100% online MSc Computer Science with Data Analytics
Credits:
180
180
Two years, part-time
£8,640
£8,640
World-class Russell Group member
University of the Year shortlisted (The Times and Sunday Times Good University Guide 2022)
100% online - study from anywhere
Six starts per year
Pay-per-module
Total programme cost: £8,640
Next start: 09 January 2023
Be in demand. Be in Data Analytics.
Data is being collected at unprecedented speed and scale, becoming an ever-increasing part of modern life. While ‘big data’ is big business, it is of little use without big insight. The skills required to develop such insight are in short supply, and the expertise needed to extract information and value from today’s data couldn’t be more in demand.
Our 100% online MSc Computer Science with Data Analytics programme is designed for working professionals and graduates who may not have an academic background in computer science or data analytics and want to start a career in this fascinating and lucrative field.
Request information here
What you’ll study
You’ll develop specialist practical skills and knowledge in machine learning, data analytics, data mining and text analysis via specialised modules and an independent data analytics project. You’ll also develop your core computer science skills such as computational thinking, computational problem solving and software development.
Our online programmes allow you to study around full-time work and home commitments, at different times and locations. This is your Masters degree, on your own terms, in your own time.
With six start dates a year, you’re not restricted to the traditional academic year and can begin your postgraduate study within weeks.
Advancing your career
In the UK alone, over 1.5 million people work in the digital sector, while the number of digital technology jobs has grown at twice the rate of other roles.
The postgraduate programme will help prepare you for a range of in demand roles in computer science, software development, programming, and data driven solutions. You will be able apply computational thinking, and apply current data and text analysis techniques such as machine learning in a range of business and academic settings.
Why York?
- Member of the elite Russell Group of major research-intensive universities
- Over 20,000 students and 4,000 staff from 150 countries
- Ranked joint 10th in the UK for the quality of research in the Times Higher Education
- 17th overall in the Complete University Guide 2023
- University of the Year shortlisted (Times Higher Education Awards 2023)
- University of the Year shortlisted (The Times and Sunday Times Good University Guide 2022)
Entry requirements for home and international students:
- 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:
- International English Language Testing System (IELTS): 6.5, with 6.0 in each component
- IELTS Indicator: 6.5, with 6.0 in each component
- TOEFL IBT (internet-based and special home edition): 87, with 21 in each component
- Trinity ISE: Level 3 with Merit in each component
- PTE Academic: 61, with 55 in each component
- Cambridge Certificate in Advanced English (CAE) and Cambridge Proficiency (CPE): 176, with 169 in each component
- GCSE: B / 6 or above
- Duolingo: 110, with 100 in each component
- LanguageCert B2 Communicator: High Pass with 33/50 in each component
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
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.
Big Data Analytics (15 credits)
This module provides data science 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.
Data Mining and Text Analysis (15 credits)
This module covers the concepts that underpin data mining and the algorithms and tools commonly used. It explores text processing, where linguistic theory, algorithms and techniques for computer-assisted text processing will be provided. You will have the opportunity to apply the tools and algorithms for data mining and text processing to a variety of data sets.
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 will also learn the principles, design and implementation of system software such as operating systems.
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.
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 will look at principles and patterns of software design, where to apply them, and how they inform design choices. 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.
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.