Full Time/Online Delivery with Scheduled Lectures
180 Credits
7 Modules
One Exam, Dissertation and Oral Defence
Study Materials/E-library
12 Months
September, January & June
This degree is awarded by the University of Greater Manchester and distance delivered by WINC.
The MSc Data Analytics and Technologies is an innovative and dynamic program designed to equip students with the necessary skills and expertise in data analytics. Students will learn how to analyse and interpret data, uncover valuable insights, and effectively communicate their discoveries. This programme combines specialised study in data analytics with essential training in high-level transferable skills.
The MSc Data Analytics and Technologies programme offers a comprehensive curriculum that equips students with the necessary technical skills and analytical capabilities to excel in the field of data analytics. Graduates will be well-prepared for a successful career in this rapidly growing field, as they will have the ability to make sense of complex data and effectively communicate their findings. By enrolling in this programme, students can become masters of their own career development, with the knowledge and skills to thrive in data analytics.
You should have at least a lower second class (2.2) honours degree (or equivalent) in a computing-related subject or five years of relevant work experience.
If English isn’t your first language, you’ll also need IELTS 6.0 with no less than 5.5 in any band (or equivalent). We also accept a range of other English language qualifications.
The University of Greater Manchester, based in Bolton, United Kingdom, is an esteemed institution dedicated to delivering excellence in education. With a rich history spanning over 190 years, the university is renowned for its rigorous academics, innovative teaching methods, and emphasis on practical skills development.
The University of Greater Manchester prepares students for their future careers by offering globally recognised programmes and a curriculum designed to meet industry demands. With a focus on practical learning and real-world applications, students graduate equipped with the knowledge and skills to make a meaningful impact in their chosen fields.
Learning and teaching methods apply a blended style. This may include lectures, seminars, tutorials and critiques, self-directed learning, e-learning and laboratory/workshop sessions, as well as online sessions and support. Practical skills are acquired through technical introduction and support, workshop sessions, demonstrations and activity-based assignments. Active learning is promoted with a strong practical theme, throughout.
The following modules will be covered in the MSc Data Analytics and Technologies degree course, carrying a total of 180 credits.
Credits: 20 – Module Type: Core
This module develops an understanding of the professional and legal constraints within which computing specialists operate. The module operates using a ‘discursive’ environment where you will be confronted with the social and ethical issues of using technology, considering both regional and global trends and perspectives. Skills learnt will include how to communicate your work effectively keeping in line with the process and standards to be adhered to as a Professional in Computing Field. The module helps to develop a mature attitude to working as an ethical, sustainability aware, computer or information systems professional as well as build upon your undergraduate research skills through the introduction and application of advanced techniques to support you in your professional practice. The following GAME+ attributes are covered in this module: Influence and impact, and Critical self-management.
Credits: 20 – Module Type: Core
This module allows you to develop skills, knowledge and techniques to improve your capabilities in research and to deal with complex issues systematically and creatively. This includes investigating processes to help evaluate and critically appraise both qualitative and quantitative research papers; identify, select and utilise different approaches to literature searching and review; identify appropriate epistemological and methodological approaches that will underpin your research design; and formulate and develop achievable research aims, questions and objectives. This module builds on previous learning focused on gaining insights from academic literature and formulating research project proposals. Knowledge gained in this module will be consolidated and extended in the capstone project module while writing the dissertation and preparing for your viva voce. The following GAME+ attributes are covered in this module: Influence and Impact, and Critical Creativity and Innovation.
Credits: 20 – Module Type: Core
This module aims at developing advanced knowledge and skills in data analysis and visualisation. The module will be delivered in a lab environment where sessions grounded in theory are underpinned by practical labs. These practical lab sessions leverage real-world data for analysis and visualisation using contemporary tools in the industry. This module builds upon previous learning focused on strategies for leveraging data for insight and innovation. Knowledge gained in this module will be consolidated across other modules in the programme and extended in the capstone project module depending on dissertation theme and area of specialisation. The following GAME+ attributes are covered in this module: Critical Creativity and innovation and Skills mastery.
Credits: 20 – Module Type: Core
This module covers the use of Big Data frameworks and Cloud technologies for effective manipulation and analysis of large data sets. Students will be exposed to core Big Data analytics concepts and models, contemporary technologies, as well as develop skills to structure and analyse structured, semi-structured, and unstructured data using Big Data tools such as Hadoop and Spark. This module builds upon previous learning focused on strategies for leveraging data for insight and innovation. Knowledge gained in this module will be consolidated across other modules in the programme and extended in the capstone project module depending on dissertation theme and area of specialisation. The student will able to perform CRUD operations and query relational and non-relational databases using SQL and NoSQL. The following GAME+ attributes are covered in this module: Influence and Impact, and Critical Creativity and Innovation.
Credits: 20 – Module Type: Core
This module introduces students to the principles, theories, and applications of data mining and machine learning techniques. Students will learn about different algorithms and techniques for analysing large datasets and building predictive models. The module will cover techniques for data preprocessing, feature selection, and model selection, as well as model evaluation and interpretation. The module will also address ethical considerations and current challenges associated with using data mining and machine learning techniques. This module builds upon previous learning focused on strategies for leveraging data for insight and innovation. Knowledge gained in this module will be consolidated across other modules in the programme and extended in the capstone project module depending on dissertation theme and area of specialisation. The following GAME+ attributes are covered in this module: Professional identity and Skills mastery.
Credits: 20 – Module Type: Offered
This module introduces students to the concepts of business analytics. students will learn the fundamentals required to analyse time series data, perform time series forecasting using various statistical, machine learning, and deep learning techniques. The module will also cover the optimisation techniques for problem solving. This module builds upon previous learning focused on strategies for leveraging data for insight and innovation. Knowledge gained in this module will be consolidated across other modules in the programme and extended in the capstone project module depending on dissertation theme and area of specialisation. The following GAME+ attributes are covered in this module: Professional identity and Skills mastery.
Credits: 60 – Module Type: Core
This module enables the demonstration of research capability and application of advanced technical knowledge relating to a relevant aspect of the subject pathway. Students first determine the theme of the project which is then evaluated by the assigned research supervisor to ensure that it meets the required academic standards before work is undertaken. This module requires significant use of academic skills and knowledge of research practice, which is crucial for investigating literature and presenting findings, determining appropriate research methodologies and methods, conducting research activity and presenting outputs. Ethics and professional practice is to be adhered to throughout the project. This module culminates with the submission of substantial dissertation and the verbal presentation of significant aspects of work in a viva voce, which is conducted to a professional standard. The following GAME+ attributes are covered in this module: Influence and impact, Critical self-management, Critical Creativity and innovation, Professional identity and Skills mastery.
As a graduate of this master’s degree, you’ll possess an impressive all-round combination of skills and knowledge. In addition to a strong theoretical and practical knowledge of data analytics and technologies, you’ll be able to demonstrate essential interpersonal and people skills, such as collaboration and team working, negotiation and persuasion. You’ll have a clear understanding of the contexts in which data analysts work, coupled with commercial awareness and business-relevant knowledge. You’ll also possess high-level academic skills in research, critical thinking and curiosity. Not only will all this help you become established early on in your career, but you’ll also be primed to take on leadership roles. Moreover, you’ll have the lifelong learning, problem-solving and decision-making skills needed to adapt to new challenges throughout your career.
