KV6015 - Data Analytics

What will I learn on this module?

This module will give you an essential foundation to focus on how to conduct statistical analysis and interpret various measures correctly. You will learn to think about the process of examining data from the “ground up”, adopting pragmatic approaches e.g., how to investigate and explore data, data structures and visualisations.

‘Data Analytics’ will prepare you for the study of the computational principles, methods, and systems for extracting and structuring knowledge from data. It will also prepare you for the application and use of those principles. For example, large data sets are now generated by almost every activity in science, society, and commerce - ranging from molecular biology to social media, from sustainable energy to health care. You will explore methods to conduct efficient and pragmatic approaches to ensure you have translational skills.

During ‘Data Analytics’ you will work through a series of exercises, making use of Northumbria’s state-of-the-art computer labs. Your learning will be research-rich by providing you opportunities to link with active research groups tackling real world problems to prepare you for life beyond Northumbria. The main element in assessment (100%) will be a final assignment that will bring together all your new skills and techniques.

How will I learn on this module?

You will learn through lectures, workshops, and independent learning. The lectures will cover theories and concepts that will enable you to tackle a series of guided exercises. You will work on these during workshops and hands-on sessions in Northumbria’s CIS building computer labs, which are fully equipped with the latest industry-standard software.

Outside class contact time, you are expected to read research papers, conduct research in relevant areas and if possible pursue research publications based on your implemented creative research work. Guidance on accessing online or library resources will be given by the module team. In addition, outside class time, student volunteers may also have opportunities to be involved in the evaluation of e.g., PhD projects as testing subjects (i.e., you will be guided by the module team on how to work with any PhD student and their project to further your data analytical skills). There may also be an opportunity to apply your data analysis skills to a live academic research project led by a member of the teaching team.

Inquiry-based learning is used throughout the module.

How will I be supported academically on this module?

The module team will guide and support you in the lecture and workshop practical sessions. During the lectures, you will be required to conduct interactive activities based on the lecturers’ guidance. The module team will prepare diverse examples of real-life applications to support you in learning approaches to data analytics. The module team will work closely with you in the practical sessions to conduct discussions and provide further detailed guidance on the subjects covered.

You can also request appointments with the module teaching team outside of scheduled class time to ask questions and seek advice.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

What will I be expected to achieve?

Knowledge & Understanding:

ML01. Demonstrate critical understanding of foundations and principles of data analytics.
ML02 Demonstrate knowledge of mathematical concepts that underpin data analytics techniques.
ML03. Demonstrate deep knowledge of fundamental statistical methods, techniques
and applications in data analytics.

Intellectual / Professional skills & abilities:

ML04. Critically assess, select, and apply data collection and cleaning, visualization, statistical inference, predictive modelling, and decision making for statistical analysis in the context of applied data analysis problems.

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
ML05 – Critically evaluate the choice of data science techniques and tools for particular

How will I be assessed?

Summative assessment
The module will be assessed by two assignment components, a data analysis process (e.g., code) described and presented with a 4000-word report (100%). All work to be undertaken individually.

For the assignment, you will practise the knowledge and skills learnt from this module by investigating and analysing a known data set from a list of given topics. This will assess MLOs KU1, KU2, KU3, IPSA34 and 5.

The assignment includes a report on research into e.g., the data and analytics used. The report will mainly assess your ability to present research work and your knowledge of relevant techniques and topics. It will assess MLOs KU1, KU2, KU3, KU4, PVA1, PVA5.

You will be provided with written, electronic, feedback for each of the summative assignments.

Formative assessment and feedback
The exercises in the practical sessions provide opportunities for formative assessment, helping you and your tutors to assess your progress. You will receive guidance and ongoing feedback on your work and progress verbally in lab sessions.

You will also have the opportunity to discuss your progress and the needs of the summative assessment informally in the practical class sessions.





Module abstract

This module introduces you to the theory, principles and practice behind data analytics. During the semester long delivery of this module you will be exposed to a range of topics, including but not limited to: mathematics, statistics, business intelligence systems, research methods, data mining techniques, and clinical informatics. Theory is followed by practical workshops where you will be introduced to different software kits as well as guided exercises to ensure you become comfortable/familiar with adopting data analytics processes in your own work. You will apply the acquired theoretical and practical knowledge in building a substantial individual analytical project to ensure your work is addressing real world problems. You will have weekly contact with the academic team to ensure some continuous assessment with feedback during workshop tasks. The structure of the module will encourage you have good communication and pragmatic skills to aid your personal and professional development and employability factor.

Course info

UCAS Code G411

Credits 20

Level of Study Undergraduate

Mode of Study 3 years Full Time or 4 years with a placement (sandwich)/study abroad

Department Computer and Information Sciences

Location City Campus, Northumbria University

City Newcastle

Start September 2024 or September 2025

Fee Information

Module Information

All information is accurate at the time of sharing. 

Full time Courses are primarily delivered via on-campus face to face learning but could include elements of online learning. Most courses run as planned and as promoted on our website and via our marketing materials, but if there are any substantial changes (as determined by the Competition and Markets Authority) to a course or there is the potential that course may be withdrawn, we will notify all affected applicants as soon as possible with advice and guidance regarding their options. It is also important to be aware that optional modules listed on course pages may be subject to change depending on uptake numbers each year.  

Contact time is subject to increase or decrease in line with possible restrictions imposed by the government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors if this is deemed necessary in future.


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