Data Science and Analytics MSc

Program Overview

Program Overview

Data Science and Analytics MSc

The Data Science and Analytics MSc is part of the Computer Science and Engineering and Data Science and Informatics department.

Program Overview

This course addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course stretches the artificial intelligence (AI), machine learning (ML) and decision science themes to business intelligence, data science and business analytics.

Attendance and Fees

• Attendance: Part-time day, Full-time
• UK Fees: £1,225 (Price per 20-credit module)
• International Fees: £1,985 (Price per 20-credit module)

Course Structure

Core Modules

• Business Analytics This module is a self-contained unit in applied statistics and operational research (OR) for decision making. It covers the essentials of descriptive, predictive and prescriptive analytics in an application-driven manner.

Data Mining and Machine Learning

This module provides an overview of modern techniques in machine learning and data mining customised for data science applications.

MSc Project

The project consolidates and extends the knowledge students acquired in the taught part of the course, encouraging and rewarding individual inventiveness and application of effort.

Data Warehousing and Business Intelligence

This module teaches students how to build Data Warehouses by understanding their structures and the concept of multi-dimensional modelling.

Data Visualisation and Dashboarding

This module covers the theoretical and practical aspects of data visualisation, including graphical perception, dynamic dashboard visualisations, and static data ‘infographics’.

Option Modules

• Web and Social Media Analytics
• Simulation Modelling
• Data Repositories Principles and Tools
• Big Data Theory and Practice

Entry Requirements

• A minimum of a lower second class honours degree (2:2) in a scientific or engineering discipline with some exposure to the use of IT.
• If you do not have a formal qualification, but you are already in employment, you may be considered if your role involves the data mining and decision support techniques and technologies deployed in the course.

Assessment

• The graphs below give an indication of what you can expect through approximate percentages, taken either from the experience of previous cohorts, or based on the standard module diet where historic course data is unavailable.
• Changes to the division of learning time and assessment may be made in response to feedback and in accordance with our terms and conditions.

How You’ll Be Taught

• Teaching methods across all our postgraduate courses focus on active student learning through lectures, seminars, workshops, problem-based and blended learning, and where appropriate practical application.
• Learning typically falls into two broad categories: Scheduled hours and Independent study.

How You’ll Be Assessed

• Our postgraduate courses include a variety of assessments, which typically fall into two broad categories: Practical and Coursework.

Supporting You

• Study support – workshops, 1-2-1 support and online resources to help improve your academic and research skills
• Personal tutors – support you in fulfilling your academic and personal potential
• Student advice team – provide specialist advice on a range of issues including funding, benefits and visas
• Extra-curricular activities – volunteering opportunities, sports and fitness activities, student events and more

Research Groups

• Our research achieves real-world impact and we are proud to claim a rich and diverse profile of high-quality research and knowledge exchange in a wide range of disciplines.
• Find out more about the following research group related to this course:
  • Centre for Parallel Computing
  • Health and Social Care Modelling Research Group

Contact Us

Please refer to the university's website for contact details.

Program Outline

The program blends artificial intelligence (AI), machine learning (ML), and decision science themes with business intelligence, data science, and business analytics. The program aims to equip students with the skills and knowledge to develop solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data. Students will gain a deep understanding of the underlying models and techniques, as well as the impact of technological advances on data science, business intelligence, and analytics. The program emphasizes two key themes:

Technology and Application:

Students will develop skills in the use and application of various technologies, architectures, techniques, tools, and methods for data science, including data warehousing and mining, distributed data management, and appropriate AI and ML techniques.

Algorithms and Quantitative Techniques:

Students will enhance their knowledge of algorithms and quantitative techniques, including AI, ML, and Operational Research (OR), suitable for analyzing and mining data and developing decision models in a broad range of application areas.

Outline:

The MSc in Data Science and Analytics program is structured as follows:

• Core Modules (5):
• Business Analytics:
This module covers applied statistics and operational research (OR) for decision making, laying the foundation for more advanced modules in data mining, optimization, and simulation modeling. It focuses on descriptive, predictive, and prescriptive analytics in an application-driven manner, utilizing software tools like Excel and R. Students will be introduced to toolkits like R and Python and explore the features and strengths of different machine learning and data mining methodologies using selected datasets related to specific public sector or business application domains.
• MSc Project: This module consolidates and extends the knowledge acquired in the taught part of the course, encouraging individual inventiveness and application of effort.
Students will carry out a comprehensive piece of individual work on an approved topic relevant to their course of studies, involving research, planning, critical evaluation, and reflection activities. The module includes a series of four blended learning workshops to provide foundational knowledge for project development. The focus is on Data Warehouse design, multi-dimensional modeling, the integration of multi-source data and analysis, cloud-based data warehousing, NOSQL OLAP, aiming to support better business decision making. Tools like R and Tableau are used to prepare students for becoming data visualization specialists. The aim is to equip students with the necessary technical skills and industrial knowledge for a career in web or social media marketing.
• Simulation Modelling: This module focuses on the choice and use of appropriate simulation modeling approaches to treat real-world problems, developing solutions using powerful simulation software and explaining the business and industrial implications thereof.
Relevant applications to problems such as stock control, reliability, project management, and service redesign will be considered in domains such as healthcare, supply-chain, and transport. It addresses practical issues related to data modeling and database design and provides practical skills by introducing the features and constructs of SQL.

Assessment:

Modules are typically assessed through practical coursework, which may also include an in-class test.

Teaching:

Teaching approaches include lectures, tutorials, seminars, and practical sessions. Students will also learn through extensive coursework, class presentations, group research work, and the use of a range of industry-standard software such as R, Python, Simul8, Palisade Decision Tools, Tableau, and Oracle.

Careers:

• The program is based at the Cavendish Campus in central London, offering students access to state-of-the-art science and psychology labs and refurbished computer suites.
• The program provides students with opportunities to attend presentations from industry professionals and go on site visits to see the work of data science and analytics teams.
• The program offers a Westminster Employability Award, which allows students to formally document and demonstrate their personal and professional development activities and achievements.
• The program provides access to free online courses in Adobe and Microsoft Office applications, as well as thousands of specialist courses on LinkedIn Learning.

We do not increase your tuition fees each year. We do not increase your tuition fees each year. We do not increase your tuition fees each year. This opportunity is available if you have a personal tuition fee liability of £2,000 or more and if you are self-funded or funded by the Student Loans Company.Find out more about paying your fees.