Students using University computers

MSc Data Science and Analytics

Explore and analyse insights from data across industries, research institutions and the government

1 years Full Time, 2 years Part Time
Bognor Regis Campus

Top 25

UK University

1.National Student Survey 2021

Top 5

for courses and lecturers

2. WhatUni Student Choice Awards 2021

14th

for student satisfaction

3. Complete University Guide 2022

Overview

As the amount of data available to organisations grows, the science of gaining insights from this data grows with it.

Industry, research institutions and governments seek to extract value from data to improve products and services, serve their customers better, and run more operationally efficient organisations. This creates a growing need for skilled Data Scientists who use their mathematical, computational and presentational skills to mine data for value.

This MSc Data Science and Analytics degree will give you an essential understanding of the methods, tools and techniques you will use in your career as a Data Scientist and provide you with opportunities to apply your theoretical knowledge in practical situations.

You will complete a range of project work on this course to prepare you for the workplace. You will link your theoretical learning to real-world scenarios across a range of industry and government sectors and have the opportunity to decide the methods and tools best suited to the project based on your previous learning.

The course may be for you if you are:

  • a mathematics graduate who wants to use your skills in a vocational, business based environment
  • a computer science graduate wishing to follow a vocational route
  • an individual currently working in business and looking to grow your career through gaining Data Science and Business Analytics skills.

This course was designed in consultation with industry partners to ensure it reflects the current needs of businesses. The course focuses on the skills and experiences businesses need in their employees.

Teaching and Assessment

How you will learn

This course uses interactive lectures, self-learning, workshops and hands-on projects. You will be assigned an Academic Advisor from the start of your course who will work with you throughout your studies to help you reach your academic potential.

The Course

What you will study

The programme’s content emphasises practice (based on theory), which is underpinned by industry style projects and a focus on practical assessment tasks.

You will study a selection of core modules in each year. Each module is worth a number of credits and is delivered differently, depending on its content and focus of study.

This list is indicative and subject to change.

Select a year

Programming for Data Science

In order to collect, analyse, and present data, a data scientist should be able to understand algorithms for data processing, analysis and implementation in programming language and integrate them with existing software tools. This module covers the design, development and implementation of processing and analysis algorithms used in developing Data Science solutions.

Modern Database Systems

The storage, analysis, and systematic extraction of information from Big Data pose challenges that are too complex to be addressed by traditional databases. The module initially covers topics in traditional database systems then introduces the modern view of data processing for storage and retrieval of data from unstructured datasets.

Mathematics and Statistics

This module aims to cover the key mathematical and statistical concepts which are of fundamental importance to many topics within computing. Throughout the module extensive use will be made of real-world problems to highlight how the ideas and techniques covered can be practically applied.

Professional and Research Practice

The module aims to explore and develop professional and research skills, providing students with an in-depth understanding of the principles of critical thinking, appraisal of research methods, and critical literature review. The module also covers professional, legal, social and ethical issues involved in the sustainable exploitation of computing technologies.

Data Visualisation

The need to communicate effectively using the appropriate visualisation tools to reflect the trends or patterns in datasets is an essential skill for the data scientist. This module explores selecting and implementing appropriate visualisation tools and techniques and produces an effective analytical report. Various models and concepts behind visualising data are reviewed and applied in the Data Science context.

Deep Learning

This module is an introduction to the key deep learning methods which are widely applied in a variety of real-world problems, from healthcare to robotics.  In particular, this module focuses on the practicalities of how to build deep neural networks and deep learning frameworks such as Tensorflow or Pytorch. Throughout the delivery of this module numerous examples of applications will be used from image recognition, music generation and natural language processing.

Machine Learning

This module is an introductory course into machine learning methods which are of fundamental importance in the modern world. Many of the techniques covered in this module form the basis for the growth in artificially intelligent systems in recent years. In particular, we shall see how the different machine learning methods are applied in a variety of settings such as medical diagnosis, fraud detections, house price predictions and many more.

Advanced Topics in Data Science

This module explores a range of topics that are increasingly predominant and emerging in Data Science, Data-Intensive Computing, Parallel Computing and Natural computing. The topics will be explored through guided reading and research within a group project component. Students will learn to read academic papers and report on research papers dealing with various current topics in Data Science.

MSc Project in Data Science

The MSc Project provides an opportunity to investigate a problem, gap, or challenge within Data Science. The module provides the opportunity for students to examine an area of particular interest within the Data Science context. The module is designed to make a major contribution to the professional and intellectual development of students through enabling students to demonstrate their capacity for sustained independent thought, learning and critical reflection.

Facilities

Use industry standard equipment

Teaching takes place at the Bognor Regis campus and in our purpose-built and state-of-the-art Tech Park, giving you access to truly cutting-edge facilities.

The University of Chichester’s cutting-edge Tech Park aims to produce graduates with enterprise skills, creativity, technical knowledge and are equipped to enter the graduate workforce.

Our Engineering, Computing, Design and Creative & Creative Industries departments are also based in this building and have access to brand new equipment, machines and studios.

Careers

Where this degree could take you

This MSc Data Science and Analytics degree will give you a practical understanding of the issues relating to sourcing, curating, analysing and presenting data in business and other public sector and not-for-profit organisations.

When you graduate you will have transferable skills that will help you in the workplace. You could pursue a role in retail, banking, government or transport.

Course Costs

Course Fees 2022/23

UK fee
£9,000
International fee
£15,300

For further details about fees, please see our Tuition Fee page.

For further details about international scholarships, please see our Scholarships page.

University of Chichester alumni receive a 15% fee discount.

Entry Requirements

Typical offers (individual offers may vary):

Honours degree
2:2 or higher
IELTS
6.5
with no element lower than 5.5.

FAQs

Frequently asked questions

How do I apply?

Click the ‘Apply now’ button to go to our postgraduate application form.

When does this course start?

This course starts in September 2022.

Other questions

For more information contact Dr Mohammad Ali Javaheri Javid at m.javaherijavid@chi.ac.uk.

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