ITEC623 - Essentials of Artificial Intelligence and Machine Learning

Year

Credit points

Campus offering

Prerequisites

ITEC613 Introduction to Data Science and Machine Learning

Teaching organisation

150 hours over a twelve-week semester or equivalent study period

Unit rationale, description and aim

Data science is an inter–disciplinary concept that employs scientific methods, algorithms, tools and systems for extracting insights, knowledge and value from data. Machine learning, as a core part of data science or data analytics and a subset of artificial intelligence, is the scientific study of algorithms and mathematical models that computer systems use to make decisions or predictions. Machine learning algorithms and models are widely used in human’s digital life such as email client, search engine, social media, virtual personal assistant, or recommendation system, although machine bias is an important ethical concern of which many people are unaware. Python is one of the most popular programming languages or tools for putting data science and machine learning into practice. This unit will focus on practical aspects of data science and machine learning including python data science and machine learning libraries and tools, unsupervised and supervised machine learning, and machine learning applications in industry, while considering the issue of machine bias and how it may have an adverse impact on the common good, especially the poor or vulnerable. The aim of the unit is to learn fundamental concepts, key techniques and popular tools in machine learning to solve real–world data science problems.