Enquire now Apply now

MSc Data Science and Analytics (Online)

Book an open day Apply now

Why choose Herts?

Our MSc in Data Science and Analytics builds on our extensive experience in data science research and KTP projects. The modules are prepared and taught using delivery methods that have been tested throughout our long-term provision of the field.
The course focuses on the exciting fields of machine learning, designing and developing data mining applications, and studying, understanding, and applying data analytics in big data and cloud computing fields.
The mode of delivery and assessments is problem solving based, combining real-life scenarios with a reflective learning experience, aimed at developing the highest level of problem solving and data analytic skills.

For admission to the MSc Data Science and Analytics (Online):

a recent good honours degree (or equivalent) in computer science or cognate discipline;
applicants whose first language is not English must demonstrate sufficient competence in English to benefit from the programme. This is normally demonstrated by recognised awards equivalent to an overall IELTS score of 6.0 candidates who do not satisfy these requirements will be considered on a case-by-case basis.

Supporting documents required

copies of the front and back of your undergraduate degree transcript and certificate
curriculum vitae
English language qualification certificate (you should have a score of 6.0 overall if presenting an IELTS test)
a substantial personal statement about why you want to study this programme, what you hope to gain from the course and where you see your future development taking your career
a copy of the photo page of your passport
one academic or professional reference.

Find out more about international entry requirements

See what system requirements are needed for online study

View our simple steps to a successful application (PDF - 0.17 Mb)


Institution code	H36
School of study	School of Physics, Engineering and Computer Science
Course length	Online - Full Time, 16 Months Online - Full Time, 1 Years Online - Part Time, 3 Years
Location	University of Hertfordshire, Hatfield

Employability

Careers

Our online masters programme is designed to give you the up-to-date skills and knowledge sought after by employers, whether in business, industry, government or research.

The MSc Data Science and Analytics course will equip students with the knowledge and practical skills in data science and analytics from the foundations of data science, data mining, machine learning, to big data analytics.

Successful graduates may pursue a career as a data scientist or data engineer, data analytics consultant, digital marketing manager across a wide range of sectors.

About the course

The MSc in Data Science and Analytics utilises our strong international reputation for research in these areas. The expertise of our staff influences this course which explores current research and practice in data science and analytics, extending your knowledge and understanding of the principles and practice of obtaining data from various sources, the essential methods for pre-processing and cleaning data, data analytics and modelling especially in big data analytics.

Why choose this course?

Find out more information about how online study works, funding and how to apply.

One of a range of advanced courses within our postgraduate Master's programme in Computer Science, this particular course provides you with a specialism in Data Science and Analytics.
Advanced topics studied include mathematics and programming of data science, data mining, machine learning, and big data analytics.
You will gain an internationally recognised master's degree from the UK's University of Hertfordshire.
Flexible online learning allows you to fit study around your other commitments, without travel and accommodation costs.
You will be taught by a highly regarded and long-established computer science department.
Benefit from the same academic standards and quality control procedures as our equivalent on campus course.

What will I study?

Our online MSc programmes are taught 100% online through the University’s virtual learning environment, Studynet. Assessment is by coursework and online tests.

You will receive learning materials, take part in discussions and submit your assignments online. Additionally, you will receive study resources such as key e-books and any specialist software. You will have access to the University's extensive online library facilities, or be able to visit in person if you so choose.

The amount of study time required is no different from that needed for an on campus programme. You should expect to spend at least 30 hours per week if studying full-time, and in proportion if part-time.

Where will I study?

Learn in our brand-new School of Physics, Engineering and Computer Science building, opening in 2024, where you’ll experience a range of experiential learning zones.

The computer science labs are home to telecommunications, robotics and UX empathy labs, with a variety of research spaces that range from dark rooms to clean rooms, and sample prep labs to calibration and assembly labs.

You will also benefit from a Success and Skills Support Unit, which is aimed at helping you build your employability and academic skills. Plus, have access to industry mentors who will provide you with pastoral support, vocational guidance, and career progression opportunities.

The new building will also provide space to collaborate, with plenty of workshops, social and meeting spaces available. Even better, the building has been designed with the University’s net zero carbon target in mind, and forms part of our plan to replace or upgrade older sites that are energy inefficient.

Level 7

Module	Credits	Compulsory/optional
Big Data Analytics (COM)	15 Credits	Compulsory
As part of this module, students will explore principles and applications of big data analytics. Indicative topic modules includes: types of big data; source of big data; big data mining; the analytic tools for big data management; big data applications; measurement; and standards and ethics in big data.
Data Mining (COM)	15 Credits	Compulsory
In general, data mining techniques are used in organisations which collect data. This module will cover various data mining algorithms for discovering hidden knowledge, unexpected patterns, and new rules from data. Potential applications include market analysis and management (target marketing, customer relation management, market basket analysis, cross selling, market segmentation), risk analysis and management (forecasting, customer retention, quality control, competitive analysis), fraud detection and management, text mining (news group, email, documents) and web analysis, etc.
Foundations of Data Science (COM)	30 Credits	Compulsory
This module will include a study of a selection of topics centred around basic mathematical concepts and skills. For example: basic linear algebra, calculus, basic statistics, probability and fundamentals of Bayesian inference, basic set theory and information theory and instantiating some of the mathematical foundation as computational techniques. Actual topics taught may vary from year to year.
Machine Learning (COM)	30 Credits	Compulsory
As part of this module, students will engage with a selection of research topics centered around machine learning including supervised and unsupervised learning, data mining, bio computation, evolutionary algorithms, data visualisation, and neural networks as models of brain function in health, disease and development. Topics covered are likely to vary from year to year to reflect contemporary research.
Responsible Technology (COM)	30 Credits	Compulsory
This module is concerned with legal, social, ethical and professional issues that may affect the work of practitioners in the computing and technology sectors. Its main focus is on the ethical considerations inherent in the development of responsible technologies. Topics covered are likely to vary from year to year to reflect contemporary research and issues.
Data Science and Analytics Masters Project (COM)	60 Credits	Compulsory
The project is a show piece opportunity for students to demonstrate what they know about current research and practices in computer science and show off their skills in applying their skills in a range of computer science topics in order to conduct a practical investigation of a particular computer science problem. The project is a self-directed piece of work, conducted with minimum supervision that demonstrates the student's ability to plan and manage a substantial piece of work, and steer their own efforts. Students are expected to be thorough in their work, and, particularly, identify and tackle any difficult or challenging aspects of the problems they are trying to solve. It is not just the quantity, or even the quality of work that is considered when grading the project, but the level of difficulty and the scope of the problem being addressed.

Further course information

Course fact sheets
MSc Data Science and Analytics (Online)	Download

Programme specifications
MSc Computer Science (Modular) On-Line/Tutored E-Learning	Download

Additional information
Sandwich placement or study abroad year	n/a
Applications open to international and EU students	Yes

Student experience

At the University of Hertfordshire, we want to make sure your time studying with us is as stress-free and rewarding as possible. We offer a range of support services including; student wellbeing, academic support, accommodation and childcare to ensure that you make the most of your time at Herts and can focus on studying and having fun.

Find out about how we support our students

You can also read our student blogs to find out about life at Herts.

Funding and fees
Other financial support

Find out more about other financial support available to UK and EU students

Fees 2023
UK Students

Full time
- £9900 for the 2023/2024 academic year
Part time
- £825 per 15 credits for the 2023/2024 academic year
EU Students

Full time
- £9900 for the 2023/2024 academic year
Part time
- £825 per 15 credits for the 2023/2024 academic year
International Students

Full time
- £9900 for the 2023/2024 academic year
Part time
- £825 per 15 credits for the 2023/2024 academic year
*Tuition fees are charged annually. The fees quoted above are for the specified year(s) only. Fees may be higher in future years, for both new and continuing students. Please see the University's Fees and Finance Policy (and in particular the section headed "When tuition fees change"), for further information about when and by how much the University may increase its fees for future years.

View detailed information about tuition fees

Read more about additional fees in the course fact sheet

2023

Start Date	End Date	Link
21/09/2023	30/09/2024	Apply online (Distance (Full Time))
18/01/2024	31/01/2025	Apply online (Distance (Full Time))
21/09/2023	30/09/2024	Apply online (Distance (Part Time))
20/01/2024	31/01/2025	Apply online (Distance (Part Time))

2024

Start Date	End Date	Link
21/09/2024	30/09/2025	Apply online (Distance (Full Time))
18/01/2025	31/01/2026	Apply online (Distance (Full Time))
21/09/2024	30/09/2025	Apply online (Distance (Part Time))
20/01/2025	31/01/2026	Apply online (Distance (Part Time))

MSc Data Science and Analytics (Online)

Why choose Herts?

Supporting documents required

Careers

About the course

Why choose this course?

What will I study?

Where will I study?

Further course information

Student experience

Other financial support

Fees 2023

UK Students

Full time

Part time

EU Students

Full time

Part time

International Students

Full time

Part time

2023

2024