Learn to transform data into insights – and transform your career

As big data powers more aspects of industry and society, demand is rising for professionals with the expertise and technical know-how to harness business analytics.

Develop foundational knowledge of concepts and software for capturing insights that improve decision-making and performance for UK organisations by pursuing your Postgraduate Diploma (PGDip) in Business Analytics online.

Our online PGDip course focuses on business analytics tools and techniques for analysing data to solve challenges and unlock new opportunities. You'll take 12 units from our complete master's degree course as you learn to identify data patterns and trends, leverage machine learning capabilities, gather business intelligence, and more.

Quick course facts

Course benefits

Capitalise on the prestige of a PGDip in Business Analytics offered by a top-ten university in the UK.1 There is no dissertation requirement, and our partnerships provide hands-on experience with next-level software and resources. After completing the course, you'll have the option to level up your credentials by seeking your Master of Science in Business Analytics degree.

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Career impact


The global data management market is projected to exceed £175 billion by 2030,2 making now an ideal time to acquire business analytics acumen. By attaining your PGDip online, you can gain business intelligence, machine learning, and predictive modelling skills relevant to some of the UK's fastest-growing fields. The PGDip provides hands-on experience with analytics platforms.

Learning outcomes


  • Demonstrate a systematic and thorough understanding of contemporary methods and practices related to business analytics and their consequences in the wider and international context
  • Analyse, interpret, and present multidimensional and complex data
  • Identify operational, tactical, and strategic level resource management problems and the appropriate amount of detail to analyse based on the level
  • Frame managerial problems as mathematical problems and have an appreciation of which methods might be used for solutions
  • Appreciate ethical dilemmas arising in data acquisition, management, and mining
  • Acquire expert skills in using spreadsheet software
  • Use state-of-the-art business analytics software
  • Develop written communication skills for effectively presenting technical results to non-technical audiences
  • Improve your time management skills and apply your problem-solving skills to diverse areas

Explore the curriculum


Offered by the AMBA- and EQUIS-accredited Bath School of Management, our online PGDip in Business Analytics course immerses you in quantitative techniques used to organise and interpret big data. You'll acquire a firm grasp of data analysis and reporting systems by completing 12 units from our Business Analytics master's degree, omitting the dissertation. Each course unit lasts eight weeks.

Units

Phase 1

Business Intelligence (10 credits)

Get to grips with key Business Intelligence software, including graphical report design, dashboard design, and visualisation techniques to develop high-level insights.

You’ll learn to:

  • Identify the underlying data model of a business process
  • Visualise processed data in multiple dimensions to maximise its business value.
  • Perform exploratory data analysis

Learning Outcomes:

  • Understand the uncertainties associated with data analysis.
  • Perform statistical analysis to a set of given data.
  • Make managerial conclusions about a set of given data using descriptive statistics.
Databases (10 credits)

This introduction to databases for storing data and retrieving information helps you optimise and process data to derive managerial insights.

You’ll learn to:

  • Identify the underlying data model of a business process
  • Design a database for efficient data storage and retrieval
  • Eliminate data duplication to achieve information consistency
  • Present multidimensional data in tabular format

Learning Outcomes:

  • Understand and implement data models.
  • Design a database that will best fit the needs of a business in terms of both flexibility and efficiency.
  • Use optimised queries to process data and derive managerial insights.
  • Use SQL and general database software.
Optimisation (10 credits)

Learn how to make the best possible decisions through the use of mathematics and computers, and present the optimised results to a non-technical audience.

You’ll learn to:

  • Model and solve real-life managerial challenges as optimisation problems
  • Recognise components of an optimisation problem within a given managerial context
  • Assess the complexities to solve issues using an optimisation model
Spreadsheet Modelling (10 credits)

Understand the advanced functions of Excel as well as the programming language (VBA) embedded within it, to support business decision-making.

You’ll learn to:

  • Understand and critique the capabilities and limitations of Excel
  • Use advanced functions of Excel to provide business decision support
  • Assess ways in which to solve business problems using Excel and VBA
Business Statistics (10 credits)

Review concepts of data analysis, using statistical analytics software to develop your interpretations.

You’ll learn to:

  • Explore the uncertainties associated with data analysis
  • Perform statistical analysis on a set of given data
  • Make managerial conclusions about a given set of data using descriptive statistics
Forecasting (10 credits)

Examine forecasting techniques to achieve the best possible estimates for unknown parameters such as customer demand.

You’ll learn to:

  • Interpret patterns and trends in data, while understanding the uncertainties associated with forecasting
  • Draw managerial conclusions from data using forecasting methods and software
  • Prepare business forecasting model reports to a non-technical audience

Phase 2

Project Management (10 credits)

Apply concepts, frameworks and tools of project management and strategies in the context of business analytics projects, using case studies to examine the real-world management challenges.

You’ll learn to:

  • Select appropriate management approaches and analytics goals for each project, applying techniques to reduce uncertainty
  • Assess the project data requirements and associated time-budgets for data collection
  • Plan for project success within the constraints of time, cost and quality
  • Understand the risks and uncertainties associated with managing analytics projects, applying principles to manage project teams
  • Understand the importance of integrating analytics teams with business teams
  • Apply basic tools of project management at strategic, systems and operational levels in real-world analytical contexts

Learning Outcomes:

  • Make assessments of the data requirements of the project and associated time - budgets for data collection.
  • Assess and plan for project success beyond the triple constraints of time cost and quality.
  • Understand the general risks and uncertainties associated with managing analytics projects.
  • Apply principles of managing project teams.
  • Use and apply basic tools of project management at strategic, systems and operational levels in analytics contexts likely to be encountered in practice.
Data Mining (10 credits)

Building on from ‘Databases’ and ‘Business Intelligence’, you will learn how to spot patterns in data using algorithms, detecting previously unknown rules and identifying the business implications.

You’ll learn to:

  • Model business challenges as data mining models, using state-of-the-art data mining software
  • Measure the accuracy and precision of the rules and patterns detected
  • Prepare business reports and present the results of an optimisation model to a non-technical audience

Learning Outcomes:

  • Model business challenges as data mining models.
  • Choose appropriate algorithms to detect previously unknown rules and patterns within data and infer their business implications.
  • Measure the accuracy and precision of the rules and patterns detected.
Machine Learning (10 credits)

This unit covers the fundamentals and applications of machine learning (ML). This is accompanied by some programming exercises to apply theoretical knowledge in practice (using available AI libraries).

The unit also covers deep learning, which has been revolutionising many applications in the recent decade.You will implement these deep learning algorithms (e.g., using Keras - a very powerful and easy-to-use Python library for developing and evaluating such models)and gain experience in training deep neural networks with Cloud GPU in Google Colab.

Other than supervised learning algorithms, you will learn unsupervised approaches that include Gaussian mixture models and dimension reduction techniques (e.g., principal component analysis), and will get an overview of current research and applications within the area.

You’ll learn to:

  • Distinguish between different formulations of the machine learning challenge such as supervised and reinforcement learning.
  • Demonstrate understanding of a wide range of machine learning techniques, their strengths, and their limitations.
  • Write code in a relevant programming language (e.g. Python) and employ software libraries to solve problems in machine learning.

Topics covered in this unit may include (but are not limited to) the following:

  • Central concepts and algorithms of supervised and unsupervised learning.
  • Deep learning.
  • Convolution neural networks.
  • Intelligent control and cognitive systems (will cover data augmentation and transfer learning).
  • Current research and applications of Deep learning (e.g., unsupervised, geometric).
Heuristics (10 credits)

Building on skills and knowledge acquired during the ‘Optimisation’ and ‘Spreadsheet Modelling’ units, you’ll learn how to develop algorithms and implement them to optimise your business decisions.

You’ll learn to:

  • Design heuristic algorithms for optimisation problems
  • Understand and improve the computational complexity of an algorithm
  • Provide solutions for managerial decision problems using a programming language, such as VBA

Learning Outcomes:

  • Design heuristic algorithms for solving optimisation problems.
  • Understand and improve the computational complexity of an algorithm.
  • Provide solutions for managerial decision problems using a programming language.
Simulation (10 credits)

Understand how to simulate business processes using computer software, and to apply what-if analysis.

You’ll learn to:

  • Use of state-of-the-art simulation software
  • Construct simulation models of real-world business processes
  • Test and compare business scenarios using simulation

Learning Outcomes:

  • Construct simulation models of real- -world business processes.
  • Identify terminating and non-terminating systems and choose appropriate statistical methods to evaluate their performance.
  • Test and compare business scenarios using simulation.
Analytics in Practice (10 credits)

Delivered by faculty members and industry experts in business analytics, this unit focuses on business analytics software, its applications in practice in different sectors and its implications in a wider international context.

You’ll learn to:

  • Use contemporary business analytics software to identify problems, devise solutions and implement them
  • Assess past and current business analytics implementations, considering ethical implications
  • Project the future needs, solutions and trends for business analytics solutions across diverse industries
  • Critically evaluate state-of-the-art software for business analytics, and its presentation to non-technical audiences

Learning Outcomes:

  • Use contemporary business analytics software to discover unidentified problems, devise solution approaches and implement them.
  • Assess the past and current business analytics implementations, in particular with respect to ethical considerations.
  • Project the future needs solutions, and trends for business analytics solutions across diverse industries.
  • Critically evaluate state of the art software for business analytics, and its presentation to non- technical audiences.

Entry requirements


Qualifications

  • Typically, you should have a first or second class bachelor's honours degree or international equivalent.
  • To apply for this course, you must have an undergraduate degree in a subject with high quantitative content such as mathematics/statistics, computer science, engineering, physics, chemistry, biology, economics, or a quantitative social science. We may consider other subjects if they have enough quantitative content
  • Previous experience of computer programming is an advantage. You should include information about your quantitative and programming experience in your personal statement

International students

  • If your first language is not English you will need IELTS with a grade of at least 7.0 overall and no less than 6.5 in any of the four parts (listening, reading, writing and speaking). If you completed your degree in the UK within the last 2 years prior to the start of the course, you may be exempt from our English language requirements.

Fees and funding details


Our online PGDip Business Analytics course costs £833* per 10 credits (10% alumni discount). Fees are paid in unit instalments corresponding with the course units. To qualify for a PGDip, you will need a total of 120 credits.

To learn the complete details, review the fees and funding page.

Why choose online?


Our active learning environment will keep you connected to the curriculum all the way through to graduation.

  • Engaging video content and real-life case studies
  • Interaction and networking with students and lecturers
  • Digital resources to support your studies and develop your career

University of Bath
Online learning

Interactive.
Immersive.
Supportive.

Designed exclusively for online study,
the University of Bath’s Virtual Learning Environment…
takes the learning experience further.

1: Find everything you need quickly and easily

2: Prep your workload and set your weekly agenda
Unit calendar
Upcoming events
Calendar of deadlines

3: Study in bite-sized blocks at a time and place that suits you

4: Tap into a wealth of all-inclusive e-resources

5: Experience academic content in a variety of engaging ways

6: Connect with specialist support when you need it

7: Bring learning to life with video and real-world case studies

8: Enhance your studies with hands-on interactive assignments

9: Collaborate and network with peers and tutors

10: Build your own portfolio and share your best work

Take what you’ve learned and apply it in the real world

Time to further your career? Request information and apply now.

Professor Gunes Erdogan

Prof. Gunes Erdogan

Prof Gunes is a Director of Studies MSc in Business Analytics, Information, Decisions & Operations, Bath Centre for Healthcare Innovation and Improvement. His area for research interest and expertise includes exact and heuristic algorithms for integer and mixed-integer optimisation problems and their applications to healthcare and logistics problems. His projects include the 'Vaccines4All' location, routing and allocation models to support large-scale vaccination and 'Newton RCUK - TUBITAK' innovating the Turkish Supply Chain for Services in Humanitarian Aid.

Explore your options with the University of Bath. If you are interested in studying the equivalent on-campus MSc, you can find out more by visiting our full-time Business Analytics MSc course page.

  1. The best UK universities 2023 – rankings by The Guardian
  2. Enterprise Data Management Market to Hit $221.58 Billion by 2030: Grand View Research, Inc. by Bloomberg.
* Valid up to and including September 2024 intake. Tuition fees are liable to increase each January. You should budget for an increase of up to a maximum of 5% each year.