Introduction

This course is designed to introduce participants to the core principles and practices of Artificial Intelligence (AI) and Machine Learning (ML). AI and ML are technologies that enable machines to learn from data and experience, making decisions and predictions. AI and ML are utilised in various industries, including healthcare and finance, to enhance efficiency and accuracy. This course guides learners through key concepts such as AI, machine learning algorithms, neural networks, and data pre-processing.

Learning Outcome

By the end of this program, participants will be able to:

• have a strong grasp of the fundamental principles of AI and ML
• develop an awareness of the ethical implications and societal impacts of AI and ML
• acquire knowledge of the tools and libraries of AI and ML
• understand the structure and function of neural networks to construct learning models
• recognise the role of an organisation in building an AI-ready culture and mindset
• showcase their abilities in applying AI and ML concepts to solve real-world problems

Key Topics

Key topics include:

• Definition and foundation of AI and ML
• Overview of AI applications in various industries
• AI Search Algorithms
• AI Decision Making and Problem Solving
• Types of Machine Learning
• Introduction to Neural Networks and Types of Neural Networks
• Overview of Model Evaluation, Optimisation and Deployment Strategies
• Building Culture and Mindset with AI and ML
• Understanding ethical implications of AI and ML
• The Future and Emerging Trends in AI and ML

Duration

2 Days | 13 Hours

Target Participant

• 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 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:

• Lecture
• Instructor-Led Training
• Group Discussion
• Demonstration
• Case Study

Assessment Methods

Pre-Test & Post-Test

Program Evaluation