Computer Science MSc

Teesside University

You gain the foundational knowledge to study a wide range of AI applications and solutions, and are introduced to logic-based knowledge representation, reasoning, problem solving and algorithms, planning and AI applications.

You develop your ability to design and implement database, big data and analytics applications to meet business needs. A case study is used to follow the system development lifecycle. You develop a plausible application from inception to implementation for a real-world scenario. You investigate the issues and technologies associated with implementing and supporting large scale databases and the services that are needed to maintain and access a repository of data. Investigations are undertaken in a number of areas including big data, data warehouses, integrating legacy data, data management and approaches that support the modelling and visualisation of data for a range of use views.

You undertake a major, in-depth, individual study in an aspect of your course. Normally computing master's projects are drawn from commercial, industrial or research-based problem areas. The project involves you in researching and investigating aspects of your area of study and then producing a major deliverable, for example software package or tool, design, web-site and research findings. You also critically evaluate your major deliverable, including obtaining third party evaluation where appropriate. The major deliverable(s) are presented via a poster display, and also via a product demonstration or a conference-type presentation of the research and findings. The research, project process and evaluation is reported via a paper in the style of a specified academic conference or journal paper. The written report, the major deliverable and your presentation of the product are assessed. The project management process affords supported opportunities for goal setting, reflection and critical evaluation of achievement.

Machine learning is a subfield of computer science concerned with computational techniques rather than performing explicit programmed instructions. You build a model from a task based on observations in order to make predictions about unseen data. Such techniques are useful when the desired output is known but an algorithm is unknown, or when a system needs to adapt to unforeseen circumstances. You explore statistics and probability theory as the fundamental task is to make inferences from data samples. The contribution from other areas of computer science is also essential for efficient task representation, learning algorithms, and inferences procedures. You gain exposure to a breadth of tasks and techniques in machine learning. Assessment is an in course assessment (100%).

You develop android apps for smartphone and tablet devices to a professional standard. You explore the industry-standard development processes and tools used to build today's mobile apps. You are also informed by current industry practice, to plan and execute a successful software development project. Assessment is an in-course assignment. You design, plan and build a mobile app for a smartphone or tablet device using industry approaches. Your artefacts and decisions are assessed by a presentation with supporting materials.

You are given an intensive introduction to programming assuming little, if any, previous experience. You cover the principles of object oriented programming and event driven GUI (graphical user interfaces) systems using the Java Language. You are introduced to the fundamental skills required for mobile app and pattern driven development. Topics covered include: Object oriented concepts: classes, objects, methods, inheritance, polymorphism; Event handling and elements of the Swing GUI API; Software development using a source code editor and an IDE; Software design techniques, problem solving and algorithm development; Software documentation; Software testing and evaluation techniques. You are assessed by individual course work that requires you to produce a portfolio of practical and reflective work.

You gain the knowledge and skills to understand the research process in computing and digital media, and the necessary skills to undertake your masters project. You learn how to use and critically evaluate previous academic research, and to generate good evidence material to justify their professional practice. This involves you learning about different research strategies and data generation methods and how they fit into the development lifecycle and the evaluation of the user experience, the use of the academic research literature, and research ethics. Assessment involves you preparing a research proposal which can form the basis of your master's project.