IPA

Introduction

This course is designed to equip participants with foundational knowledge and practical skills in applying machine learning (ML) techniques for data analytics. In response to the growing need for evidence-based decision-making and efficient public service delivery, the course introduces core ML concepts, tools, and workflows tailored to government use cases.

Learning Outcome

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

  • understand the fundamentals of machine learning and its role in data analytics
  • utilise beginner-friendly ML tools to process and analyse data
  • apply basic ML models to datasets
  • interpret ML outputs to support decision-making and policy recommendations
  • identify ethical considerations, data privacy requirements and limitations of ML

Key Topics

Key topics include:

  • Introduction to Machine Learning
  • Types of Machine Learning
  • Collecting, cleaning and transforming data for analysis
  • Machine Learning Models
  • Interpreting and Visualising Results
  • Ethics, Privacy and Governance in ML

Duration

 3 Days | 19.5 Hours

Target Participant

  • Senior Executive Services 1 (SES 1) – Grade A1 | A2
  • Senior Executive Services 2 (SES 2) – Superscale Special
  • Senior Executive Services 3 (SES 3) – Superscale A | B | C
  • Executive Services 1 (ES 1) – Bahagian I: Kumpulan 1 | 2 | 3
  • Executive Services 1 (ES 1) – Bahagian I: Kumpulan 1 | 2 | 3
  • Executive Services 2 (ES 2) – Bahagian II: B3 | B2
  • Executive Services 3 (ES 3) – Bahagian III: C3 | C2 | C1

Pre-Requisite

N/A

Language

English

Methodology

The course will be delivered using:

  • Interactive lectures
  • Case studies
  • Group discussion
  • Hands-on practical

Assessment Methods

Pre-Test & Post-Test

Program Evaluation

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