and specific prompts to leverage Python in accounting and finance tasks. Learn to generate insightful outputs, including cashflow analysis, forecasting, internal control evaluations, and net present value models.

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    Certificate and Assessment

    A Certificate of Participation will be issued to participants who

    • Attend at least 75% of the course
    • Undertake and pass non-credit bearing assessment during the course

    Fee Structure

    The full fee for this course is S$2,398.00.

    Category After SF Funding
    Singapore Citizen (Below 40) S$719.40
    Singapore Citizen (40 & Above) S$279.40
    Singapore PR / LTVP+ Holder S$719.40
    Non-Singapore Citizen S$2,398.00 (No Funding)


    Note: All fees above include GST. GST applies to individuals and Singapore-registered companies.

    Course Runs

    There are no upcoming course runs at the moment.

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    Frequently Asked Questions

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      What coding skills do I need for this programme?

      No programming skills are required for this programme.

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