This module will address:

Theory & Knowledge Exchange

Core Components Hardware Logic & Number Systems Basic Networking Operating Systems (Windows, Linux, Mac) and Architectures (x86, Arm) Type 2 Virtualisation Cloud Computing - Resourcing and Offloading Maths operations

Technology & Resources

VMware Academy Microsoft Azure Dev Tools

Practical Content

Tutorial practical content reinforcing theory sessions and enabling hands-on demonstration of concepts.

CLASS-TEST: A Class Test assessing topics of the module related to main computer science principles as applied to Artificial Intelligence and Data Science & Informatics and testing student knowledge at applying these to several scenarios (Learning Outcome 1).

PRACTICAL: A case study will be provided to students that contains several problems to solve in relation to a final computing solution as applied to Artificial Intelligence and Data Science & Informatics. Students will need to combine theory and practical skills taught throughout the module. (Learning outcomes 2 to 4).

All teaching sessions will blend theory and practical learning. Students will be introduced to curriculum concepts and ideas and will then be able to apply theory to practical examples within the same sessions. In addition, students will be provided with a range of resources for independent study such as case studies, academic papers and industry stories. There will be a mixture of practical and theoretical formative (mock or practice) exercises which will help students build knowledge and confidence in preparation for summative (formal) assessment.

1. Be able to demonstrate a systematic understanding of Computer Science concepts and principles as applied to Artificial Intelligence and Data Science & Informatics

Knowledge & Understanding

2. Develop lines of argument and be able to evaluate possible approaches, tools, techniques, platforms, and solutions based on knowledge of underlying Computer Science concepts and principles as applied to Artificial Intelligence and Data Science & nformatics

Learning

3. Be able to develop appropriate questions and strategies to achieve a solution (or

identify a range of solutions) to a Computer Science based problem as applied to

Artificial Intelligence and Data Science & Informatics Problem Solving

4. Be able to apply Computer Science concepts, principles, and techniques, including

those at the forefront of the discipline to computing problems as applied to Artificial

Intelligence and Data Science & Informatics Application

Internet and Office software
VMware Software
Microsoft Azure Dev Tools

All texts and electronic resources will be updated and refreshed on an annual basis and available for students via the online Study Links resource platform. All reference materials will be collated and curated and aligned to Equality, Diversity & Inclusion indicators.

Core Text/Resource: Ledin, J. (2020). Modern Computer Architecture and Organization, Packt Publishing, 9781838984397 Mueller, S. (2015). Upgrading and Repairing PCs, 22nd Edition, Que, 9780134057729
Optional Text/Resource: Bhowmik, S. (2017), Cloud Computing, Cambridge University Press, ISBN-10: 1316638103 Portnoy, (2012) Virtualization Essentials, Sybex, ISBN 9781118176719

All resources will be updated regularly and available via a module KeyLinks online function

Students will learn about how devices and services relate and work together. In the module we will explore hardware, virtualisation and cloud systems enabling students to explore the different areas of technology within computing and identify core elements within the field to make an informed choice for purchasing, designing, and developing systems. In addition to these core skills students will further bolster their mathematical skills in order to apply them later in the course.