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Masters Degrees (Predictive Analytics)

We have 24 Masters Degrees (Predictive Analytics)

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The digital revolution has led to an unprecedented volume of information about consumers, which progressive organisations are eager to understand and use. Read more

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.

Course content

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.

Course structure

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.

  • Geographic Data Visualisation & Analysis 15 credits
  • Big Data and Consumer Analytics 15 credits
  • Predictive Analytics 15 credits
  • Applied GIS and Retail Modelling 15 credits
  • Business Analytics and Decision Science 15 credits
  • Consumer Behaviour 15 credits
  • Marketing Research Consultancy Project 15 credits
  • Direct, Digital and Interactive Marketing 15 credits
  • Marketing Strategy 15 credits
  • Dissertation OR Marketing Consultancy Project 30 credits

Optional modules

You'll take one further optional module.

  • Applied Population and Demographic Analysis 15 credits
  • Corporate Social Responsibility and Sustainability 15 credits
  • Internal Communications and Change Management 15 credits

For more information on typical modules, read Consumer Analytics and Marketing Strategy MSc in the course catalogue

Learning and teaching

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

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.

Career opportunities

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.

Careers support

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.



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Programme description. 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. Read more

Programme description

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.

Programme structure

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.

Learning outcomes

General Educational aims are to:

  • Enable all participants to recognise, understand and apply the language, theory and models of the field of business analytics.
  • Foster an ability to critically analyse, synthesise and solve complex unstructured business problems.
  • Encourage an aptitude for business improvement, innovation and entrepreneurial action.
  • Encourage the sharing of experiences to enhance the benefits of collaborative learning.
  • Instil a sense of ethical decision-making and a commitment to the long-run welfare of both organisations and the communities that they serve.

Specific Educational aims are to:

  • Understand and critically apply the concepts and methods of business analytics.
  • Identify, model and solve decision problems in different settings
  • Interpret results/solutions and identify appropriate courses of action for a given managerial situation whether a problem or an opportunity.
  • Create viable solutions to decision making problems.

Career opportunities

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.



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About the programme. 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. Read more

About the programme

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.

Programme syllabus

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.



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Why choose the MSc in Business Analytics?. Do you want to be a professional analyst who understand both the technologies and the business?. Read more

Why choose the MSc in Business Analytics?

  • Do you want to be a professional analyst who understand both the technologies and the business?
  • Do you want to master the skills in making data-driven business decisions?
  • Do you want to learn the practical use of data visualization tools, statistical analysis tools, and big data technologies?

What is business analytics?

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.

Programme overview

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).

Teaching and Learning

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.

Career options for this degree

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:

  • Find a job in the business firms that require the knowledge of big data and advanced analytic techniques.
  • Study the organisations, management, and international external environments.
  • Gain business insights and professional skills in data mining, data visualization, data management, process modeling, predictive and advanced analytics.
  • Develop the ability to optimize the business processes and management practice.
  • Contribute to business and society at large.

What are the potential careers of our graduates?

  • Business intelligence analytics,
  • Marketing analyst
  • Business systems analyst
  • Data scientist
  • Business consultant
  • Solution Architects


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Gain in-depth knowledge of analytical and predictive modelling skills as well as management, communication and research skills. Read more
Gain in-depth knowledge of analytical and predictive modelling skills as well as management, communication and research skills.

In the era of Big Data, analytics is becoming a strategic necessity in virtually all areas of business and is an essential tool to drive real-time decisions, foster evidence-based decision-making and sustain competitive advantage. According to a recent ranking by US News and World Report, Market Research Analyst and Operations Research Analyst are in the top four Best Business Jobs of 2015, and Harvard Business Review claims Data Scientist is the 'sexiest job of the 21st century' with practitioners having rare and highly sought-after skills.

To meet the growing demand for graduates with analytics capabilities, the MSc in Business Analytics degree equips you with the latest analytics tools to analyse and interpret data, forecast future trends, automate and streamline decisions, and optimise courses of action. Emphasis is placed on learning fundamental analytics techniques, such as statistical analysis, data mining, forecasting and regression, optimisation, simulation and spreadsheet modelling among others.

You will learn how to apply descriptive, predictive and prescriptive modelling techniques to help organisations improve performance, explore alternatives, and anticipate and shape business outcomes in a rapidly changing environment. Upon graduation, you will be ready to start a fast-track career in a variety of industries and sectors including airlines, manufacturing companies, energy, healthcare delivery, banking, marketing and government.

Students enrolled in the programme have the opportunity to work for real organisations, improve their consultancy skills and enhance their employability through the Student Implant Scheme, which bridges the gap between classroom learning and the real world. Students are also involved in a variety of activities, including case studies, team project work, guest lectures and industry visits.

Software demonstration workshops supported by IBM/ILOG are regularly organised to support the teaching of state-of-the-art analytics packages including IBM Watson Analytics, R, SPSS, Weka, MS Excel and VBA, as well as optimisation packages including Optimization Programming Language, IBM/ILOG, CPLEX and Simul8.

This programme is ideal for graduates with a good background in a quantitative area who are seeking to gain an in-depth knowledge of analytical and predictive modelling skills as well as management, communication and research skills.

Visit the website https://www.kent.ac.uk/courses/postgraduate/292/business-analytics

About Kent Business School

Kent Business School has over 25 years’ experience delivering business education. Our portfolio of postgraduate programmes (http://www.kent.ac.uk/kbs/courses/msc/index.html) demonstrates the breadth and depth of our expertise. Academic research and links with global business inform our teaching, ensuring a curriculum that is relevant and current. We are ranked (http://www.kent.ac.uk/kbs/whychooseus/rank-accred.html) as a top 30 UK business school for the standard of our teaching and student satisfaction. We also hold a number of accreditations (http://www.kent.ac.uk/kbs/whychooseus/rank-accred.html?tab=accreditations-and-professional-bodies) by professional bodies.

Studying at Kent Business School (KBS) gives you the opportunity to increase your employability with real-life case studies, a student council and a business society. We have strong links to local and national organisations providing opportunities for projects, internships and graduate placements. The School attracts many high-profile speakers from industry and last year included visits and lectures from staff of the Bank of England, BAE Systems, Barclays, Lloyds Insurance, Cummins, Delphi and Kent County Council.

Careers

You gain much more than an academic qualification when you graduate from Kent Business School – we enhance your student experience and accelerate your career prospects.

From the moment you start with us, our efforts are focused on helping you gain the knowledge, skills and experience you need to thrive in an increasingly competitive workplace.

In today’s business climate employers are increasingly demanding more from new employees, we are therefore proud that they continually target our graduates for their organisations across the globe. Employers respect our robust teaching and reputation for delivering international business expertise, leading global research and an outstanding international learning experience.

Recent graduates have gone on to work for Barclays Capital, British Embassy, Gray Robinson PA and Holiday Extras.

To find out more about business analytics and future career prospects, see the following links.

- OR Society: British Society of Operational Research: http://www.theorsociety.com/

- What is OR? Video and success stories: http://www.learnaboutor.co.uk/

Professional recognition

Kent Business School is a member of the European Foundation for Management Development (EMFD), CIPD, CIM and the Association of Business Schools (ABS). In addition, KBS is accredited by the Association of MBAs (AMBA).

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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Learn how to overcome the major challenges facing industry, business and the public sector today, and influence the decision-making processes of the future. Read 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.

  • Gain a solid theoretical foundation and quantitative skills, alongside practical problem-solving techniques
  • Apply your knowledge to real-life scenarios using case studies, individual and team consulting-based assignments, presentations and software tools
  • Use SAS Enterprise as part of the `Data Analytics for Business Decision Making' unit. SAS sponsor a coursework prize for this project
  • Choose from a broad range of options to meet your interests or career aspirations
  • Prepare for a career in consultancy, finance, retail, manufacturing, government analytics units, defence, IT systems, outsourcing and telecoms.

Special features

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.

Coursework and assessment

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.

Course unit details

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:

  • Web analytics for evaluating online user experience
  • Capacity management of product test equipment
  • Risk management in the hotel industry 
  • Equity forecasting using ARIMA and neural networks
  • Predictive modelling: A case study for selling additional contracts to existing customers in the telecommunications industry

Scholarships and bursaries

Contact us for further information on scholarships available .

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: 

Career opportunities

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.



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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. Read more

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.

About this degree

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

  • Business Strategy and Analytics (15 credits)
  • Data Analytics (15 credits)
  • Programming for Business Analytics (15 credits)

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.

  • Consulting Psychology (15 credits)
  • Consumer Behaviour (15 credits)
  • Data Science for Spatial Systems (15 credits)
  • Decision and Risk (15 credits)
  • Decision and Risk Analysis (15 credits)
  • Group Mini Project: Digital Visualisation (30 credits)
  • Introduction to Machine Learning (15 credits)
  • Mastering Entrepreneurship (15 credits)
  • Statistical Design of Investigations (15 credits)
  • Statistical Models and Data Analysis (15 credits)
  • Talent Management (15 credits)
  • Urban Simulation (15 credits)
  • Web Economics (15 credits)

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

Careers

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.

Why study this degree at UCL?

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.

Research Excellence Framework (REF)

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.



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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. Read more

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.

  • Experience a startup-driven environment in a city that epitomizes the entrepreneurial spirit 
  • Network in the city that’s home to the biggest break-through companies of this century 
  • See the latest trends in the digital innovation capital of the world

Curriculum

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

  • Business Intelligence Analyst
  • Business Insights Analyst
  • Commercial Insights Manager
  • Business Analyst
  • Data Science Manager
  • Risk Analyst
  • Data Analyst 

Career development

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.

  • Line-by-line resume reviews
  • Webinars on global employment trends, personalizing your job search, and how to get your resume to a globally competitive standard
  • Interactive sessions with expert Careers Advisors 

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.

Post-graduation

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.

  • Hult Connect, the online portal for our 16,000+ alumni network
  • Alumni Mentorship Program
  • Global job board and networking events


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Whether you are looking to start a career in data science or wanting to further develop your current career, our innovative online Masters programme in Data Analytics provides you with vital data science skills. Read more

Whether you are looking to start a career in data science or wanting to further develop your current career, our innovative online Masters programme in Data Analytics provides you with vital data science skills. This skills-based, yet rigorous curriculum provides you both with a thorough foundation in the underlying principles of learning from data and practical technical expertise in data handling, visualisation and modelling. The programme uses cutting-edge learning technology to deliver an interactive and collaborative online learning experience. Community building and collaborative learning is a key focus of our online delivery and you will be encouraged and supported to interact with your fellow classmates and tutors in a variety of ways throughout the duration of the course.

Why this programme?

  • The University of Glasgow’s School of Mathematics and Statistics is ranked 3rd in Scotland and 16th in the UK (Complete University Guide 2018).
  • The Statistics Group at Glasgow is the largest statistics group in Scotland and internationally renowned for its research excellence.
  • You will obtain an MSc degree from a world renowned university while being in full-time employment (around 10 hours of study per week).
  • You can personalise your learning by having the freedom to work at your own pace.
  • You can take advantage of rich interactive reading material, tutor-led videos and computer-led programming sessions.

Programme Stucture

This flexible part-time programme is completed over three years. In the first two years you will be taking two courses each trimester. In the third year you will be working on a project and dissertation.

The courses are designed to allow you to work at your own pace, with milestones and assessment to be completed according to an agreed timetable.

Core courses

  • Stochastic Models and Probability
  • Learning from Data
  • Predictive Models
  • R Programming
  • Data Programming in Python
  • Data Management and Analytics using SAS
  • Advanced Predictive Models
  • Data Mining and Machine Learning I: Supervised and Unsupervised Learning
  • Data Mining and Machine Learning II: Big and Unstructured Data
  • Uncertainty Assessment and Bayesian Computation
  • High-performance Computing for Data Analytics
  • Data Analytics in Business and Industry

You will also carry out a 60 credit research project.

In the first year of the programme you will need to take three paper-based examinations, held on the second Monday of May and the following Tuesday. UK-based students will have to take these examinations in Glasgow. Students from abroad can choose to either travel to Glasgow or take the examination in a local test centre, such as British Council offices. Test centres are subject to approval by the University and the candidate is responsible for any local fees charged by the test centre.

Career prospects

Data is becoming an ever increasing part of the modern world, yet the talent to extract information and value from complex data is scarce. There is a massive shortage of data-analytical skills in the workforce. Statistical Analysis and Data Mining was listed by LinkedIn as the hottest skill in 2014 and came second in 2015 and 2016. This programme opens up a multitude of career opportunities and/or boosts your career trajectory.

Graduates from the programmes in our School have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance, business consulting and government statistical services, while others have continued on to a PhD. 



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Since the world went online, information has grown rapidly in volume and become infinitely more accessible. At the same time, information science and systems have been converging towards a common focus on information discovery, organisation, and management. Read more
Since the world went online, information has grown rapidly in volume and become infinitely more accessible. At the same time, information science and systems have been converging towards a common focus on information discovery, organisation, and management. Information management is essential in libraries, archives, museums and business, and is a much sought-after skill in careers spanning the sectors for example, in governmental, legal, financial, media and publishing organisations. Meanwhile, owners and users of information need to be able to access and evaluate information in faster and more intuitive ways.

Key benefits

This course is accredited by The Chartered Institute of Library and Information Professionals (CILIP).

Course detail

The MSc Information Management is vocational and practice-oriented, designed to support information and knowledge managers. The course provides an excellent balance of traditional information management and library science, informed by cutting edge developments in information architecture and data management. It's an important route for anyone seeking professional chartership or progress to management roles.

Modules

• Information Contexts (30 credits)
• Knowledge Organisation (30 credits)
• Information and Digital Literacy (15 credits)
• Personal and Organisational Management (15 credits)
• Information and Knowledge Management
• Data Management
• Designing The User Experience
• Big Data
• Cloud Computing
• Linked, Open Data and The Internet of Things
• Machine Learning and Predictive Analytics
• Social Media and Web Science
• Dissertation

Format

You'll learn through lectures, discussions, tutorials, practical exercises and independent reading, as well as working together in small groups.

The course has a virtual learning environment online that supports you throughout your studies. It's a useful way to communicate with fellow students and teaching staff, find administrative details about the modules, and access course materials.

We regularly welcome specialist tutors to the department to contribute to specific modules.

Assessment

Assessment in most modules is through written coursework, portfolios, presentations and written exams. The supervisor and second marker will assess your dissertation.

Careers / Further study

This qualification is an excellent route to range of careers, and as a complement to existing career skills and professional development for example, for those moving into managerial roles. Our graduates have gone on to successful careers in a wide range of sectors, including educational, public sector and museum archivist roles, plus a variety of consultancy and professional services positions.

Alumni have prominent roles in local library services, university libraries in Bristol and Bath, with the government, and in records management roles in public and private sectors.

For anyone looking to pursue PhD research positions, this course is considered a highly valuable preparatory route.

How to apply

Information on applications can be found at the following link: http://www1.uwe.ac.uk/study/applyingtouwebristol/postgraduateapplications.aspx

Funding

- New Postgraduate Master's loans for 2016/17 academic year –

The government are introducing a master’s loan scheme, whereby master’s students under 60 can access a loan of up to £10,000 as a contribution towards the cost of their study. This is part of the government’s long-term commitment to enhance support for postgraduate study.

Scholarships and other sources of funding are also available.

More information can be found here: http://www1.uwe.ac.uk/students/feesandfunding/fundingandscholarships/postgraduatefunding.aspx

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The MSc Information Technology prepares you for the intellectual, analytical and practical challenges of a career in IT. Read more
The MSc Information Technology prepares you for the intellectual, analytical and practical challenges of a career in IT. You will develop the knowledge and skills necessary to collate information, define, design and build or select the most appropriate IT solutions and develop a deeper understanding of how those solutions apply to professional contexts.

You can study part-time whilst in full-time employment, as there are few pre-requisites for most modules.

Key benefits

The British Computer Society's Professional Graduate Diploma (PGD) is accepted as an appropriate entry qualification for this course. The PGD is also accepted as advanced standing to IT-related undergraduate degrees at UWE Bristol.

Course detail

Upon graduation, you will be able to critically evaluate developments and new applications of information and communication technology systems, and relate them to the roles and uses of IT in different business settings. You will also have an enhanced understanding of system problems and how to choose the right methods and approaches to develop systems. From engaging in primary research for the dissertation and studying relevant literature, you will learn to recognise what constitutes suitable research questions or hypotheses and the appropriate perspectives for analysis.

Structure

The full Masters course is made up of 180 credits divided into three 60 credit stages: Postgraduate Certificate, Postgraduate Diploma and Masters. You will work incrementally through the three stages and need to pass all modules at each stage to be able to progress onto the next.

The MSc route is structured so that three quarters of the taught course comprises core modules, while you choose the rest to fit your personal and professional aspirations and career goals. In the first term, there are four core modules, followed by one core module and two optional ones in the second term.

Modules

Core modules:

• Professionalism And Governance In IT (15 credits)
• Project Management (15 credits)
• Information Security (15 credits)
• Digital Design and Development (15 credits)
• Group Software Development Project (30 credits)

Optional modules:

• Information and Knowledge Management
• Data Management
• Designing The User Experience
• Cloud Computing
• Linked, Open Data and The Internet of Things
• Machine Learning And Predictive Analytics
• Social Media And Web Science
• Big Data

Format

You learn through taught classes supported by independent study, and we provide considerable material online, via UWE Bristol's virtual learning environment, Blackboard.

Assessment

Assessment is through coursework and exams, and the dissertation.

Careers / Further study

UWE Bristol monitors its employment trends closely, and since 1986, we have ensured graduates of this course are equipped for the demands of the real world and are highly regarded by potential employers.

There is a growing need for creative IT graduates who can work with an ever-widening range of technologies and can meet organisational needs in business, education and health. This newly designed course tackles the challenges of technology in modern business and society, head on.

How to apply

Information on applications can be found at the following link: http://www1.uwe.ac.uk/study/applyingtouwebristol/postgraduateapplications.aspx

Funding

- New Postgraduate Master's loans for 2016/17 academic year –

The government are introducing a master’s loan scheme, whereby master’s students under 60 can access a loan of up to £10,000 as a contribution towards the cost of their study. This is part of the government’s long-term commitment to enhance support for postgraduate study.

Scholarships and other sources of funding are also available.

More information can be found here: http://www1.uwe.ac.uk/students/feesandfunding/fundingandscholarships/postgraduatefunding.aspx

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The Online MSc in Data Analytics covers 18 5-credit modules, two per semester over 9 semesters or 3 years, of which the Online Professional Diploma in Data Analytics covers the first 4. Read more
The Online MSc in Data Analytics covers 18 5-credit modules, two per semester over 9 semesters or 3 years, of which the Online Professional Diploma in Data Analytics covers the first 4. This first year is designed to introduce you to statistical and mathematical concepts in Data Analytics and Data Mining, and to get you started on programming with data. The second year is split between understanding the theory behind statistical and mathematical models for data via predictive analytics, and dealing with data sets at scale using Python and multivariate techniques. The final year covers some advanced methods: Monte Carlo, Bayesian Analysis, Time Series Data, and Complex Stochastic models. A provisional list of topics is as follows:

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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. Read more

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.

About this degree

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

  • Business Strategy and Analytics
  • Marketing Analytics
  • Mathematical Foundations for Business Analytics
  • Programming for Business Analytics
  • Predictive Analytics
  • Operations Analytics

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

Careers

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.

Why study this degree at UCL?

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.

Research Excellence Framework (REF)

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.



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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. Read more

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.

  • Apply leading-edge tools and technologies from companies such as IBM, Microsoft and SAS
  • Explore industry-standard open-source development platforms such as Hadoop
  • Achieve industry recognition with SAS joint certification in the programme's Data Analytics module

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.

What you will study

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.

Work placements

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.

Assessment methods

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.

Graduate prospects

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.



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The MS program in applied statistics is available to both full- and part-time students with courses available both on-campus and online. Read more

Program overview

The MS program in applied statistics is available to both full- and part-time students with courses available both on-campus and online. Cooperative education is optional. The program is intended for students who do not wish to pursue a degree beyond the MS. However, a number of students have attained doctorate degrees at other universities.

Plan of study

The program requires 30 credit hours and includes four core courses, five electives, and a capstone or thesis.

Core courses

There are four required core courses. Students, in conjunction with their advisers’ recommendations, should take the core courses early in the program.

Curriculum

Applied statistics, MS degree, typical course sequence:
First Year
-Statistical Software
-Fundamentals of Statistical Software
-Regression Analysis
-Foundations of Experimental Design
-Electives
Second Year
-Electives
-Capstone

Concentration areas

-Predictive Analytics
-Data Mining/Machine Learning
-Industrial
-Biostatistics
-Theory

Electives, capstone or thesis

Elective courses are chosen by the student with the help of their adviser. These courses are usually department courses but may include (along with transfer credits) up to 6 credit hours from other departments that are consistent with students’ professional objectives. The capstone course is designed to ensure that students can integrate the knowledge from their courses to solve more complex problems. This course is taken near the end of a student’s course of study. Students, with adviser approval, may write a thesis as their capstone.

Other admission requirements

-Have a satisfactory background in mathematics (one year of university-level calculus) and statistics (preferably two courses in probability and statistics).
-Submit official transcripts (in English) of all previously completed undergraduate and graduate course work.
-Submit a current resume.
-Submit two letters of recommendation, and complete a graduate application.
-International students whose native language is not English must submit scores from the Test of English as a Foreign Language (TOEFL).
-Scores from the Graduate Record Exam (GRE) are not required, however submitting scores may support the admission of an applicant who is deficient in certain admission requirements.

Additional information

Grades:
Students must attain an overall program grade-point average of 3.0 (B) for graduation.

Maximum time limit:
University policy requires that graduate programs be completed within seven years of the student's initial registration for courses in the program. Bridge courses are excluded.

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