Undergraduate DipHE

DipHE Data Science





Two year

Four year

Next enrolment

September 2025


In a nutshell

Data Science is a fast-growing interdisciplinary field which combines statistics, machine learning, Artificial Intelligence and data analysis to extract insights from data. This two-year course will introduce you to the fundamentals of Data Science and data analysis and give you practical experience working with industry-standard tools, systems and programming languages. Through problem-based learning, practical computer-based workshops and group activities, you will gain the skills and knowledge you need to succeed in industry.

What is a 'DipHE'? 

A Diploma of Higher Education (DipHE) at Level 5 is awarded after two years of full-time study at university. Our DipHE programmes are hands-on and practical, with flexible learning options available so you can choose to study full or part time.  

You can take a DipHE straight from college when you have completed qualifications like BTECs or A-Levels. Some people choose to take a gap year first or spend some time working before they start a DipHE.  

Diplomas of Higher Education are perfect for people who want a university experience, but do not want to take a full undergraduate degree qualification. You get the support and teaching quality of a degree but don’t have to commit to three years of study before you begin. A DipHE can lead directly to a career as you will have gained valued skills and experience, or you might choose to continue with further studies.  

This course is subject to approval

You will:

  • Be studying at a university with longstanding links in Data Science, giving you maximum employment and placeholder opportunities
  • Broaden your understanding of data science, machine learning and AI, some of the most 'in demand' skills in the modern economy
  • Gain experience using programming languages such as Python and SQL
  • Learn through hands-on exercises, group activities and live industry briefs, and work with messy, real-world datasets in realistic, problem-based scenarios
  • Build the practical skills you need for a broad range of career paths within data science and data analysis
  • Develop your skills using a wide-range of industry-standard tools for data visualisation, statistical analysis and Big Data analytics

This is for you if...


you are interested in finding out more about Artificial Intelligence, machine learning and Big Data


you have an enquiring mind, with a practical and analytical approach to problem solving


you enjoy working with data to spot patterns and trends or to solve problems

Course details

All about the course

Course Delivery

This course has been designed alongside our industry partners to ensure that it meets the needs of industry. Modules that make up the programme have been developed as new learning experiences bespoke to the course, which will give you a concentrated two-year experience to prepare you for employment or top-up study.

Find out more about the modules below. The structure reflects a two-year full-time route:

Year one

Introduction to Data Analysis with Python

In this module, you will be introduced to the Python programming language and will build your skills working with a range of Python libraries for analysing, manipulating and visualising data, including NumPy, Pandas, SciPy, Matplotlib and Seaborn. Based around practical exercises and challenges, this module will develop your problem-solving skills and proficiency in Python. This module will also focus on developing your computational thinking, challenging you to think like a computer scientist when tackling problems. 


This module will introduce you to relational databases and the fundamentals of Structured Query Language (SQL). In the first half of the module, practical workshops will introduce you to using SQL to query, extract and analyse data. In the second half, you will learn how to design a database and take into consideration issues such as data security, recovery and integrity.

Probability and Statistics

R is a widely used programming language in statistics, used to assess the governing company's financial performance, as well as other performance indicators, for example, patient outcomes for the NHS. You will undertake practical assessments from companies, evaluating statistical performance.

Data Visualisation

In this module, you will consider the importance of good data visualisation for communicating with data. You will learn the principles and theory behind data visualisation, best practices when visualising data and how to avoid misleading visualisations. Practical workshops will introduce you to industry standard tools for building data dashboards and reports and, across the module, you will create your own portfolio of dashboards and data stories.

Machine Learning

This module will introduce you to the core concepts of supervised and unsupervised machine learning, and how we can use machine learning to discover patterns in data and make predictions. 

The emphasis of the module is on practical application and you will use the Python programming language, and libraries such as Scikit Learn, to implement machine learning algorithms and build predictive models.

Introduction to Business Intelligence

This module sheds light on the use of business intelligence (BI) systems in organisational scenarios. The module will provide you with a broad set of skills applicable to the origins and evolution of BI systems, as well as distinctions between characters, data, information and knowledge.

Students will also learn about BI Systems, Data and Information, Problems with data, Data Warehousing, OLAP and Data Mining.

Year two

Artificial Intelligence & Deep Learning

Deep learning is at the heart of many of today's advances in Artificial Intelligence (AI). You will learn the theory behind neural networks and you will discover how deep learning is used within fields such as computer vision. Practical workshops will challenge you to build and train your own neural networks, working with a range of datasets of increasing complexity.

Professional Practices

The Professional Practices module will equip you with the research and professional skills required within industry. You will undertake team working used in the workplace, on real-world mathematics problems for which you will be required to develop a solution. You will also learn about the professional body, reflect on your skills and future direction with continuing professional development, and also take library-led courses on CV writing and soft skills development.

Big Data Analytics

In this module, you will learn the challenges and opportunities which characterise Big Data and will gain practical skills working with the tools and techniques used to process and analyse Big Data.

Text Mining and Natural Language Processing

In this module, you will learn the text mining techniques and methods used to analyse unstructured text and the latest deep learning approaches to Natural Language Processing (NLP). You will consider a wide range of applications, including text classification, document clustering, sentiment analysis and chatbots.

Data Science Project

In this module, you will use your data science and analysis skills to work with a complex dataset and solve a real-world business problem. You will synthesise the knowledge you have gained throughout the course to develop and justify your own solution. You will also develop your written and oral communication skills and learn how to communicate your results to both technical and non-technical stakeholders.

Digital Leadership & Management

This module sheds light on the role of business leadership and management in digital business scenarios. The module will provide you with a broad set of skills applicable to leadership in contemporary digital business, including skills development in management styles in digital business scenarios, digital business strategy, digital innovation and digital analytics and customer insights.

Please note that it may not be possible to deliver the full list of options every year as this will depend on factors such as how many students choose a particular option. Exact modules may also vary in order to keep content current. When accepting your offer of a place to study on this programme, you should be aware that not all optional modules will be running each year. Your tutor will be able to advise you as to the available options on or before the start of the programme. Whilst the University tries to ensure that you are able to undertake your preferred options, it cannot guarantee this.

What will I be doing?


The focus of this course is on practical, problem-based activities and on applying your learning through hands-on exercises in computer-based laboratories.

  • Combined workshops and lectures will be used to introduce the theory that underpins the field, and to practise applying this knowledge in individual and group activities
  • Computer-based laboratories will be used to provide practical, hands-on experience using a range of industry standard tools, systems and programming languages.


A variety of assessments are used within this programme including practical assessments, written assignments, oral presentations and examinations.

Greater Manchester Institute of Technology

Located across England, Institutes of Technology (IoTs) are a national network of partnerships between local colleges, universities, and leading employers.

We are a proud partner in the Greater Manchester Institute of Technology. This means as a student on this course you will benefit from being part of the University of Salford community, with access to our facilities and support, and taught by our tutors. You will also be part of the GMIoT network, with access to additional events and activities.

Greater Manchester Institute of Technology logo
Employment and stats

What about after uni?


Demand for data scientists outstrips supply and there is continued demand for qualified professionals across many global industries. Recent government commissioned research shows that almost 50% of businesses are recruiting for roles that require hard data skills. On completing this course, you could apply for junior roles in data analysis or data science.


What you need to know


As an applicant for this course, you will be interested in working with data and curious about the fields of Artificial Intelligence and Big Data. You will have gained some aptitude for mathematics at GCE A-Level (or equivalent) and have an interest in applying your knowledge to work with real-world datasets.


All of our courses are taught and assessed in English. If English is not your first language, you must meet our minimum English language entry requirements. An IELTS score of 6.0 (no element below 5.5) is proof of this, and we also accept a range of equivalent qualifications.

Read more about our English language requirements, including information about pathways that can help you gain entry on to our degree courses.

Standard entry requirements

UCAS tariff points

72 points

A level

C or above in Maths

Alternative entry requirements

Salford Alternative Entry Scheme (SAES)

We positively welcome applications from students who may not meet the stated entry criteria but who can demonstrate their ability to pursue the course successfully. Once we receive your application, we'll assess it and recommend it for SAES if you are an eligible candidate.

There are two different routes through the Salford Alternative Entry Scheme and applicants will be directed to the one appropriate for their course. Assessment will either be through a review of prior learning or through a formal test.

For further information, please contact: enquiries@salford.ac.uk.


Type of study Year Fees
Full-time home 2024/25 £8,500.00per year
Part-time 2024/25 Part-time costs will be calculated on a pro rata basis
Full-time home 2025/26 £9,250.00per year

Additional costs

You should consider further costs which may include books, stationery, printing, binding and general sustenance on trips and visits. 

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All Set? Let's Apply?

UCAS Code: GG10

Start Date(s): September


One year full-time

Two years part-time

Enrolment dates

September 2025

September 2026

UCAS information

Course ID GG10

Institution S03