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BSc (Hons) Data Science and Artificial Intelligence

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UCAS code: 
I400
Institution code: 
S82
Location: 
Ipswich

Duration: 

Three years full-time.
 

Introduction

It is estimated that we currently produce over 2.5 quintillion bytes of data every single day. This data includes over 94 million photos and videos shared on Instagram, over 306 billion emails and over 5 million Tweets. In the last two years alone, an astonishing 90% of the world’s data has been created. Our BSc (Hons) Data Science and Artificial Intelligence degree has been designed to provide you with everything you need to be able to find meaning in this data as a successful data scientist.

In the first year of the degree, you will gain a solid foundation in data science, artificial intelligence, programming, networks and computer systems. In the second year, you will have the opportunity to create a substantial software product that incorporates software design, implementation and testing. You will also undertake the degrees core research skills module in preparation for your final year project and dissertation. During the final year of your degree, you will complete your final project and dissertation. For this, you will be assigned a supervisor who is familiar with your chosen topic. You will also study advanced modules in data science, artificial intelligence, cyber security and distributed systems preparing you for a career as a data scientist.

Throughout the degree, you are also encouraged to attend an extensive range of seminars and events provided by guest lecturers with backgrounds in technology, business and academia. These same experts often provide real-world briefs for module assessments allowing you to undertake a project specified by industry to meet an organisation’s real needs.

Course modules

Platforms (Requisite)

This module covers the principles of computer systems, hardware components, the essence of operating systems, and relevant computing-related mathematics. It will provide the foundational underpinning to enable students to progress deeper into the disciplines of computing and networking, and a grasp of the history of computing, recent developments and its possible future

Networking Overview (Requisite)

This module introduces the concepts of communications and networking. It explores the Open Systems Interconnectivity (OSI) 7-layer reference model and TCP/IP Routing Suite (the 5-layer Internet reference model). TCP/IP is the model which is most commonly deployed in the majority of modern-day networks.

Introduction to Programming (Requisite)

This module introduces the concepts of programming and a modern programming language. Through programming practical’s, students will become fluent in structured programming constructs, procedural programming and object-oriented programming.

Operating Systems (Requisite)

This module will introduce the concepts of operating systems, including their structure, memory and storage management, protection and security. Designed with software developers in mind, it will look closely at real-world operating systems such as Windows and UNIX.

Introduction to Artificial Intelligence (Requisite)

This module introduces the exciting field of artificial intelligence, covering the history of the discipline and exploring a variety of “classical AI” topics. It then studies the tasks involved in addressing problems involving communication, perception and action, preparing the way for techniques developed in later modules.

Python Programming for Data Science (Requisite)

This module will cover Python programming with particular emphasis on using Python to solve problems with artificial intelligence and data science techniques. No programming experience will be assumed. The module will begin with the key elements of Python programming and build towards harnessing the standard Python libraries and packages to create solutions.

Software Design, Development and Engineering (Requisite)

The module seeks to provide students with the opportunity to produce a complete, substantial software product that incorporates elements such as software design, implementation, testing and the production of documentation suitable for end-users as well as advanced engineering topics.

Introduction to Relational Databases (Requisite)

Database systems, particularly those based on the Relational Database Model, play a significant role in the world of Information Technology. This module provides essential knowledge and appreciation of the role of relational database systems, including basic principles and practice of design, implementation and development for both system designers and software engineers. It will include practical exercises in Structured Query Language (SQL).

Computing Research Skills, Professional Practice and Ethics (Mandatory)

Research skills are an essential set of capabilities in the toolkit of a computing professional. In this module, students will develop knowledge and understanding of the purpose, processes, methods (surveys, experiments, interviews, case studies, etc.), analysis (qualitative and quantitative), and outputs of research and will be able to apply them. This module also delves into the professional, legal and ethical standards and guidelines that inform and guide best practice in business and computing.

Data Mining (Requisite)

Data science includes many techniques for classification, analysis and prediction. This module focuses on those techniques relating to data mining and statistically driven approaches. These techniques also have the advantage of being “explainable AI”, more so than deep learning approaches, and some are long established techniques of “business intelligence”.

Data Structures, Algorithms and Advanced Programming (Requisite)

This module focuses on data structures (e.g. linked lists, trees, heaps, hash tables, etc), algorithms (sorting, searching, dynamic programming, greedy, graph, geometric, cryptographic, string matching and compression algorithms, etc), and advanced programming techniques and other language paradigms.

NoSQL Databases (Requisite)

Industry, commerce and research are being transformed by the potential to capture, store, manipulate, analyse and visualise data and information on a massive scale. The advent of Big Data with its variety, velocity and volume disrupted the way we store and manage data. During this module you will learn NoSQL approaches to data modelling, database design and manipulation.

Project and Dissertation (Requisite)

This is a major project in a specialist area of computing, addressing a specific real-world business or research issue, suggested by the student, an employer or a staff member. Projects may be undertaken individually or in groups if the problem topic supports a team approach.

Neural Networks and Deep Learning (Requisite)

A sufficiency of inexpensive computing power, sufficiently large datasets and a number of key theoretical advances created deep learning techniques which have facilitated a wave of accuracy increases across many computational tasks (computer vision, natural language processing, speech recognition, autonomous driving, etc.), making many applications practical. Deep learning is central to modern artificial intelligence. This module explains the underlying mathematics and techniques and how to use them to achieve similar feats of computational accuracy.

AI and Data Science Applications (Requisite)

This module provides an opportunity to explore in greater depth several areas of artificial intelligence and data science. This will include an understanding of the domain theory, typical problems faced in the domain and how these might be solved.

Distributed Systems (Requisite)

This module provides a systematic understanding of distributed operating systems, software services and applications in terms of their architectures, functionality and behaviour. It includes case studies on the “Internet of Things” and cloud computing as well as topics on parallel programming.

Cyber Security: Attack and Defence (Requisite)

On one hand, this provides insights into the mindset of cyber attackers, a secure understanding of the ethics and legal issues in this area, and knowledge and skills in attack technologies and techniques. On the other hand, this module provides a detailed knowledge and understanding of the techniques and tools available to a security professional, and the practical skills in selecting, evaluating, designing, implementing and deploying defences to protect vulnerable software, networks and systems.

Career opportunities

Upon graduation from this degree, students can progress into a range of roles, including:

• Data Scientist
• AI Expert
• Data Analyst
• Data Engineer
• Machine Learning Engineer
• Data Architect
• Business Analyst

Fees and finance

Full-time tuition fee: £9,250 p.a.
International tuition fee: £11,790 p.a

Entry requirements

112 UCAS tariff points (or above)
BBC (A-Level) DMM (BTEC)

Staff

Professor of Information Systems Engineering

Lecturer in Computing

Lecturer in Computing

Associate Professor and Course Leader in MSc Games Development

Facilities and Resources

Specialist modules in data science, artificial intelligence and cyber security may take place in the DigiTech Centre at Adastral Park, which was unveiled by Her Royal Highness the Princess Royal on 12th November 2019. A collaboration between University of Suffolk and BT, with funding from the New Anglia Local Enterprise Partnership (LEP), it has been established to provide training in cutting-edge digital skills for people looking to pursue careers in the nationally-important information and communications technology (ICT) sector, as well as fuelling high tech businesses who increasingly require access to a talented technology workforce. A regular bus operates from the university to Adastral Park (bus route H66) with the average journey taking only 15 minutes.