100% online MSc Computer Science with Artificial Intelligence
Credits:
180
180
Two years, part-time
£8,160
£8,160
World-class Russell Group university
16th in UK (THE World University Rankings 2021)
100% online - study from anywhere
Six starts per year
Pay-per-module
Total programme cost: £8,160
Next start: 10 January 2022
Be in demand. Be in artificial intelligence.
Artificial intelligence and machine learning is becoming ubiquitous. It is everywhere, from recognising you in a photo, giving you advice about your next purchase, to assisting in medical diagnosis. Employer demand for skills in this area remains high. According to the job search site Indeed, the number of job postings for jobs featuring ‘AI’ or ‘machine learning’ increased by 100% between 2015 and 2018.
The 100% online MSc Computer Science with Artificial Intelligence has been designed for ambitious professionals and graduates who do not have an academic or professional background in computer science or artificial intelligence and who want to launch a career in this highly skilled, in-demand and lucrative field. It is also suitable for professionals who have experience in computer science and are looking for a Masters qualification to enhance their credentials.
The online delivery of this Masters programme means that you can study and complete it from anywhere in the world, with no need to attend campus. The flexible design means that you can fit your studies around work and family commitments.
Request information here
What you’ll study
On this Masters programme, you’ll develop the core computer science skills of computational thinking, computational problem solving and software development. Importantly, you’ll also develop specialist skills and knowledge in problem structuring, machine learning, neural networks, genetic algorithms, and data analytics, and undertake an independent artificial intelligence project.
Advancing your career
The programme will help prepare you for a range of in demand roles in computer science, software development, programming, and AI oriented solutions development. You will be able to apply computational thinking, generate solutions using current AI techniques, such as genetic algorithms and neural networks in a range of business and academic settings.
Why York?
- Part of the elite Russell Group of major research-intensive universities
- Ranked Top 20 in the UK (THE World University Rankings 2021)
- Top 150 in the world (THE World University Rankings 2021)
- Over 20,000 students and 4,000 staff from 150 countries
- Ranked 10th for research impact (Times Higher Education’s ranking of the most recent Research Excellence Framework)
Admission requirements:
You should normally have, or be about to complete, a 2:2 undergraduate degree (or equivalent qualification).
Alternatively, we would accept a Masters degree (or equivalent).
- 2:2 (or equivalent) undergraduate degree in any subject
- Or Masters degree (or equivalent) in any subject
- Students whose first degree was not taught in English should have an appropriate English language qualification
- If you earned your degree outside the UK, check that it is equivalent to a 2:2. Our country-specific pages can help you to find out more
- If English isn’t your first language you may need to provide evidence of your ability, such as:
- IELTS: 6.5, with no less than 6.0 in each component
- PTE: 61, with no less than 55 in each component
- CAE and CPE (from January 2015): 176, with no less than 169 in each component
- TOEFL: 87, with a minimum of 21 in each component
- TOEFL iBT Special Home Edition: 87, with a minimum of 21 in each component
- Trinity ISE: level 3 with Merit in all components
- Duolingo – 110, minimum 100 in all other components
You need to have completed the test within two years of the start date of your programme. You cannot combine scores from more than one sitting of the test.
- You will not need to provide evidence of your English language abilities:
- If you’re from a specified majority English-speaking country
- If you’ve completed a degree in English in a specified country within two years of your intended start date
Successful completion of this course will require you to access widely used software and university systems. Please speak to our enrolment advisers for more information on this.
Modules
Artificial Intelligence and Machine Learning (15 credits)
This module explores the field of artificial intelligence along with the principal ideas and techniques in three core topic areas: problem solving, knowledge representation and machine learning. The implications of AI for business and society are also covered.
Applied AI (15 credits)
This module explores advanced AI techniques through the application and evaluation of genetic algorithms, neural networks, local search techniques and deep learning. It develops your understanding of the application areas and problems that advanced AI techniques can enhance and optimise.
Algorithms and Data Structures (15 credits)
This module provides techniques for using algorithms and associated data structures. It also covers computational thinking and the theoretical underpinnings and practical applications of computer science, covering: programming; control structures; methods; inheritance; arrays and mechanics of running and testing; and complexity and implementation of algorithms in programs.
Advanced Programming (15 credits)
This module details advanced programming concepts such as file manipulation, event-driven programming, multi-threaded programming, programming for data analysis and the use of packages and documentation. It also covers the social context of computing: social impact of computers and the internet; professionalism; codes of ethics and responsible conduct; copyrights, intellectual property; and software piracy.
Computer Architecture and Operating Systems (15 credits)
The module covers the concepts of modern computer architecture and system software. After an overview of computer architecture, it then delves into how computer systems execute programs, store information, and communicate. You’ll also learn the principles, design and implementation of system software such as operating systems.
Computer and Mobile Networks (15 credits)
A sound understanding of internet architecture, protocols and technologies and their real-world applications forms the core of this module. Discussions around networks and the internet, network architecture, communication protocols and their design principles, wireless and mobile networks, network security issues and networking standards feature. The module also covers related social, privacy and copyright issues.
Software Engineering (15 credits)
This module focuses on designing and building software systems. You’ll look at principles and patterns of software design, where to apply them, and how they inform design choices. You’ll learn techniques for ensuring systems you build behave correctly. We demonstrate how the application of these principles makes it possible to evolve systems effectively and rigorously.
Big Data Analytics (15 credits)
This module provides skills in data analytics, including the preparation of data, data handling, formulating precise questions and using tools from statistics and data mining to address them.
Research Methods (15 credits)
This module provides you with a range of approaches to research and individual research projects. Formulate research questions appropriate to an area of interest, and evaluate the relationship between question, methodology and method.
Research Proposal (15 credits)
This is an extended research proposal for your final Individual Research Project. The module is created to ensure you are prepared for the IRP in sufficient depth before undertaking final studies. Designed to give you the flexibility of developing a proposal, it explores a work-based problem or one that is driven by your own findings.
Individual Research Project (30 credits)
The 30-credit Individual Research Project (IRP) builds on your Research Project Proposal, defining and developing a plan for research within a particular field of your choice. The IRP is the implementation and write-up of these results. A self-study module, you’ll draw on skills acquired throughout the degree, including self-management, deadlines and subject knowledge.