The Artificial Intelligence with Computer Science degree will enable you to provide solutions to real-world problems that require the acquisition and representation of information, knowledge and intelligence within computerised processes, which form the basis for intelligent computer systems powered by Artificial Intelligence.
Entrants develop skillsets particular to pattern identification, the modelling of processes or actions associated with those patterns and the utilisation of machine learning techniques that automate this process alongside mainstream computing topics that form a foundation for working with AI.
The development of the Artificial Intelligence with Computer Science degree is rooted in the knowledge and experience of Computer Science and Artificial Intelligence (CSAIP) research unit members, their experiences with collaborative projects spanning over twenty years and feedback from past and present students relating to their educational experience and preferences associated with delivery of Artificial Intelligence.
What you will study
The Artificial Intelligence with Computer Science degree is structured around six main themes, or pillars, that are developed through year of study, specifically:
Mainstream programming tailored to producing software solutions that encompass artificial intelligence and their foundations:
- Year 1: Introduction to Programming
- Year 2: Agent Based Systems
- Year 3: Robotics and Autonomous Systems
Logic programming and machine learning approaches rooted in the understanding and application of methods, tools and packages appropriate to a general audience:
- Year 1: Logic Programming and Knowledge Representation
- Year 2: Intelligent Decision Support Systems
- Year 3: Machine Learning and Natural Intelligence
Information system and database development that ultimately leads to the application of Data Science techniques for the mining of information:
- Year 1: Information Management, Assurance and Security
- Year 2: Database Development
- Year 3: Data Mining
Computer System Concepts that address hardware, software, operating systems and networking:
- Year 1: Computer System Concepts
- Year 2: Operating System Concepts
- Year 3: Computer Networks
Project work that allow for the development of management, planning, development and review of solutions developed in teams and individually:
- Year 1: Immersive Learning Team Project
- Year 2: Professional Practice and Employability Team Project
- Year 3: Individual Project
Mathematical foundations for computational intelligence and computer science:
- Year 1: Mathematical Tools for Computation
- Year 2: Computational Mathematics
Teaching
This undergraduate computing course is delivered in a traditional format.
Full-time students will typically spend 12 hours in classes and 24 hours outside of classes each week.
If you choose to study part-time, this is reduced to around six hours each week. You will study through lectures, tutorials, practical sessions, seminars and projects.
You will need to spend a significant amount of time working independently, reading and preparing for assessments.
Assessment is primarily by coursework, varying from a research-style paper or essay to practical assignments. You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.
Assessment
Assessment is primarily by coursework, varying from a research-style paper or essay to practical assignments to presentations and team based project work.
You will also work on a significant research project of your own choice, where strong independent thinking, critical analysis and project management skills will be important.
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