Course Detail()

Software Installation and Laptop

As this class places strong emphasis on the hands-on experience, you will be working with data for the majority of the time in class. To optimise the learning experience, it is mandatory for all participants to be equipped with a laptop, pre-installed with Microsoft Excel 2021 or any latest version.

Artificial Intelligence (AI) and Machine Learning (ML) are transforming the landscape of accounting and finance, allowing professionals to derive deeper insights from data and make more informed decisions. This course is designed to introduce accounting and finance professionals to the foundational concepts of AI and ML, with practical applications using the familiar tool of Microsoft Excel. Participants will explore key AI/ML techniques, including data mining, anomaly detection, and predictive analytics, and learn how to integrate these into everyday workflows to enhance data-driven decision-making.

On the completion of this course, you will be able to:

Understand the fundamentals of AI and Machine Learning and their application in accounting and finance;
perform data mining and exploration tasks in Excel to uncover insights from financial data;
detect anomalies and patterns in financial transactions using Excel-based tools;
build and validate basic predictive models for practical use in finance, integrating advanced AI techniques like Natural Language Processing (NLP); and
apply Excel for practical AI/ML tasks, leveraging its capabilities for automation and insight generation in accounting and finance.

Programme Outline

Introduction to AI and Machine Learning in Excel

Overview of AI/ML concepts and terminology.
Understanding algorithms and Black Box AI.
Practical introduction to AI/ML tools in Excel.

Data Mining and Data Exploration

Basics of Data Mining in finance and accounting using Excel.
Data quality and the concept of "Garbage In, Garbage Out" (GIGO).
Tools for data exploration, including PivotTables and feature engineering.

Advanced Techniques: Anomaly Detection, Correlation Analysis, and NLP

Techniques for anomaly detection and correlation analysis in Excel.
Introduction to Natural Language Processing (NLP) and tokenization.
Applications of NLP in financial data analysis.

Predictive Analytics and Model Validation

Building simple predictive models using data mining techniques.
Feature engineering and model validation in Excel.
Practical examples and applications in accounting and finance.

Training Methodology

Facilitated learning which includes classroom or practical sessions in a workshop

Closing Date for Registration

1 week before programme or until full enrolment.

Intended For

Accountants and financial analysts who want to improve their data analysis and reporting efficiency
Finance managers and executives seeking to make better business decisions using AI and machine learning insights
Auditors and compliance officers keen to use AI and ML for fraud detection and compliance analysis.

Schedule & Fees

Testimonial

Funding

1] NTUC Union Training Assistance Programme (UTAP)

NTUC members enjoy 50% *unfunded course fee support for up to $250 each year when you sign up for courses supported under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025.

*Unfunded course fee refers to the balance course fee payable after applicable government subsidies. This excludes material fees, registration fees, misc. fees etc.

This course is approved for UTAP support for intakes conducted between 05 December 2024 – 31 March 2025.

As UTAP is given on calendar year basis, and calculated based on year of training taken, it cannot be accumulated.

Maintained paid-up NTUC membership before course, throughout course duration and at the point of claim and;
Course by training provider must be supported under UTAP and training must commence within the supported period and;
Unfunded course fee must not be fully sponsored by company or other types of funding
Unfunded course fee must be S$20.00 and above, and;
Member must achieve a minimum of 75% attendance for each application and sat for all prescribed examination(s), if any and;
UTAP application must be made within 6 months after course ends.

For more information on UTAP Funding and to submit for UTAP claims, please visit https://www.ntuc.org.sg/uportal/programmes/union-training-assistance-programme. Terms and conditions apply.

Programme Facilitator(s)

Understand the fundamentals of AI and Machine Learning and their application in accounting and finance;
perform data mining and exploration tasks in Excel to uncover insights from financial data;
detect anomalies and patterns in financial transactions using Excel-based tools;
build and validate basic predictive models for practical use in finance, integrating advanced AI techniques like Natural Language Processing (NLP); and
apply Excel for practical AI/ML tasks, leveraging its capabilities for automation and insight generation in accounting and finance.