Postgraduate study
Computing & Web

MSc Artificial Intelligence

Artificial intelligence (AI) is increasingly important in developments in all parts of business and society. The School has active research groups in machine learning and intelligent systems, and AI related modules.

Course information

Full-time

  • within 1 year (September start), 16 months (January start) or 2 years with advanced practice (September or January start)

More full-time details

2019 entry

Part-time

  • Up to 3 years (can be completed in 2 years if preferred)

More part-time details

2019 entry

Contact details

Further information

  • Facilities

    Computing and Web

    Teesside has fantastic state-of-the-art facilities for web and computing students including a wide range of web, multimedia, network and programming studios. This environment prepares students for work in industry by promoting team work and the use of case studies, problem solving and methods such as peer programming.

 

The course gives you specialist skills in artificial intelligence, opening the door to a range of careers. You will develop strong theoretical and technical knowledge and skills including a thorough grounding in data analytics and specialist skills in artificial intelligence, which will provide the directly transferable skills for a career in the field of AI.

You will explore state-of-the-art technologies, concepts and theories, supported by a thriving active research community. You will develop specialist knowledge and experience in the development of intelligent systems. Topics studied will include machine learning, A I Programming, research and statistical methods and data analytics.The distinctive nature of the award is the close integration with our AI and Machine Learning research groups coupled with the opportunity for an internship and a highly supportive environment, particularly for international students.The course also provides you with directly transferable skills for a career in a range of industries from the finance sector to healthcare to automotives, as well as progression opportunities to PhD research

There are three routes you can choose from to gain an MSc Artificial Intelligence:

full-time - 2 years with advanced practice (September and January start)
full-time - 1 year (September start) or 16 months (January start)
part-time - 2 years.

Course structure

Core modules

Advanced Data Analytics

This module provides you with the core principles and practical skills to apply state-of-the-art computational methods to perform data analytics. The skills are very important in the new horizon of data analysis where existing massive amount of data contains valuable knowledge, which is critical for prediction and decision-making. Due to its characters (3V: volume, velocity, and variety), computational methods are required to extract such knowledge.

You form a solid foundation of 1) predictive analytics, 2) data-driven decision making which refers to tools and techniques for building statistical or machine learning models to make predictions and decisions based on data. Practical guidance about how to handle unlabelled, noisy, incomplete, large-scale data is discussed and you learn how to select the best technique to handle different type of data in different scenarios.

Intelligent Agents

This module examines knowledge-based artificial intelligence (AI), which is concerned with building and deploying logic-based inference, planning and decision making. The focus of knowledge-based AI has become increasingly interested in building intelligent agents – independent entities that perceive their environment and take actions to maximise the chances of achieving their goals. These agents range from simple, reactive forms to complex cognitive decision-makers, often residing in social spaces with other agents. You examine the tools and techniques used to engineer intelligent systems (agent-based and other) and present an in-depth study of key research and application areas of intelligent systems.

Intelligent Systems Programming

You examine modern approaches to building symbolic artificial intelligence (AI) inference mechanisms into software applications, contrasting simple reactive systems with those whose behaviours are plan-based and cognitive. The module has a strong practical underpinning investigating the semantics of Clojure: a modern functional and symbolic programming language for the java virtual machine. It builds on earlier studies of programming and algorithms to bridge the gap between theoretical understanding and implementation developing those advanced programming skills necessary to construct and evaluate knowledge-based AI software.

Machine Learning

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%).

Master's Project: Artificial Intelligence/ Data Analytics

Research Methods

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.

Statistical Methods

You develop necessary knowledge and practical understanding of the main statistical techniques. You explore quantitative and qualitative data analysis techniques, reflecting scientific and social science methods. You focus on correlation testing, regression, data categories, normalization - the tools needed, rather than the philosophical approaches. You understand how to apply valid techniques and interpret the results in preparation for experimental work.

Your assessment is a single ICA based around a number of case studies that require you to identify the correct data analysis and modelling processes.

 

Advanced practice

Internship

The internship options are:

Vocational: spend one semester working full-time in industry or on placement in the University. We have close links with a range of national and international companies who could offer you the chance to develop your knowledge and professional skills in the workplace through an internship. Although we cannot guarantee internships, we will provide you with practical support and advice on how to find and secure your own internship position. A vocational internship is a great way to gain work experience and give your CV a competitive edge.

Research: develop your research and academic skills by undertaking a research internship within the University. Experience working as part of a research team in an academic setting. Ideal for those who are interested in a career in research or academia.


 

Modules offered may vary.

Career opportunities

In recent years, careers in artificial intelligence (AI) have grown significantly to meet the demands of digitally transformed industries. There are plenty of jobs in artificial intelligence, however coupled with that is a significant shortage of top tech talent with the necessary skills, ie there will be a skills shortage in this field leading to increased demand for talented individuals with this skillset.

Careers in AI include business intelligence developer, data scientists, AI developer and big data engineers.

Throughout your course we offer a wide range of business networking opportunities for you to extend your knowledge of the industry and show case your skills, enhancing your opportunity of securing your dream job. We host events such as:-

ExpoTees our end of course showcase of graduate work which attracts over 150 business partners each year, these are businesses who are looking for the emerging talent in the digital fields.

Drawing on our extensive industry links we invite guest speakers in your field to present to our students. Throughout your course we bring in industry speakers to ensure that you develop your knowledge of the industry that you plan to build your career in. In addition to covering technical subjects these speakers provide an insight into what employers are looking for in their employees, from technical to professional skills.

Entry requirements

You will normally have a first degree in related discipline (2.2 minimum) or relevant experience or equivalent qualifications.

In addition, international students will require IELTS 6.0 or equivalent.

For additional information please see the entry requirements in our admissions section

International applicants can find out what qualifications they need by visiting Your Country

Course information

Full-time

  • within 1 year (September start), 16 months (January start) or 2 years with advanced practice (September or January start)

More full-time details

2019 entry

Part-time

  • Up to 3 years (can be completed in 2 years if preferred)

More part-time details

2019 entry

Contact details

Further information