The digital revolution has led to an unprecedented volume of information about consumers, which progressive organisations are eager to understand and use. This innovative masters degree will give you the practical skills to analyse consumer data and provide insights for successful marketing strategies.
Taught by leading academics from Leeds University Business School and School of Geography, you’ll explore a range of analytical techniques including applied Geographic Information Systems (GIS) and retail modelling, consumer and predictive analytics and data visualisation. You’ll also develop the softer skills to use the results of these analyses to inform decisions about marketing strategy.
Thanks to our connections with businesses worldwide, you’ll have access to emerging trends in topics such as consumer behaviour, decision science and digital and interactive marketing. You’ll further develop your practical skills with the opportunity to work on a live data project provided by a company.
Academic excellence
This courseoffers you a rare combination of teaching expertise; the Business School’s academic excellence in Marketing alongside world-class teaching from the School of Geography, which draws on the knowledge of the Centre for Spatial Analysis and Policy.
The University of Leeds is a major centre for big data analytics and you’ll benefit from affiliation with the UK’s Consumer Data Research Centre. The centre aims to make data that are routinely collected by businesses and organisations accessible for academic purposes. Coordinating and analysing this large and complex data has the potential to increase productivity and innovation in business, as well as to inform public policy and drive development.
Read an interview with the academic team to learn more about our expertise and the growing importance of this emerging subject area.
Core modules will introduce you to a range of analytical methods, ensuring you develop a solid foundation in the essential skills for consumer analytics and marketing strategy.
You’ll learn how to analyse geographic data using GIS software and understand the application of this in retail modelling, to evaluate new markets and locations. You’ll study predictive analytics, big data and consumer analytics, business analytics and decision science, and learn how to communicate results through data visualisations.
Alongside this, you’ll learn how to deploy data to inform decisions about marketing strategy. Marketing modules include marketing strategy, consumer behavior and direct, digital and interactive marketing. You’ll also deliver your own data-driven marketing research project for a company.
Optional modules allow you to further your knowledge in a related area of interest, either corporate social responsibility, internal communications and managing change, or applied population and demographic analysis.
By the end of the course, you’ll submit an independent project. You can either research a topic in-depth and submit a dissertation, or gain practical experience through a consultancy project working with an external organisation.
Compulsory modules
You’ll take the nine compulsory modules below, plus your dissertation, which can be a choice of either a research dissertation or marketing consultancy project.
Optional modules
You'll take one further optional module.
We use a range of teaching methods so you can benefit from the expertise of our academics, including lectures, workshops, seminars, simulations and tutorials. Company case studies provide an opportunity to put your learning into practice.
Independent study is also vital for this course, allowing you to prepare for taught classes and sharpen your own research and critical skills.
Assessment methods emphasise not just knowledge, but essential skills development too. You’ll be assessed using a range of techniques including exams, group projects, written assignments and essays, in-course assessment, group and individual presentations and reports.
As a graduate of this course you will be equipped with advanced skills in consumer analytics and marketing strategy, ideal for those wishing to pursue a career in consumer data analytics, marketing and/or management.
Due to the digital revolution, companies from around the world and in many industrial sectors have access to greater amounts of data.
The most progressive companies in the world are particularly interested in marketing graduates with strong analytical skills, and typical roles could include marketing or consumer data analyst, direct marketing manager, marketing manager, retail manager, or marketing or management consultant.
As a masters student you will be able to access careers and professional development support, which will help you develop key skills including networking and negotiating, and put you in touch with potential employers.
Our dedicated Professional Development Tutor provides tailored academic and careers support to marketing students. They work in partnership with our academics to help you translate theory into practice and develop your interpersonal and professional business skills.
You can expect support and guidance on career choices, help in identifying and applying for jobs, as well as one-to-one coaching on interpersonal and communication skills.
Read more about careers support at the Business School.
In our social media and mobile-driven world, data and digital marketing have never been more vital. Enroll in our Digital Marketing and Data Analytics online master's program to gain critical, in-demand skills and advance your marketing career. With courses in digital campaigns, branding, web and predictive analytics, social and mobile marketing, customer segmentation, and more, graduates of this program develop the digital and analytic skills you need to compete in today's insight-driven market.
In this program, you will learn how to:
The 32-credit program can be completed in one year for students choosing to take the accelerated course schedule, or in a 16-month or longer period. The program is designed to be flexible, meeting the needs of working professionals.
Ready to advance your career in digital marketing and analytics? Apply to our online graduate program in Digital Marketing and Data Analytics today.
The MA in Digital Marketing and Data Analytics can also be completed as individual certificate programs. Student have the opportunity to develop critical skills through our 16-credit graduate certificates in Digital Marketing or Data Analytics.
Our expertly designed online curriculum empowers working professionals to advance their careers in the areas of digital marketing and data analytics. According to the U.S. Bureau of Labor Statistics, the demand for advertising and marketing managers will grow by 9% over a 10-year span. With a balanced curriculum of digital-centric marketing and omni-channel customer analytics courses, graduates of the program develop digital and analytic skills that are necessary to compete in today's dynamic insight-driven marketing environment.
You can complete our 32 credit program entirely online. The program curriculum is made up of four classes (16 credits) for Digital Marketing and four classes (16 credits) for Data Analytics. The online environment provides the flexibility to meet the needs of busy working professionals. Students can choose to take between 1-3 classes a semester and can complete the program in as little as 1-year with our accelerated option.
The program allows students who are eager to gain critical, in-demand digital marketing or data analytics skills to choose one of our 16 credit certificate options. Upon completion of a certificate, students have the option to apply to continue and complete the full degree program. The certificate program is made up of the 4 Digital Marketing or Data Analytics courses.
The student learning outcomes of the Digital Marketing and Data Analytics program balance the priorities of both digital marketing and data analytics. Students will be able to:
Digital Marketing
Data Analytics
Drawing upon Emerson's longstanding expertise in strategic communication, the Department of Marketing Communication has created a unique online master's program that equips working professionals with the cross-functional skills required to be successful in today's insight-driven marketing environment.
Our online learning and collaboration platform offers a student-centric learning experience. Enrollment in each course is capped at 20 to maintain a low student-to-faculty ratio. Smaller class sizes promote interactive learning and stimulating discussions with peers and faculty.
Students in this program are exposed to industry leading analytics software such as SAS Studio, SAS Enterprise Miner, Google Analytics, and social analytics platforms to acquire the skills to turn data into valuable insights that support better decision-making across myriad business applications.
Companies need people who can take data and transform it into a powerful strategic asset. This specialisation provides a rigorous, practical foundation in the key skills needed to unlock the value of data, and an in-depth understanding of how companies can use data to make decisions and improve business performance.
Business Analytics (with specialisation in Management Science) is taught by UCL School of Management (in conjunction with UCL Computer Science). It combines modules that explore how data and analytics are transforming key areas of business (decision-making, strategy, marketing, operations) with modules that provide the mathematical and computational skills needed to make effective use of the latest business analytics tools.
Students undertake modules to the value of 180 credits.
The programme consists of six core modules (90 credits), two optional modules (30 credits) and a dissertation/report (60 credits).
Core modules
Optional modules
Students take two optional modules from a selection of elective modules offered by the UCL School of Management and other selected UCL departments. Possible electives, subject to agreement, may cover topics including software engineering, consulting psychology, project management and network analysis.
Dissertation/report
All students undertake an independent research project which culminates in a dissertation of 12,000 words.
Teaching and learning
The programme is delivered through a combination of lectures, seminars, tutorials and project work. Assessment is through unseen written examinations, coursework and the dissertation.
Further information on modules and degree structure is available on the department website: Business Analytics (with specialisation in Management Science) MSc
Graduates from this new programme will be likely to find employment in global companies and high-growth businesses, finance and banking organisations, and consulting firms.
Employability
Students will develop strong quantitative and analytical skills, an in-depth understanding of how companies use data to make decisions and improve business performance, and practical experience with leading business analytics tools.
They will be equipped to influence strategy and decision-making, and be able to drive business performance by transforming data into a powerful and predictive strategic asset.
The world is changing: more than 30 billion pieces of content are shared on Facebook every month; and companies are capturing trillions of bytes of information about their customers, suppliers, and operations. This explosion of data is disrupting industries and creating new opportunities. Companies need people who can take data, understand it, process it, extract value from it, visualise it, and communicate it. They need people who deeply understand data, its potential and its limitations, who can frame business problems, analyse data with statistical techniques, develop and maintain predictive models, and communicate analytics results to business executives, partners and customers.
Business Analytics requires a combination of management insight, strong quantitative and analytical skills, and an understanding of the technology required to handle data at scale.
UCL School of Management offers innovative undergraduate, postgraduate, and doctoral programmes to prepare people for leadership roles in the next generation of innovation-intensive organisations. The school works closely with global companies and high-growth businesses at the cutting-edge of management practice. UCL Computer Science is a global leader in research in experimental computer science.
Students on the Business Analytics (with specialisation in Management Science) MSc will benefit from the extensive industry networks of both departments.
The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.
The following REF score was awarded to the department: UCL School of Management
70% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)
Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.
At the intersection between data science, statistics and management, Business Analytics consists of using data to inform strategic decision making under uncertainty and to optimise business processes. In the digital economy with the proliferation of data, businesses have understood the tactical and strategic importance of analytics - the learning from data - as a critical field to detect and monitor client behaviours and expectations, or even future market trends.
Business Analytics tries to answer the following questions: "What has happened?" (descriptive analytics), "Why did it happen?" (explanatory or diagnostic analytics), "What will happen?" (predictive analytics) and "What should be done?" (prescriptive analytics). As such, Business Analytics is about bringing the business questions to the data.
Investing in Business Analytics can lead to a substantial competitive advantage, which, in certain sectors, ensures prosperity or even survival. Analytics is also one of the most promising approaches for public authorities who, in terms of transport, energy or public health, are required to manage and leverage the explosion of data to generate greater value for both businesses and society.
Given the increasing importance of "big data" in the economy, GSEM offers a new master program in Business Analytics that provides a wide range of career opportunities. This program responds to the growing need of medium to large organisations to leverage the use of data and to transform data assets into better management decisions.
With the proliferation of data and the present lack of analytical talent, students of the Master in Business Analytics will have excellent career opportunities across the globe. The McKinsey Global Institute estimated in 2016 a demand of 2 to 4 million “business translators” that serve as the link between analytical talent and practical business applications in the US economy by 2026. In 2017, the Business Higher Education Forum and PricewaterhouseCoopers projected data science and analytics-related job postings in the US alone to grow from 2.35 million in 2015 to 2.72 million by 2020.
The application procedure opens every year at the beginning of January.
Applications close on 28 February for all students.
There is only one Master intake in September every year. Attendance is mandatory for admitted students from day one.
The first period in France
Regardless of how you would like to later specialize, you would always start your program in France. During the first period (P1), that runs from September to December, you receive "refresher courses" and core courses. The refresher courses - taken in September - are courses geared at bringing everybody up to the knowledge level needed for the rest of the program. Core courses, or fundamentals, cover the basis for your specialization further on in the year. In total, you will have six highly intensive course courses in P1. Both the refresher courses as the core courses take place on both campuses in the area around Paris: on the ESSEC Business School campus or the CentraleSupélec Saclay campus.
You choose your campus and Major
During period 2 you will choose one of three Majors to specialize in. Depending on your choice, you will continue your program either at the CentraleSupélec Saclay Campus in France, the ESSEC France Campus also in France or the ESSEC Asia-Pacific Campus in Singapore. The first part of P2 is uniquely devoted to your specialization choice. After this, depending on your choice of Major, you will have the opportunity to take courses or minors from the other directions, giving you a well-rounded and balanced set of skills. P2 ends with an International Field Trip, and the length of this period varies depending on your choices. The electives are available from January to June.
Applying your new skills to the real world
During the final phase of the program in period 3, you will do an internship and write your thesis. The internship can take anywhere between 4 to 6 months and allows you to put your newly acquired skills and knowledge to the test. It is also an excellent way to grow your business network and to take the first steps to secure a job after graduation.
During the first period, you will attend six intensive foundation courses. Below is a short description of these courses. To read a more detailed description of the foundation courses offered, have a look at our brochure by clicking on the name of a course.
Foundation courses offered at the
ESSEC Business School Campus
This course will develop your analytical problem-solving skills and present you with the statistical methods needed to analyze and leverage multidimensional data.
Forecasting & Predictive Analytics
This course develops your judgment and critical sense in order to be able to produce and evaluate operational forecasts, and understand how it all can go wrong.
This course will teach you to design, assess and manage business strategies and how to use quantitative techniques in a strategic consulting approach through real life case studies.
Foundation courses offered at the
CentraleSupélec Saclay Campus
Continuous & Discrete Optimization
Programming exercises are covered in this course as well as the basic theory and methods for the solution of optimization problems, and linear and non-linear programming.
Big Data Algorithms, Techniques & Platforms
This course will teach you all about big data management - algorithms, techniques and tools needed to support big data processing.
This course will give the opportunity to apply the course theory to real-world problems through group lab projects with a particular focus on statistical risk and its minimization with respect to prediction function.
The Data Sciences & Business Analytics program is built on the premise of learning by doing. That is to say, we don't want you to just theorize about your chosen field of expertise, but to experience it and to delve into the complexities of business life in the real world. That is why, all students will go on an international field trip, do an internship and write a final thesis.
Your Internship, with a duration of 4 to 6 months, can take place anywhere in the worlds and is designed to facilitate your professional integration. Through the developed network of ESSEC and of CentraleSupélec's partnering firms, institutions, and alumni, you are sure to easily find an internship that suits your career ambitions.
The Thesis is an individual research that you carry out on a cutting-edge topic related to data sciences and/or business analytics. It will be a great way for you to combine your built-up expertise with an inquisitive mindset and real-world data. The objective for you is to experience a first complete and original applied theoretical research experience.
Finally, the International Field Trip is a one-week trip to meet local professionals and business leaders all over the world. You may travel to Hong-Kong, Silicon Valley, etc.
The MSc in Data Sciences & Business Analytics benefits from several professional networks which have been established by both ESSEC Business School and CentraleSupélec, independently or conjointly. When you obtain your degree with us, you tap in the network, partners, faculty and general contacts of not one but two top-tier schools both highly respected in their respective fields. You will boost your career before even having graduated.
The ESSEC Digital Business Centre of Excellence, for example, was launched in 2014 and incorporates not training programs but all activities linked to research, education, and work in the digital field. You would have access to wide range of conferences and interactions with professionals from the different sectors.
Do you want to learn how to turn data into business insights at a state-of-the-art teaching facility led by international experts? Are you interested in discovering cutting-edge analytics using real-world datasets, developing both your career and consultancy skills?
This course has been developed by the Neo-demographic Laboratory for Analytics in Business (N-LAB), a state-of-the-art teaching, data visualisation and research facility within the Business School. It is offered in collaboration with multinational business in order to provide the exact skillset that they are looking for.
As well as learning to harness big data tools, data science techniques and manage analytics projects, you will benefit from significant industry engagement.
N-LAB's partners span the world, and currently include:
In addition to guest lectures, coursework will be based on real-world datasets, providing hands-on practical experience in the techniques businesses are looking for, as well as required skills in managing practical business analytics projects.
Academic English preparation and support
If you require additional support to take your language skills to the required level, you may be able to attend a presessional course at the Centre for English Language Education, which is accredited by the British Council for the teaching of English in the UK. Students who successfully complete the presessional course to the required level can progress to postgraduate study without retaking IELTS or equivalent.
Specialist business and management courses are available and you could be eligible for a joint offer, which means you will only need to apply for your visa once. Students who enter via the CELE route are exempt from paying the school's £2,000 reservation fee. For more details, please contact us.
Key facts
Across the autumn and spring semesters, you will take 120 credits of taught modules. Each module typically consists of 10 two to three hour sessions.
You will complete a 60-credit 12-15,000-word dissertation over the summer, and will be allocated an appropriate dissertation supervisor who will oversee your progress.
Assessment
You will be assessed through a combination of individual essays or group projects and written exams.
Semester one
Core modules
Optional modules
One from:
Core modules
Optional modules
One from:
Summer
The modules we offer are inspired by the research interests of our staff and as a result may change for reasons of, for example, research developments or legislation changes. This list is an example of typical modules we offer, not a definitive list.
Career destinations for our postgraduates include accountants, finance and investment analysts, higher education teaching professionals, investment bankers, IT business analysts, management consultants, marketing professionals, public relations professionals and university researchers.
Postgraduate careers team
Taught students benefit from the support of our postgraduate careers team who will help you to explore your career options and develop your career management skills. Our weekly MSc Advanced Career Leaders Programme is complemented by individual careers consultations, networking events and access to a wide range of employer presentations, volunteering activities and work experience opportunities.
Through a combination of your academic studies and the careers support on offer, you will be in an excellent position to enhance your career prospects and move onto the next stage of your career.
Employability and average starting salary
82.1% of postgraduates from Nottingham University Business School who were available for employment secured work or further study within six months of graduation. £28,500 was the average starting salary, with the highest being £50,000.*
* Known destinations of full-time home postgraduates 2015/16. Salaries are calculated based on the median of those in full-time paid employment within the UK.
Career and professional development
Whether you are looking to enhance your career prospects or develop your knowledge, a postgraduate degree from the University of Nottingham can help take you where you want to be.
Our award-winning Careers and Employability Service offers specialist support and guidance while you study and for life after you graduate. They will help you explore and plan your next career move, through regular events, employer-led skills sessions, placement opportunitiesand one-to-one discussions.
Given the ever-increasing volume of data that businesses have access to today, there is a demand for employees who have computational and analytical skills and who can help inform business decisions to increase efficiency and ultimately build a competitive edge. Our Masters in Business Analytics has been developed with just that in mind and aims to train students to understand the variety of business environments as well as importance and relevance of decision problems facing organisations and ways of solving these using a variety of techniques.
Students will learn how to apply descriptive, predictive, and prescriptive analytics of big data concepts and techniques to generate valuable insight that can assist with decision making. Last, but not least, the Masters will provide students with hands-on experience in applying these concepts and using these techniques and most of the popular analytics software through their projects including industry projects. In sum, the programme aims to equip students with the skills required to interpret, conceptualise and convert Big Data into useful information and thus enabling students to make better informed decisions as future business managers.
All students attend and complete four core courses in Semester 1 and four option courses in Semester 2. The programme concludes with a 60-credit Dissertation.
General Educational aims are to:
Specific Educational aims are to:
It is anticipated that the demand for data analytics employees will continue and indeed grow as analytics is viewed as a key competitive resource by many companies. If market forecasts are anything to go by then the worldwide revenues for big data and business analytics will grow from $130.1 billion in 2016 to more than $203 billion in 2020 (Source: IDC). This will inevitably lead to further growth of the market for employees in the area of data analytics.
The new MSc in Business Analytics will offer students from a range of degree backgrounds the opportunity to equip themselves with an artillery of concepts, methods and applications of business analytics along with hands-on and practical experience in applying them to industry projects in different business settings. It is not just about being able to analyse and digest the data available but to then translate this into effective decision-making. In sum, we expect the new programme to open a range of career pathways in analytics for our graduates including business consultants, business analysts, business intelligence & analytics consultants, metrics & analytics specialists, analytics associates, data analysts, solution architects, business process analysts, management consulting associates, and operational research consultants.
In addition to being a science in its own right, mathematics plays a fundamental role in the quantitative areas of practically all other academic disciplines, particularly in the natural sciences, engineering, business administration, economics, medicine and psychology. Mathematical results permeate nearly all facets of life and are a necessary prerequisite for the vast majority of modern technologies – and as our IT systems become increasingly powerful, we are able to mathematically handle enormous amounts of data and solve ever more complex problems.
Special emphasis is placed on developing students' ability to formalise given problems in a way that facilitates algorithmic processing as well as enabling them to choose or develop, and subsequently apply, suitable algorithms to solve problems in an appropriate manner. The degree programme is theoretical in its orientation, with strongly application-oriented components. Studying this programme, you can gain advanced knowledge in the mathematical areas of Cryptography, Computer Algebra, Algorithmic Algebra and Geometry, Image and Signals Processing, Statistics and Stochastic Simulation, Dynamical Systems and Control Theory as well as expert knowledge in Computer Science fields such as Data Management, Machine Learning and Data Mining.
Furthermore, you will have the chance to learn how to apply your knowledge to tackle problems in areas as diverse as Marketing, Predictive Analytics, Computational Finance, Digital Humanities, IT Security and Robotics.
The core modules consist of two mathematics seminars and the presentation of your master's thesis.The compulsory elective modules are divided into eight module groups:
1) Algebra, Geometry and Cryptography
This module group imparts advanced results in the areas of algebra and geometry, which constitute the fundament for algorithmic calculations, particularly in cryptography but also in many other mathematical areas.
2) Mathematical Logic and Discrete Mathematics
The theoretical possibilities and limitations of algorithm-based solutions are treated in this module group.
3) Analysis, Numerics and Approximation Theory
Methods from the fields of mathematical analysis, applied harmonic analysis and approximation theory for modelling and approximating continuous and discrete data and systems as well as efficient numerical implementation and evaluation of these methods are the scope of this module group.
4) Dynamical Systems and Optimisation
Dynamical systems theory deals with the description of change over time. This module group is concerned with methods used for the modelling, analysis, optimisation and design of dynamical systems, as well as the numerical implementation of such techniques.
5) Stochastics, Statistics
This module group deals with methods for modelling and analysing complex random phenomena as well as the construction, analysis and optimisation of stochastic algorithms and techniques used in statistical data analysis.
6) Data Analysis and Data Management and Programming
This module group examines the core methods used in computer science for the analysis of data of heterogeneous modalities (e.g. multimedia data, social networks and sensor data) and for the realisation of data analysis systems.
7) Applications
In this module group, you will practise applying the mathematical methods learned in module groups 1 to 6 to real-world applications such as Marketing, Predictive Analytics and Computational Finance.
8) Key Competencies and Language Training
In this module group, you will choose seminars that develop your non-subject-specific skills, such as public speaking and academic writing and other soft skills; you may also undertake internships. This serves to complement your technical expertise gained during your degree studies and helps to prepare you for your professional life after university.
Business Analytics is the intersection of management science and machine learning in real world applications.
It offers new potential to improve financial performance, strategic management and operational efficiency.
Business Analytics is an increasingly critical component in preparing organizations to solve 21st-century business challenges and support data driven decision making.
Our MSc Business Analytics programme is a one year, full-time programme consisting of 6 core modules, and 2 elective modules from a choice of 7 elective modules.
The core modules are conducted via lectures, tutorials, and computer laboratory sessions. Students undertake the dissertation project in Business Analytics in collaboration with one of our international industrial partners.
Graduates of the programme will have gained the necessary skills and knowledge in a range of fields, including business operation, database, statistics, informatics, data analytics, machine learning and big data technologies in real-world business contexts.
Applicants for this programme are required to have at least a second class honours in the first division or international equivalent in any discipline, including business and management, and at least 10 credits equivalent value with significant mathematical/statistical content (However, this course is not suitable for students who have previously studied a significant amount of business analytics).
Our learning environment is highly interactive and innovative with student-centred learning activities.
Other than examinations, our students will be assessed via essays writing, practical exercises, group and individual projects, and oral presentations.
The dissertation focuses on developing students’ skills in applying analytic techniques, communicating and solving the data analytics problem.
The area of business analytics is growing in financial sectors, customer services, enterprise optimization, and consumer marketing.
When our students graduate, they will be able to:
What are the potential careers of our graduates?
Embark on a career in a leading-edge field and master the exciting and challenging world of big data!
Big data techniques are revolutionising how organisations and industries acquire and analyse data, offering valuable insights into how people live, work, play, travel, shop and exercise. These insights are valuable to marketers, researchers, designers, city planners, app developers, educators and many more.
GCU's MSc in Big Data Technologies helps students build the fundamental knowledge and practical skills for success in this fast-growing field. You'll develop competence in a range of emerging technologies: big data, cloud computing and the internet of things. You'll learn from the experts; GCU is internationally recognised for the strength of its research in these exciting subjects, driving 21st century innovation.
With both full-time and part-time study available, the programme is ideal for someone with a background in computer science, software engineering, web technologies or computer engineering who wants to enhance or update their skills. Those with backgrounds in mathematics and electronics are also well suited.
The up-to-date curriculum keeps a career-focused approach, so you'll gain valuable skills you can immediately put to work in the industry.
Your expertise in big data will enable you to provide new insights into human behaviour and psychology, which can help us build stronger and happier societies across the globe. Your work could shape smart, sustainable cities; remove barriers to education; help people make healthier choices day-to-day; improve public health… and so much more. All meaningful ways of contributing to the common good.
Full-time students complete six taught modules; three in trimester A and three in trimester B and an MSc dissertation project in trimester C. Part-time students complete six taught modules; three in Year 1, three in Year 2and an MSc project in Year 3.
Cloud Computing and Web Services
This module provides analytical and practical coverage of cloud computing and web services. It focuses on the technology, frameworks and associated standards: cloud models, cloud platforms and scalability. It also provides coverage of current web service technology and data transport representations, and integrated cloud and web service application development. Current examples from industry technology are used throughout.
Big Data Landscape
This module covers the process of managing Big Data throughout its lifecycle, from requirements through retirement. The lifecycle crosses different application systems, databases and storage media. Students will gain an understanding of the full Big Data value chain. They will be able to analyse the challenges and opportunities associated with the different stages that Big Data passes through.
Data Analytics
This module covers the basic concepts of statistics needed to understand the critical concepts of data mining, machine learning and predictive analytics used in the visualisation and analysis of data, particularly Big data. Students will gain an understanding of data preparation, the process models used in analytics, the algorithms and their requirements, the implementation of these algorithms using current technologies, and their applicability to different types of scenario. They will also gain advanced practical skills in the design, implementation and evaluation of analytical solutions to problems involving Big Data.
Big Data Platforms
This module covers the platforms that support data storage, processing and analytics in Big Data scenarios. It focuses on highly scalable platforms that provide operational capabilities for real-time, interactive processing and on platforms that provide analytical capabilities for retrospective, complex analysis. Students will gain an advanced understanding of the principles on which these platforms are based, and their strengths, weaknesses and applicability to different types of scenario. They will also gain advanced practical skills in the design and implementation of scalable Big Data platform solutions.
Internet of Things
This module provides fundamental and practical coverage of the set of converging technologies known as the Internet of Things (IoT). It focuses on representative IoT applications, technologies, frameworks and associated standards that support and underpin IoT applications, such as sensor networks, messaging protocols, security, data storage, analytics, services and human interaction. The module provides in-depth practical coverage of representative IoT implementation frameworks including cloud-based service delivery models.
IT Professional Issues and Project Methods
This module seeks to develop understanding and practical skills in advanced project methods which are inline with industry regulations, standards and practices and are applicable to complex IT projects. Study is undertaken in an integrated fashion to ensure that the professional frameworks within which such projects are developed, deployed and managed are fully understood.
Masters Dissertation
Students will investigate a topical or emerging theme in Cloud Computing or related technologies. The dissertation acts as a vehicle for extending the knowledge and understanding of the student and the technical community in some specialist technical area. It serves through its length, complexity and rigour as a suitable vehicle for extending students' range of personal, interpersonal and communication skills. In addition it serves to develop and extend a range of high-level thinking skills, including analysing and synthesising skills and affords the opportunity for the student to demonstrate initiative and creativity in a major piece of technical work.
Students will be made aware of placement opportunities provided by our industry partners. Typically a placement would be undertaken after graduating from the MSc programme but opportunities can sometimes be made available for students to undertake their MSc Dissertation in partnership with a commercial company.
The methods of assessment include class tests, coursework assignments, practical tests and technical reports. Practical implementation and evaluation form a significant part of the assessment for the taught modules and for the work of the MSc dissertation.
When you graduate, you'll be a competitive candidate for roles as a systems developer, architect or administrator in data and analytics. You'll find opportunities in a diverse range of industries: engineering, pharmaceuticals, finance, healthcare, retail, security, smart environments and more.
Learn how to overcome the major challenges facing industry, business and the public sector today, and influence the decision-making processes of the future.
We run a core module on Data Analytics which will introduce students to SAS Enterprise. A coursework prize for this project will be sponsored by SAS.
Recent highlights included a case study run by British Airways, a presentation from SAS on the Future of Analytics and ongoing dissertation projects with Unilever and LBM.
Assessment varies depending on course units taken. It may include a combination of course work, group project assessment and presentations, report, assignments, in-class tests and examination. The dissertation normally ranges between 12,000 and 25,000 words.
During the course you will be taking 180 credits in all. The eight taught modules during semester one and two total 120 credits and consists of both compulsory and optional taught units which can be viewed in the list below.
The core courses unit introduce you to mathematical principles and practical tools for Optimization, Decision Making, Data-Mining, Statistical Analysis, Simulation and Risk Analysis. Specific software packages include SAS, SPSS, Minitab, AMOS, Eviews, Excel, Excel Solver, SIMUL8, iThink, Risk Solver, IDS.
Over the summer period, you will carry out your Research Dissertation, worth 60 credits. Examples of recent dissertation project topics include:
Contact us for further information on scholarships available .
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
There are many potential career roles for postgraduates with an understanding of analytical approaches in business and management - including job titles such as operational research analyst, systems analyst, risk analyst, financial analyst, performance analyst, business analyst, marketing analyst, business modeller, and operations, logistics, production, project, risk, quality, performance, or general manager. Employers include general and specialist consultancies, the finance, retail and manufacturing sectors, government analytics units, defence and major 'solution providers' in IT systems, outsourcing and telecoms.
In many of these areas an MSc is generally accepted as highly desirable for developing an initial career in the field. In addition to preparing you for specialist professional work, the course is also a valuable preparation for further study and for research degrees.
More details on our Careers Service.
Latest information on visa changes and opportunities in the UK for international students.
This exciting and challenging programme studies how data can be utilised to solve major business and societal challenges. The programme provides students with the knowledge, technical ability and skills for leadership roles in the fields of business analytics and data science.
The programme is designed to give students multidisciplinary skills in computing (i.e. programming, big data), analytics (i.e. data mining, machine learning, computational statistics, complexity), and business analysis. Emphasis will be on business problem framing, leveraging data as a strategic asset, and communicating complex analytical results to stakeholders.
Students undertake modules to the value of 180 credits.
The programme consists of three core modules (45 credits), four or five optional modules (60 to 75 credits), up to one elective module (15 credits) and a dissertation (60 credits).
Core modules
Optional modules
Students must choose a minimum of 60 and a maxuimum of 75 credits from Optional modules. A maximum of 15 credits may be taken from Electives.
Please note: the availability and delivery of optional modules may vary, depending on your selection.
A list of acceptable elective modules is available on the Departmental page.
Dissertation/report
During the summer students will undertake a work placement with a UCL industrial partner. The research and data analysis conducted during this placement will form the basis of a 10,000-word dissertation.
Teaching and learning
The programme is delivered through a combination of lectures by world-class academics and industry leaders, seminars, workshops, tutorials and project work. The programme comprises two terms of taught material, followed by examinations and then a project. Assessment is through unseen written examinations, coursework and the dissertation.
Further details are available on UCL Computer Science website.
Further information on modules and degree structure is available on the department website: Business Analytics (with specialisation in Computer Science) MSc
Graduates of UCL Computer Science are particularly valued due to the department's international status and strong reputation for leading research. Recent graduate destinations include such companies as: IBM, Samsung, Microsoft, Price Waterhouse Coopers, Citibank.
Employability
This programme is designed to satisfy the need, both nationally and internationally, for exceptional data scientists and analysts. Graduates will be highly employable in global companies and high-growth businesses, finance and banking organisations, major retail and service companies, and consulting firms. They will be equipped to influence strategy and decision-making, and be able to drive business performance by transforming data into a powerful and predictive strategic asset. We expect our graduates to progress to leading and influential positions in industry.
UCL Computer Science is a global leader in research in experimental computer science. The department scored highest among UK universities for the quality of research in Computer Science and Informatics in the Research Excellence Framework (REF2014), with 96% regarded as 'world-leading' or 'internationally excellent'.
The department consists of a team of world-class academics specialising in big data, computational statistics, machine learning and complexity.
The programme aims to create the next generation of outstanding academics and industry pioneers, who will use data analysis to deliver real social and business impact.
The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.
The following REF score was awarded to the department: Computer Science
96% rated 4* (‘world-leading’) or 3* (‘internationally excellent’)
Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.
Hult's Masters in Business Analytics is offered in San Francisco.
Hult’s San Francisco campus, located right at the center of the city at the base of iconic Telegraph Hill, and has an edgy, startup vibe.
As the role of big data becomes increasingly important, a one-year Hult Masters in Business Analytics degree equips you with the analytical and business capability to translate data statistics and analysis into action.
Who is this program for?
Candidates who have recently graduated from university or college, as well as individuals with up to three years of work experience who want to influence business decisions and strategy through harnessing the predictive capabilities of data and business analytics.
Non-U.S. residents who receive a Masters in Business Analytics will also qualify for up to three years of OPT (Optional Practical Training) in the U.S. after their studies. OPT is normally 12 months, so the degree is particularly well-suited to those hoping to experience work in the U.S. after their degree. For more details, please contact us.
Campus: San Francisco
What you’ll learn
Companies such as Google, Facebook, and Amazon have demonstrated the profitability of harnessing the predictive power of large-scale consumer data. In this new world of information overload, employers actively seek candidates who have the ability to translate data into actionable solutions. Hult’s one-year Masters in Business Analytics degree will place you at the intersection of statistical analysis and business knowledge so that you can make meaningful and impactful contributions.
Potential careers
Navigating an international job search requires an individual approach. At Hult, we are experts in international student placement and work one-on-one with you to craft a tailored career strategy.
Before you start your program at Hult, you'll have access to software that gives you a line-by-line resume review, webinars on resume writing, global market employment trends, and creating a targeted job-search strategy. So when you arrive on campus you can concentrate on your studies, networking opportunities, and begin your job search straight away.
Coaching
Throughout your program, you'll attend workshops and coaching sessions to equip you with essential knowledge and skills in areas like LinkedIn optimisation, personal branding, negotiations, interview preparation, and job search strategy.
Advice
You'll be assigned a personal Careers Advisor who will work with you one-on-one to help you position yourself to enter your target location and industry. They can advise you on everything from visas to job applications and long-term career paths. You also have the opportunity to have an alumni mentor.
Events
There is a packed schedule of career events that bring companies to campus to present, network, and recruit, as well as alumni mixers, expert guest speakers, and career open house events.
Your career development doesn't stop when you graduate and neither does Hult's support.
Constantly stay connected
Your alumni network is one of your biggest assets. Hult Connect is an online portal that allows you to link with the 16,000 Hult alumni working in every major industry in every corner of the world. You'll also have access to our global job board so you can continue to take advantage of our relationship with the world's top employers seeking talent. Hult's Alumni Mentorship Program provides you with an opportunity to be a part of coaching the next generation of leaders coming out of Hult.
