There is high demand for specialists who can extract insights and value from data. These insights inform everything from marketing activities to government strategy, transforming business and society. This integrated master’s degree provides you with a strong basis in computer science alongside specialist skills to analyse complex data sets. This degree is suitable for those who would like to develop creative computational solutions to derive the data-intensive transformation that is reshaping the way our society operates. It will build your foundational skills within computer science, such as algorithmic thinking and programming, and develop the specialist data scientists skills needed for the extraction of actionable insight from complex data collections. You should have a strong interest in technologies that produce and analyse data and will need to develop computational solutions for the acquisition and analysis of data, and use creative problem-solving skills to extract knowledge that can answer challenging questions in a domain of investigation. Data Science is a multidisciplinary domain that requires training in a wide-range of skills from programming to visualisation, to data analysis. The demand for data scientists in the UK has grown more than ten-fold in the past five years *. This programme aims to equip you with both strong foundational computer scientist skills and specialised data scientist skills. This powerful combination of computing and analytics will provide you a skill set that will be widely applicable not only within the computing industry but also in various application domains, from retail to health. This skill set will be widely applicable within the computing industry and in various other sectors including retail and health, making our graduates highly employable. - Acquire leading-edge knowledge, skills and techniques required by the data science profession - Become proficient in a broad range of programming languages and software design techniques - Work with and learn from active researchers in machine learning, high-performance computing and data visualization - Apply your knowledge and skills to develop solutions in data-intensive sectors where insights can deliver commercial advantage or social benefit - Access excellent work experience opportunities at nearby Tech City.

Year 1 Study our common first year for all our computer science students, learning six core topics including operating systems, web development and Java. - Computation and Reasoning (15 Credits) - Mathematics for Computing (15 Credits) - Systems Architecture (15 Credits) - Programming in Java (30 Credits) - Databases and Web Development (30 Credits) - Operating Systems (15 Credits) Year 2 Deepen your knowledge of computer science with core modules such as C++ and data structures. Boost your professional skills with a team project and a work-based project. - Data Structures and Algorithms (15 Credits) - Language Processors (15 Credits) - Object-Oriented Analysis and Design (15 Credits) - Professional Development in IT (15 Credits) - Team Project (30 Credits) - Programming in C++ (15 Credits) - Computer Networks (15 Credits) Year 3 Build your data science skill set with five core modules and three elective modules, including principles of data science, and AI. - Computer Vision (15 Credits) Principles of Data Science (15 Credits) - Introduction to AI (15 Credits) - Programming and Mathematics for AI (15 Credits) - Agents and Multi Agents Systems (15 Credits) - Games Technology (15 Credits) - Advanced Databases (15 Credits) - Theory of Computation (15 Credits) - Advanced Games Technology (15 Credits) - Professional Experience (Placement) Placement Reports (30 Credits) - Data Visualization (15 Credits) - Digital Signal Processing and Audio Programming (15 Credits) - Advanced Programming: Concurrency (15 Credits) - Functional Programming (15 Credits) - Cloud Computing (15 Credits) - Information Security Fundamentals (15 Credits) - User Centred Systems (15 Credits) - Semantic Web Technologies and Knowledge Graphs (15 credits) The one year placement can be undertaken following successful completion of year 3 and will be required to last for a minimum of 9 months. Year 4 Develop professional data science expertise with five core modules, including big data and visual analytics. Showcase your knowledge with a data-intensive individual research project. - Neural Computing (15 Credits) - Machine Learning (15 Credits) - Big Data (15 Credits) - Visual Analytics (15 Credits) - Information Retrieval (15 Credits) - Individual Project (45 Credits) - Software Systems Design (15 Credits) - User-Centred System Design (15 Credits) - Digital Signal Processing and Audio Programming (15 Credits) - Advanced Programming: Concurrency (15 Credits) - Advanced Algorithms and Data Structures (15 Credits) - Cloud Computing (15 Credits) - Computational Cognitive Systems (15 Credits) - Advanced Games Technology (15 Credits) - Semantic Web Technologies and Knowledge Graphs (15 credits)

"Most modules are assessed with examinations and coursework. Details can be found in the individual module specifications. Typically, modules are mainly assessed through written examination, and coursework also contributes to module assessment. The written examinations will contain theoretical questions, including mathematical aspects, as well as writing and analysing small amounts of code and small essays on the applications of computational techniques. As you move over to the more specialised modules as part of your Programme Stage 3 and Programme Stage 4, you will be expected to demonstrate how well you can synthesise various pieces of knowledge and be also assessed on how well you can critically reflect on the solutions you are suggesting. The balance of assessment by coursework (assessed essays and assignments) unseen examinations and a final year project will to some extent depend on the optional modules you choose. Year 1 Written examination: 41% Coursework: 59% Year 2 Written examination: 35% Coursework: 65% Year 3 Written examination: 24% Coursework: 76% Year 4 Written examination: 35% Coursework: 65%"

Professional Bodies are not listed for this Course.

26 January This is the deadline for applications to be completed and sent for this course. If the university or college still has places available you can apply after this date, but your application is not guaranteed to be considered.

Course code: G102

Institution code: C60

Campus Name: City, University of London

Campus code:

The following entry points are available for this course:

Year 1

Entry Requirements for Advanced Entry are not listed for this Course.

We do accept applications from students who are completing a combination of qualifications. For this course, this would be something like: D* in IT with a grade B in ‘A’ Level Computer Science and a grade B in another ‘A’ Level. We may also take ‘AS’ Level grades into consideration.

Please click the following link to find out more about qualification requirements for this course

Minimum Further Information are not listed for this Course.

Test	Grade	AdditionalDetails

English Language Entry Requirement Information are not listed for this Course.

Student satisfaction : 74%

Employment after 15 months (Most common jobs): 70%

Go onto work and study: 85%

Additional Fee Information are not listed for this Course.

Northampton Square
Address2 are not listed for this Course.
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City of London
EC1V 0HB