Course Description
Data is the foundation of Artificial Intelligence (AI) and effective decision-making. The quality, availability, and management of data directly influence the accuracy and reliability of AI-driven solutions. Public sector organisations increasingly rely on data analytics to improve service delivery, enhance operational efficiency, and support evidence-based decision-making. This programme introduces participants to the principles of data collection, data management, and analytics techniques required to support AI adoption and digital transformation initiatives.
Course Objectives
The objectives of the course are to enable participants to:
- • understand the role of data in Artificial Intelligence and digital transformation.
- • understand fundamental concepts of data collection, processing, and management.
- • identify appropriate data sources and collection methods.
- • understand the importance of data quality, accuracy, and reliability.
- • apply basic data analysis techniques to support decision-making.
- • understand how analytics contributes to AI applications.
- • recognise ethical, privacy, and security considerations in data handling.
- • promote data-driven approaches within their organisations.
Learning Outcomes
By the end of this course, participants will be able to:
- • explain the relationship between data, analytics, and AI.
- • identify different types of data and data sources.
- • understand the stages of the data lifecycle.
- • apply basic techniques for preparing and analysing data.
- • interpret data insights to support organisational decisions.
- • recognise challenges related to data quality and governance.
- • understand responsible use of data for AI applications.
Topics covered:
- • Introduction to Data and Artificial Intelligence
- • Data Collection and Management
- • Data Quality and Preparation
- • Introduction to Data Analytics
- • Applying Analytics for AI and Public Sector Improvement
- • Data Ethics, Security and Governance