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Postgraduate

MSc Fashion Analytics and Forecasting

Digital tools and lights
Digital Lights | University of Arts London | Credit: Georgina Capdevila Cano
College
London College of Fashion Start date
September 2024 Course length
1 year

This fully online course combines fashion business expertise with machine learning, forecasting and statistical data analysis. You will be part of an online community that benefits from immersive industry participation.

Course summary

Applications closed 2024/25

We are no longer accepting applications for 2024/25 entry to this course. Applications for 2025/26 entry will open in Autumn 2024.

Re-approval

Please note that this course is undergoing re-approval. This is the process by which we ensure the course continues to provide a high quality academic experience. During re-approval there may be some changes to the course content displayed on this page. Please contact us if you have any questions about the course.

Applying for more than 1 course

You can apply for more than 1 postgraduate course at UAL but we recommend that you apply for no more than 3. Find out more in the Apply Now section.

Why choose this course at London College of Fashion

  • This MSc is currently the first Master's programme in the world to apply data analytics and forecasting in the context of fashion business.
  • This programme aims to enable graduates to use data analytics to creatively solve complex real-world problems in the fashion industry from design, production and consumption challenges through to considerations of environmental impact.
  • This is the first Master's programme to bring together the expertise of the three schools of London College of Fashion in the application of highly contextualised data analytics to Fashion Design and Technology, Fashion Media and Communication and Fashion Business disciplines across the global fashion industry.
  • This programme offers a premium online learning experience with a focus on the use of live industry briefs to develop problem solving skills.
  • Graduates will gain skills in the use of a variety of industry-relevant software tools for the collection, analysis and visualisation of data. Such tools currently include Qualtrics, R Studio, IBM SPSS Statistics, SQL, Tableau, Qualtrics and Adobe In-Design. The list is regularly reviewed with industry partners to ensure currency.
  • This programme has been developed in consultation with our industry partners in response to an identified skills gap and so positions graduates well for employment, consultancy or research futures in the fashion and allied industries.

Open days

Course overview

Introduction  

In an era marked by rapid technological advancements, the fashion industry is undergoing a transformative shift, moving beyond traditional reliance on intuition and creativity. Today, the strategic integration of data-driven insights, machine learning algorithms and AI applications are reshaping the business of style and commerce globally. Modern fashion companies are becoming data-focused, using insights for a sustainable future. This has created a rising demand for professionals who grasp the power of fashion data and navigate through the complex interplay of economic forces, consumer behaviours and global trends. 

The MSc Fashion Analytics and Forecasting course is situated at the intersection of data analytics, forecasting, predictions using machine learning and the dynamic realm of fashion business. This course combines creativity with analytics, offering a unique opportunity to explore how these data driven technologies empower fashion professionals to make informed decisions, model demand and revolutionise traditional business models.  

Delivered online, the course utilises a blend of pre-recorded content, self-guided learning activities and live, tutor-led sessions. There is emphasis on learning and practicing analytics using coding and software tools while developing a critical understanding of the complex business of fashion. Graduates develop practical skill sets that prepare them for careers in analytics, core fashion industry roles (with extended skills), strategic and leadership roles, consulting, technology and research futures. 

As an advanced signatory to the UN Principles of Responsible Management Education (PRME), Fashion Business School (FBS) ensures that our curriculum aligns with the six principles of responsible management education. We are dedicated to preparing graduates who are not only proficient in fashion data analytics and forecasting but also equipped to meet the challenges of the contemporary global fashion industry responsibly and sustainably. 

What to expect  

Learning Experience 

  • A carefully designed balance of online and offline learning methods including guided reading, practice exercises and live interaction with expert tutors. 

Technical Skills 

  • Exposure to industry relevant software tools and programming languages for the collection, analysis, modelling, and visualisation of data.  

Research 

  • Opportunity to develop research expertise in the Master’s project applying algorithms and models to address a particular issue/opportunity in the fashion industry. 

Community 

  • Interaction with global industry speakers and researchers, building an online global community of students, industry and academia. 

Collaboration and Creativity 

  • Collaboration with your postgraduate peers to creatively address advanced industry challenges   leveraging rich and varied individual experiences to enhance employability skills. 

Our online resources 

  • Access to a wide range of UAL resources, including the UAL online library, databases, third-party software and tools. 
  • You will have access to both technical and pastoral support and be part of a global community committed to promoting accessibility, diversity and inclusion. 

Industry experience and opportunities  

This course includes working on industry problems and datasets through the assignments and Master’s projects. There are opportunities for start-up mentoring, networking and support in finding employment offered by LCF’s Graduate Futures services.   

Climate, Social and Racial Justice 

The course is committed to embedding UAL’s Principles for Climate, Social and Racial Justice. 

​​We are committed to ensuring that your skills are set within an ethical framework and are working to embed UAL’s Principles for Climate, Social and Racial Justice.  

​​We are committed to developing ethical business practices. To achieve this, we are working to embed UAL’s Principles for Climate, Social and Racial Justice into the course.  

Contact us

Register your interest to receive information and updates about studying at UAL.

Contact us to make an enquiry.

Postgraduate Preparation Guide

Download the Postgraduate Preparation Guide (3.54)

Course units

Postgraduate Block 1 

Principles of Fashion Business Analytics (20 Credits) 

This unit builds the foundation of fashion business analytics, as an entry point into the course's advanced analytics journey. You will explore the role of analytics in fashion business, covering data structures and analytics techniques. You will learn statistical concepts, data science mathematics and essential coding skills. You will develop skills in data wrangling, manipulation, visualisation and be able to generate insights from raw data.  

Fashion Consumer Insights (20 Credits) 

This unit immerses you in the intricacies of consumer dynamics within the global fashion landscape. You will be introduced to the principles of communication with diverse consumer audiences and the role of data in fashion communication. This unit empowers you to decipher what data reveals about the fashion consumer, offering insights into their preferences and trends. You will develop essential skills in storytelling, enabling you to craft compelling written and visual narratives that resonate with diverse global fashion audiences. 

Data Driven Fashion Innovation (20 Credits) 

This unit examines the concepts that underpin the use of data in effective product management by critically analysing fashion supply chain and product management processes and practices. It evaluates the field within the context of fashion business models, emerging climate and social justice themes and data driven intelligence.  

 

Postgraduate Block 2 

Forecasting and Research in Fashion (20 Credits) 

This unit supports the development of your MSc Master’s project. You will develop skills in framing research problems using diverse datasets from the fashion industry. You will explore various research designs and learn the art of conducting various statistical tests to facilitate your investigations. This unit provides essential univariate and multivariate forecasting skills for navigating the dynamic landscape of advanced research in the fashion business. 

Artificial Intelligence and Machine Learning for Fashion (20 Credits) 

This unit offers a holistic journey through the fashion and technology landscape using machine learning, computer vision, neural nets, and artificial intelligence. You will engage with various algorithms, including classification, regression, clustering, prediction, product recommendation, and optimisation, within the context of the fashion business. 

Elective Units (20 Credits) 

In block 2, students will have an opportunity to take an elective unit. Individual unit descriptors can be found in the Electives Handbook. 

 

Postgraduate Block 3  

Master’s Project (60 Credits) 

The Masters Project is the final stage of your Masters’ course and is the is the culmination of your studies and provides you with a space to synthesise all the knowledge and skills you have gained on the course so far. Your project will be self-directed, and you will negotiate the shape and direction of your project at the outset with your supervisor. This important final phase of your studies is where you will effectively communicate your work along with your ability to critically interrogate your practice with robust approaches to research and theoretical analysis. Upon completion of your project, you will have generated a high-level Masters’ quality piece of work that will showcase your practice, academic literacy and the professional standards that will act as a platform for your future career and professional development. 

Programme specification

Download course specification (PDF File 463.0 KB)

Learning and teaching methods

The following teaching and learning methods are employed to support the integrated aims of the course outcomes: 

  • Online asynchronous (pre-recorded) lectures and briefings (large group) 
  • Online synchronous seminars (small group)  
  • Online asynchronous and online synchronous practical workshops and demonstrations (small group)   
  • Online academic skills workshops including library induction (small group)  
  • Online synchronous tutorials (individual or small group) 
  • Online asynchronous and online synchronous peer-to-peer and/or tutor feedback sessions (individual or small group) 
  • Presentations (live or pre-recorded) 
  • Independent learning (individual or small group)

Assessment methods

The following assessment methods are employed to support the integrated aims of the course outcomes: 

Formative Assessments 

Formative assessment opportunities are provided within each unit to enable you to check the progress of your learning. 

  • Self-assessments 
  • Peer assessments 
  • Presentations 
  • Formative Moodle quizzes 

Summative Assessments 

A range of varied summative assessment methods are used including: 

  • Time constrained assessments 
  • Group Projects and Presentations 
  • Reports 
  • Master’s project thesis, which requires the production of a body of work through independent study that demonstrates a high level of quantitative and forecasting research, advanced critical and analytical skills, an innovative approach to problem-solving and an ability to work in collaboration with the fashion industry.

EDITED

The MSc Fashion Analytics and Forecasting is supported by EDITED, the leader in Retail Market Intelligence. EDITED helps retailers increase margins, generate more sales and drive better outcomes through AI-driven market data, analytics and research.  Brands like Zara, Puma, John Lewis, Marni and Tommy Hilfiger use EDITED’s suite of Market Intelligence products to create retail strategies and make better assortment, pricing and promotion decisions everyday.

Stylumia

The MSc Fashion Analytics and Forecasting course is supported by Stylumia, a global trend forecasting solution company that uses demand sensing machine learning algorithms, augmented with consumer demand signals to predict demand. Students have access to the Stylumia software and datasets, allowing them to gain a deep understanding of the potential of predictive analytics.

MSc Fashion Analytics and Forecasting | Course Leader Satya Banerjee

Latest news from this course

Staff

Dr Satya Banerjee

Dr Satya Banerjee is the course leader and earned his PhD in Management in information systems area. Through his doctoral work on ‘Intelligent Fashion Forecasting’, he investigated the use of AI and ML in the fashion Industry. Satya completed his Master’s in Fashion Management (2009) and BA (Hons.) in Economics (2007). Satya has worked with organisations such as Nike, Walmart, and Woodland before moving into academia. With a career spanning over 12 years, he has worked in fashion retailing, marketing, and analytics. His primary research interests lie in Fashion Analytics, Artificial Intelligence, Forecasting and Predictions using Machine Learning, Data Visualisation, and the overall impact of technology on the fashion business.

Satya’s recent book “AI in Fashion Industry” with Emerald, UK (2022) is one of the first textbooks and a no.1 best seller in this area that captures the emerging developments in this field. He has presented his research in many national and international forums. His co-authored work titled “Design of Future” was awarded the best paper in the senior faculty category in IFFTI, Polimoda, Florence (2015) among all the fashion institutes, globally. He is also the recipient of the Fetzer Scholarship (2020) and an annual sponsored member of the Academy of Management (USA). He has authored/edited numerous works in the fashion business in past with a focus on analytics and intelligence.

Dr Lan Wang

Dr Lan Wang is lecturer in Economics and Finance at the Fashion Business School. Lan is a member of Centre for Business and Climate Change at University of Edinburgh Business School. She completed her PhD in climate finance at University of Edinburgh, MSc in Carbon Finance from University of Edinburgh (2013), MSc in Corporate Finance from ICMA Centre, University of Reading (2010), and BSc in Economics (2005-2009).

Lan worked for several years at Bank of China and participated in consulting and research projects funded by World Bank and British Consulate Guangdong General in China.

Lan has attended the United Nations Climate Change Conference twice as a representative of the University of Edinburgh. Lan’s research interest is in green finance, sustainable investment, climate policy, and carbon market design. She has published in the Journal of Environmental Science and Pollution Research in carbon market efficiency.

Disha Daswaney

Disha Daswaney MA is a global beauty and wellness expert. After having worked in publishing in Europe and Asia for ten years covering topics ranging from the fashion industry to travel experiences, Disha is now embedded in the School of Media and Communications LCF.

Disha’s commercial work pivots around inclusivity and emerging trends and has create content on these subjects for the London Evening Standard, Fizzy Magazine, BASE, Prestige Hong Kong and AsiaSpa Magazine.

In addition, Disha has worked with Dazed Studio, AllBright, London Evening Standard and more as a writer and trend forecaster, while providing commentary for Canvas8, Grazia and Esquire on trends in beauty, fashion, digital innovations, and the retail sector.

Mikha Mekler

Mikha Mekler MA is an innovation-led fashion supply chain expert with a deep interest in material innovation and disruptive practices in supply chains with an undetermined drive to encourage and establish circularity and next-generation materials for a responsible future in fashion. She envisions a global, joined-up effort where businesses work transparently and collaboratively.

With an industry career background including senior positions at Raeburn, Mikha’s experience is embedded within operations and management with a focus on upstream manufacturing and supply. In addition Mikha’s experience crosses the breadth of business disciplines, particularly the setup and establishment of commercial priorities to support a long-term vision for success.

Following her MA Fashion Design award, Mikha now combines her industry expertise with working with under/ postgraduate courses within the School of Design and Technology at at LCF in production management where she focuses on working with academics, technicians, and students to expand professional practice within the context of academic study, knowledge exchange and research.

Fees and funding

Home fee

£10,670

This fee is correct for 2024/25 entry and is subject to change for 2025/26 entry.

Tuition fees may increase in future years for new and continuing students on courses lasting more than one year. For this course, you can pay tuition fees in instalments.

Students from countries outside of the UK will generally be charged international fees. The rules are complex so read more about tuition fees and determining your fee status.

International fee

£22,860

This fee is correct for 2024/25 entry and is subject to change for 2025/26 entry.

Tuition fees may increase in future years for new and continuing students on courses lasting more than one year. For this course, you can pay tuition fees in instalments.

Students from countries outside of the UK will generally be charged international fees. The rules are complex so read more about tuition fees and determining your fee status.

Additional costs

You may need to cover additional costs which are not included in your tuition fees. These could include travel expenses and the costs of materials. For a list of general equipment needed for all UAL courses, visit our living expenses and additional costs page.

Accommodation

Find out about accommodation options and how much they will cost.

Scholarships, bursaries and awards

If you’ve completed a qualifying course at UAL, you may be eligible for a tuition fee discount on this course. Find out more about our Progression discount.

You can also find out more about the Postgraduate Masters Loan (Home students only) and scholarships, including £7,000 scholarships for Home and International students. Discover more about student funding.

If you’re based in the UK and plan to visit UAL for an Open Event, check if you’re eligible for our UAL Travel Bursary. This covers the costs of mainland train or airline travel to visit UAL.

How to pay

Find out how you can pay your tuition fees.

Scholarship search

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Entry requirements

The standard entry requirements for this course are as follows:

  • An Honours degree at 2.1 or above in a related discipline (e.g., any Fashion Business School undergraduate course, or undergraduate courses from other institutions in Business, Marketing or Management, or with a Product, Enterprise or Quantitative focus). 
  • OR equivalent qualifications.
  • OR applicants with a degree in another subject may be considered, depending on the strength of the application. We welcome applications from graduates with qualifications in broader fashion and creative subjects who can demonstrate an aptitude for using data and data analytics to support effective decision making.

1. APEL (Accreditation of Prior (Experiential) Learning)

Applicants who do not meet these course entry requirements may still be considered in exceptional cases. The course team will consider each application that demonstrates additional strengths and alternative evidence. This might, for example, be demonstrated by:

  • Related academic or work experience (minimum of three years)
  • The quality of the personal statement
  • A strong academic or other professional reference
  • OR a combination of these factors

Each application will be considered on its own merit but we cannot guarantee an offer in every case.

2. English Language Requirements

IELTS level 7.0 with a minimum of 6.0 in reading, writing, listening and speaking. Please check our main English Language Requirements.

Selection criteria

  • Sufficient prior knowledge and experience of and/or potential in a specialist subject area to be able to successfully complete the programme of study and have an academic or professional background in a relevant subject for the Master’s.
  • An aptitude for, or clear interest in, quantitative research, applied statistics, data analytics, data mining, machine learning, big data analytics, or forecasting from a fashion business context. 
  • A willingness to work as a team player.
  • Good language skills in reading, writing, listening and speaking.
  • The ability to work independently and be self-motivated.

Information for disabled applicants

UAL is committed to achieving inclusion and equality for disabled students. This includes students who have:

     
  • Dyslexia or another Specific Learning Difference
  • A sensory impairment
  • A physical impairment
  • A long-term health or mental health condition
  • Autism
  • Another long-term condition which has an impact on your day-to-day life

Our Disability Service arranges adjustments and support for disabled applicants and students.

Read our Disability and dyslexia: applying for a course and joining UAL information.

Apply now

Application deadline

Deadline

Round 1:

13 December 2023 at 1pm (UK time)

Round 2:

3 April 2024 at 1pm (UK time)

Decision outcome

Round 1:

End of March 2024

Round 2:

End of June 2024

Round 1
Round 2
Deadline
13 December 2023 at 1pm (UK time)
3 April 2024 at 1pm (UK time)
Decision outcome
End of March 2024
End of June 2024

Applications are now closed for 2024/25 entry. Applications for 2025/26 entry will open in autumn 2024.

Read more about deadlines

Apply now

Application deadline

Deadline

Round 1:

13 December 2023 at 1pm (UK time)

Round 2:

3 April 2024 at 1pm (UK time)

Decision outcome

Round 1:

End of March 2024

Round 2:

End of June 2024

Round 1
Round 2
Deadline
13 December 2023 at 1pm (UK time)
3 April 2024 at 1pm (UK time)
Decision outcome
End of March 2024
End of June 2024

Applications are now closed for 2024/25 entry. Applications for 2025/26 entry will open in autumn 2024.

Read more about deadlines

How to apply

Follow this step-by-step guide to apply for this course

Step 1: Initial application

You will need to submit an initial application including your personal statement and CV.

Personal statement advice

Your personal statement should be maximum 500 words and include:

  • your reasons for choosing the course
  • your current creative practice and how this course will help you achieve your future plans
  • any relevant education and experience, especially if you do not have any formal academic qualifications.

Visit our personal statement page for more advice.

CV advice

Please provide a CV detailing your education, qualifications and any relevant work or voluntary experience. If you have any web projects or other media that you would like to share, please include links in your CV. If English is not your first language, please also include your most recent English language test score.

Step 2: Interview

You may be invited to an interview following our review of your application. All interviews are held online and last 15 to 20 minutes.

For top tips, see our Interview advice.

You also need to know

Communicating with you

Once you have submitted your initial application, we will email you with your login details for our Applicant portal.

Requests for supplementary documents like qualifications and English language tests will be made through the applicant portal. You can also use it to ask questions regarding your application. Visit our After you apply page for more information.

Applying to more than 1 course

You can apply for more than 1 postgraduate course at UAL but we recommend that you apply for no more than 3 courses. You need to tailor your application, supporting documents and portfolio to each course, so applying for many different courses could risk the overall quality of your application. If you receive offers for multiple courses, you'll only be able to accept 1 offer. UAL doesn't accept repeat applications to the same course in the same academic year.

Visas and immigration history check

All non-UK nationals must complete an immigration history check. Your application may be considered by our course teams before this check takes place. This means that we may request your portfolio and/or video task before we identify any issues arising from your immigration history check. Sometimes your history may mean that we are not able to continue considering your application. Visit our Immigration and visas advice page for more information.

External student transfer policy

UAL accepts transfers from other institutions on a case-by-case basis. Read our Student transfer policy for more information.

Alternative offers

If your application is really strong, but we believe your strengths and skillset are better suited to a different course, we may make you an alternative offer. This means you will be offered a place on a different course or at a different UAL College.

Deferring your place

We do not accept any deferral requests for our postgraduate courses. This means that you must apply in the year that you plan to start your course and you will not be able to defer your place to start at a later date.

Application deadlines

For postgraduate courses at UAL there are 2 equal consideration deadlines to ensure fairness for all our applicants. If you apply ahead of either of these deadlines, your application will be considered on an equal basis with all other applications in that round. If there are places available after the second deadline, the course will remain open to applications until places have been filled.

Careers

We are in discussion with several of our current industry partners as collaborators and providers of live industry projects for this course. These partnerships are currently pending validation and legal approval.

"This course is going to provide us with future industry leaders capable of both staying ahead of fashion trends but also anticipating changing customer behaviour and how to react fast.”

Nishi Overton (Head of Marketing and Scaling at Amazon)

“Data analytics is crucial in retail. The technical proficiency this course teaches is a great opportunity for someone that has a retail background and wants to expand their skill set to make better insights with data.”

Rosie Hood (PhD, Senior Data Scientist at EDITED)

"Talented analysts are a sought after resource in retail. One of the main challenges is finding analysts who are skilled at the quantitative elements but are also tuned into the bigger picture of the business needs and the impact their number crunching has as part of a profit making venture. So, the idea of this (course) whereby you’re taking a business student and teaching the ways of data and analytics, I think that would equip your students with quite a valuable skillset to get themselves hired.”

Matthew Walsh (Director of Data and Retail at IMRG)

Graduate Futures

Graduate Futures provides a comprehensive career management service supporting our students to become informed and self-reliant individuals able to plan and manage their own careers.

LCF alumni

Many of our alumni are now impressive, leading industry figures.

London College of Fashion

Contact

Telephone

+44 (0)20 7514 7400

Address

105 Carpenter's Road
London

E20 2AR