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Masters Degrees (Predictive)

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The Predictive Modelling MSc is designed for those wishing to develop the skills and depth of knowledge to deal with the integration of Big Data with mathematical and statistical simulation tools in order to model and design complex systems in the presence of uncertainties. Read more
The Predictive Modelling MSc is designed for those wishing to develop the skills and depth of knowledge to deal with the integration of Big Data with mathematical and statistical simulation tools in order to model and design complex systems in the presence of uncertainties. The course will prepare you in the theory and practical implementation of cutting-edge predictive modelling techniques, exposing you to established and emerging applications.

Course Structure

The MSc runs over one year. The taught part consists of six 15-credit modules. Of those, three are core modules offered by the WCPM. Three more can be selected from relevant departments across the university. The second half of the course consists of a 90 credit individual research project, selected from a combined list from Engineering, Physics, Chemistry, Life Sciences, Social Sciences, Mathematics, Statistics, Computer Science, Warwick Business School, Warwick Manufacturing Group and the Centre for Scientific Computing.

You will also undertake a substantive individual research project involving a theoretical or computational investigation of a topic chosen by the student in conjunction with an academic supervisor.

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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 create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans. Read more

Learn how to create artificial information systems that mimic biological systems as well as how to use theoretical insights from AI to better understand cognitive processing in humans.

The human brain is a hugely complex machine that is able to perform tasks that are vastly beyond current capabilities of artificial systems. Understanding the brain has always been a source of inspiration for developing artificially intelligent agents and has led to some of the defining moments in the history of AI. At the same time, theoretical insights from artificial intelligence provide new ways to understand and probe neural information processing in biological systems.

On the one hand, the Master’s in Neural Computing addresses how models based on neural information processing can be used to develop artificial systems, such as neuromorphic hardware and deep neural networks, as well as the development of new machine learning and classification techniques to better understand human brain function and to interface brain and computer.

On the other hand it addresses various ways of modelling and understanding (the limitations of) cognitive processing in humans. These range from abstract mathematical models of learning that are derived from Bayesian statistics to resource-bounded computations in the brain, explainable AI, and neural information processing systems such as neural networks that simulate particular cognitive functions in a biologically inspired manner.

See the website http://www.ru.nl/english/education/masters/neural-computing/

Why study Neural Computing at Radboud University?

- Our cognitive focus leads to a highly interdisciplinary AI programme where students gain skills and knowledge from a number of different areas such as mathematics, computer science, psychology and neuroscience combined with a core foundation of artificial intelligence.

- Together with the world-renowned Donders Institute, the Behavioural Science Institute and various other leading research centres in Nijmegen, we train our students to become excellent researchers in AI.

- Master’s students are free to use the state-of-the-art facilities available on campus, like equipment for brain imaging as EEG, fMRI and MEG.

- Exceptional students who choose this specialisation have the opportunity to study for a double degree in Artificial Intelligence together with the specialisation in Brain Network and Neuronal Communication. This will take three instead of two years.

- To help you decide on a research topic there is a semi-annual Thesis Fair where academics and companies present possible project ideas. Often there are more project proposals than students to accept them, giving you ample choice. We are also open to any of you own ideas for research.

- Our AI students are a close-knit group; they have their own room in which they often get together to interact, debate and develop their ideas. Every student also receives personal guidance and supervision from a member of our expert staff.

Our research in this field

The programme is closely related to the research carried out in the internationally renowned Donders Institute for Brain, Cognition and Behaviour. This institute has several unique facilities for brain imaging using EEG, fMRI and MEG. You will be able to use these facilities for developing new experimental research techniques, as well as for developing new machine learning algorithms to analyse the brain data and integrate them with brain-computer interfacing systems.

- Deep learning

Recent breakthroughs in AI have led to the development of artificial neural networks that achieve human level performance in object recognition. This has led companies like Google and Facebook to invest a lot of research in this technology. Within the AI department you can do research on this topic. This can range from developing deep neural networks to map and decode thoughts from human brain activity to the development of speech recognition systems or neural networks that can play arcade games.

-Computational framework for counterfactual predictive processing

In a recent paper we introduced a computational framework, based on causal Bayesian networks, to computationally flesh out the predictive processing processing framework in neuroscience. In this project we want to extend this to so-called counterfactually rich generative models in predictive processing. Such models encode sensorimotor contingencies, that is, they represent 'what-if' relations between actions and sensory inputs. We aim to further operationalize this account using Pearl's intervention and counterfactual semantics. In this project you will combine formal computational modelling with conceptual analysis. 

- Brain Computer Interfacing

Brain computer interfaces are systems which decode a users mental state online in real-time for the purpose of communication or control. An effective BCI requires both neuro-scientific insight and technical expertise . A project could be to develop new mental tasks that induce stronger/easier to decode signals, such as using broadband stimuli. Another project could be to develop new decoding methods better able to tease a weak signal from the background noise, such as adaptive-beam forming. Results for both would assessed by performing empirical studies with target users in one of the EEG/MEG/fMRI labs available in the institute.

Career prospects

Our Artificial Intelligence graduates have excellent job prospects and are often offered a job before they have actually graduated. Many of our graduates go on to do a PhD either at a major research institute or university with an AI department. Other graduates work for companies interested in cognitive design and research. Examples of companies looking for AI experts with this specialisation: Google, Facebook, IBM, Philips and the Brain Foundation. Some students have even gone on to start their own companies or joined recent startups.

Job positions

Examples of jobs that a graduate of the specialisation in Computation in Neural and Artificial Systems could get:

- PhD researcher on bio-inspired computing

- PhD researcher on neural decoding

- PhD researcher on neural information processing

- Machine learning expert in a software company

- Company founder for brain-based computer games

- Hospital-based designer of assistive technology for patients

- Policy advisor on new developments in neurotechnology

- Software developer for analysis and online visual displays of brain activity

Internship

Instead of an extended research project (45 ec) you can also choose to do a smaller (30 ec) research project plus a 15 ec internship, giving you plenty of hands-on experience with AI. We encourage students to do this internship abroad.



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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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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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The Department of Oncology and the Department for Continuing Education’s CPD Centre offer a part-time MSc in Experimental and Translational Therapeutics that brings together some of Oxford's leading clinicians and scientists to deliver an advanced modular programme designed for those in full-time employment, both in the UK and overseas. Read more

The Department of Oncology and the Department for Continuing Education’s CPD Centre offer a part-time MSc in Experimental and Translational Therapeutics that brings together some of Oxford's leading clinicians and scientists to deliver an advanced modular programme designed for those in full-time employment, both in the UK and overseas.

The Programme draws on the world-class research and teaching in experimental therapeutics at Oxford University and offers a unique opportunity to gain an understanding of the principles that underpin clinical research and to translate this into good clinical and research practice.

Visit the website https://www.conted.ox.ac.uk/about/msc-in-experimental-therapeutics

The deadline for applications is Friday 15 June 2018

If your application is completed by this January deadline and you fulfil the eligibility criteria, you will be automatically considered for a graduate scholarship. For details see: http://www.ox.ac.uk/admissions/graduate/fees-and-funding/graduate-scholarships.

Programme details

The MSc in Experimental and Translational Therapeutics is a part-time course consisting of six modules and a research project and dissertation. The programme is normally completed in two to three years. Students are full members of the University of Oxford and are matriculated as members of an Oxford college.

The modules in this programme can also be taken as individual short courses. It is possible to transfer credit from up to three previously completed modules into the MSc programme, if the time elapsed between commencement of the accredited module(s) and registration for the MSc is not more than two years.

Programme modules:

- The Structure of Clinical Trials and Experimental Therapeutics

- Drug Development, Pharmacokinetics and Imaging

- Pharmacodynamics, Biomarkers and Personalised Therapy

- Adverse Drug Reactions, Drug Interactions, and Pharmacovigilance

- How to do Research on Therapeutic Interventions: Protocol Preparation

- Biological Therapeutics

Course aims

The aim of the MSc programme is to provide students with the necessary training and practical experience to enable them to understand the principles that underpin clinical research, and to enable them to translate that understanding into good clinical and research practice.

By the end of the MSc programme, students should understand the following core principles:

- Development, marketing and regulations of drugs

- Pharmaceutical factors that affect drug therapy

- Pharmacokinetics, pharmacogenetics and pharmacodynamics

- Adverse drug reactions, drug interactions, and pharmacovigilance

- Designing phase I, II and III clinical trials for a range of novel therapeutic interventions (and imaging agents).

- Application of statistics to medicine

- Laboratory assays used to support trial end-points

- Use of non-invasive imaging in drug development

- Application of analytical techniques

By the end of the programme, students should be equipped to:

- demonstrate a knowledge of the principles, methods and techniques for solving clinical research problems and translate this into good clinical and research practice

- apply skills gained in techniques and practical experience from across the medical and biological sciences

- develop skills in managing research-based work in experimental therapeutics

- carry out an extended research project involving a literature review, problem specification and analysis in experimental therapeutics and write a short dissertation

Guidance from the UK Royal College of Physician's Faculty of Pharmaceutical Medicine

The Faculty have confirmed that if enrolled for Pharmaceutical Medicine Specialty Training (PMST), trainees may be able to use knowledge provided by Experimental Therapeutics modules to cover aspects of a module of the PMST curriculum. Trainees are advised to discuss this with their Educational Supervisor.

Experimental Therapeutics modules may also be used to provide those pursuing the Faculty's Diploma in Pharmaceutical Medicine (DPM) with the necessary knowledge required to cover the Diploma syllabus. Applicants for the DPM exam are advised to read the DPM syllabus and rules and regulations.

Members of the Faculty of Pharmaceutical Medicine who are registered in the Faculty's CPD scheme can count participation in Experimental Therapeutics modules towards their CPD record. Non-members may wish to obtain further advice about CPD credit from their Royal College or Faculty.

Assessment methods

To complete the MSc, students need to:

Attend the six modules and complete an assessed written assignment for each module.

Complete a dissertation on a topic chosen in consultation with a supervisor and the Course Director.

Dissertation:

The dissertation is founded on a research project that builds on material studied in the taught modules. The dissertation should normally not exceed 15,000 words.

The project will normally be supervised by an academic supervisor from the University of Oxford, and an employer-based mentor.

The following are topics of dissertations completed by previous students on the course:

- The outcomes of non-surgical management of tubal pregnancy; a 6 month study of the South East London population

- Analysis of the predictive and prognostic factors of outcome in a cohort of patients prospectively treated with perioperative chemotherapy for adenocarcinoma of the stomach or of the gastroesophageal junction

- Evolution of mineral and bone disorder in early Chronic Kidney Disease (CKD): the role of FGF23 and vitamin D

- Survey of patients' knowledge and perception of the adverse drug reporting scheme (yellow cards) in primary care

- The predictive role of ERCC1 status in oxaliplatin based Neoadjuvant for metastatic colorectal cancer (CRC) to the liver

- Endothelial Pathophysiology in Dengue - Dextran studies during acute infection

- Literature review of the use of thalidomide in cancer

- An investigation into the phenotypical and functional characteristics of mesenchymal stem cells for clinical application

- Identification of genetic variants that cause capecitabine and bevacizumab toxicity

- Bridging the evidence gap in geriatric medicines via modelling and simulations

Teaching methods

The class-based modules will include a period of preparatory study, a week of intensive face-to-face lectures and tutorials, followed by a period for assignment work. Attendance at modules will be a requirement for study. Some non-classroom activities will be provided at laboratory facilities elsewhere in the University. The course will include taught material on research skills. A virtual learning environment (VLE) will provide between-module support.

The taught modules will include group work, discussions, guest lectures, and interaction and feedback with tutors and lecturers. Practical work aims to develop the students' knowledge and understanding of the subject.

Find out how to apply here - http://www.ox.ac.uk/admissions/graduate/applying-to-oxford



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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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Instrumentation and control engineers are highly sought after in a range of industries, including oil and gas, petrochemicals, chemical engineering, manufacturing, research, transport and infrastructure. Read more

Instrumentation and control engineers are highly sought after in a range of industries, including oil and gas, petrochemicals, chemical engineering, manufacturing, research, transport and infrastructure.

Course details

This programme will help you develop your knowledge and skills in instrumentation, electronics and control engineering, and it will help you develop the ability to synthesise information from a variety of sources and make effective decisions on complex instrumentation and control engineering problems.

What you study

For the Postgraduate Diploma (PgDip) award you must successfully complete 120 credits of taught modules. For an MSc award you must successfully complete 120 credits of taught modules and a 60-credit master's research project.

Examples of past MSc research projects:

  • effects of particle size on gas-solid flow measurement using dynamic electrostatic meters
  • an investigation of self-turning and predictive control with MATLAB
  • modelling and control of hot air blow rig PT326
  • wireless controlled car with data acquisition
  • BCD to 6-3-1-1 code converter design using VHDL
  • comparative evaluation of turning techniques for MPC
  • digital traffic signal controller design
  • proteus control board test site
  • design of temperature measurement system
  • control system design for stepping motor.

Course structure

Core modules

  • Digital Control and Implementation
  • Hydrocarbon Production Engineering
  • Identification and Model Predictive Control
  • Project Management and Enterprise
  • Research and Study Skills
  • Robust Control Systems
  • Signal Conditioning and Data Processing

MSc only

  • Major Project

Modules offered may vary.

Teaching

How you learn

You learn through lectures, tutorials and practical sessions. Lectures provide the theoretical underpinning while practical sessions give you the opportunity to put theory into practice, applying your knowledge to specific problems. 

Tutorials and seminars provide a context for interactive learning and allow you to explore relevant topics in depth. In addition to the taught sessions, you undertake a substantive MSc research project.

How you are assessed

Assessment varies from module to module. The assessment methodology could include in-course assignments, design exercises, technical reports, presentations or formal examinations. For your MSc project you prepare a dissertation.

Employability

An instrumentation and control engineer may be involved in designing, developing, installing, managing and maintaining equipment which is used to monitor and control engineering systems, machinery and processes. Graduates can expect to be employed in a wide range of sectors, including industries involved with oil and gas, petrochemicals, chemical engineering, manufacturing, research, transport and infrastructure.



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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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Digital Business Global Master has been designed to provide the necessary knowledge to all those professionals and students who want to improve their organizational skills and increase their competitiveness in the market. Read more
Digital Business Global Master has been designed to provide the necessary knowledge to all those professionals and students who want to improve their organizational skills and increase their competitiveness in the market. Additionally, under our guidance, people will not only understand but learn how to implement decision-making skills in order to elevate the existing level of the organization under their Management to a higher level of productivity and market orientation.

This course is not exclusively for “Tech Guys”, but is available for anyone who would like to be equipped with the tools to become a leader of the digital procedures of a company. No company can avoid this change and therefore all businesses must adapt their workflows to continue to compete in the current market. What Zigurat does is offers you the possibility of not only getting ahead in this marketing adjustment but rather to pioneer this movement.
This Global program has the potential to become the new MBA for the Business Sector.

In collaboration with IBM, Sabis, Elogia, Setesca ...

Goals

We have the tools and the capacity. We are the geniuses of the new era and as such we must reach out to others and overcome all the limitations imposed by humanity.
We have the power and with that, the world at our fingertips. We are unified in our desire to defeat such limitations. We are the new definition of billionaire. With our connection and our capacity to discover and evolve we can and will be the most competitive product in the market.
This is more than a conventional masters program. This course will guide you through one of the most epic changes in our era – the 4th revolution.
We will penetrate different market sectors, and for each of them, highlight the fundamental changes in each process including human resources practices and technological tools. Thereafter, we will demonstrate how to use such progress, implanting them into your business regime and converting your work ethic from “traditional” to a more progressive current way of working.
What will you be capable of doing?

By the end of this course you will understand how to apply the best plethora of collaborative and digital tools to improve your business strategies and processes.

Content Program:

Module 1: Competitive models
Module 2: Digital Business model
Module 3: Omnichannel marketing and sales models
Module 4: Digital maturation analysis of the organization and strategic model
Module 5: Basic people skills and competences
Module 6: Management and innovation models
Module 7: Transformation of the value chain: Purchasing
Module 8: Transformation of the value chain : Logistics
Module 9: Transformation of the value chain: Production
Module 10:Transformation of the value chain: Distribution
Module 11: Transformation of the value chain: Marketing
Module 12: Transformation of the value chain: FICO
Module 13: Transformation of the value chain: Information Technology
Module 14: Transformation of the value chain: Human Resources
Module 15: Cybersecurity and Digital Business Security
Module 16: Digital business enablers (IoT, BlockChain, BigData, Predictive, AI)
Module 17: Collaborative models
Module 18: Predictive models and advanced data analysis
Module 19: Industry 4.0
Module 20: Impact of electrification and sustainable consumption

International Summit
3 days in Barcelona

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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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Instrumentation and control engineers are highly sought after in a range of industries including oil and gas, petrochemicals, chemical engineering, manufacturing, research, transport and infrastructure. Read more

Instrumentation and control engineers are highly sought after in a range of industries including oil and gas, petrochemicals, chemical engineering, manufacturing, research, transport and infrastructure.

Course details

There are three routes you can select from to gain a postgraduate Master’s award:

  • MSc Instrumentation and Control Engineering - one-year full time
  • MSc Instrumentation and Control Engineering - two-years part time
  • MSc Instrumentation and Control Engineering (with Advanced Practice) – two years full time

The one-year programme is a great option if you want to gain a traditional MSc qualification – you can find out more here. This two-year master’s degree with advanced practice enhances your qualification by adding to the one-year master’s programme an internship, research or study abroad experience.

The MSc Instrumentation and Control Engineering (with Advanced Practice) offers you the chance to enhance your qualification by completing an internship, research or study abroad experience in addition to the content of the one-year MSc. This programme helps you develop your knowledge and skills in instrumentation, electronics and control engineering. And you develop your ability to synthesise information from a variety of sources and make effective decisions on complex instrumentation and control engineering problems.

What you study

For the MSc with advanced practice, you complete 120 credits of taught modules, a 60-credit master’s research project and 60 credits of advanced practice.

Examples of past MSc research projects:

  • effects of particle size on gas-solid flow measurement using dynamic electrostatic meters
  • an investigation of self-turning and predictive control with MATLAB
  • modelling and control of hot air blow rig PT326
  • wireless controlled car with data acquisition
  • BCD to 6-3-1-1 code converter design using VHDL
  • comparative evaluation of turning techniques for MPC
  • digital traffic signal controller design
  • proteus control board test site
  • design of temperature measurement system
  • control system design for stepping motor.

Course structure

Core modules

  • Data Acquisition and Signal Processing Techniques
  • Digital Control and Implementation
  • Hydrocarbon Production Engineering
  • Identification and Model Predictive Control
  • Project Management and Enterprise
  • Research and Study Skills
  • Research Project (Advanced Practice)
  • Robust Control Systems
  • Signal Conditioning and Data Processing

Advanced Practice options

  • Research Internship
  • Study Abroad
  • Vocational Internship

Modules offered may vary.

Teaching

How you learn

You learn through lectures, tutorials and practical sessions. Lectures provide the theoretical underpinning while practical sessions give you the opportunity to put theory into practice, applying your knowledge to specific problems. 

Tutorials and seminars provide a context for interactive learning and allow you to explore relevant topics in depth. In addition to the taught sessions, you undertake a substantive MSc research project.

In addition to the taught sessions, you undertake a substantive MSc research project and the Advanced Practice module. This module enables you to experience and develop employability or research attributes and experiential learning opportunities in either an external workplace, internal research environment or by studying abroad. You also critically engage with either external stakeholders or internal academic staff, and reflect on your own personal development through your Advanced Practice experience.

How you are assessed

Assessment varies from module to module. It may include in-course assignments, design exercises, technical reports, presentations or formal examinations. For your MSc project you prepare a dissertation.

Your Advanced Practice module is assessed by an individual written reflective report (3,000 words) together with a study or workplace log, where appropriate, and through a poster presentation.

Employability

An instrumentation and control engineer may be involved in designing, developing, installing, managing and maintaining equipment which is used to monitor and control engineering systems, machinery and processes. As a graduate you can expect to be employed in a range of sectors including industries involved with oil and gas, petrochemicals, chemical engineering, manufacturing, research, transport and infrastructure.



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Explore Emerson's Graduate Programs. In our social media and mobile-driven world, data and digital marketing have never been more vital. Read more

Explore Emerson's Graduate Programs

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:

  • Design mobile-friendly marketing programs focused on user experience
  • Implement digital storytelling and content marketing strategies that connect consumers with brands
  • Use web and social media analytic tools to evaluate online interactions to generate consumer leads
  • Incorporate best practices for digital campaign testing and measurement

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.

Program Details

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.

Learning Outcomes

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

  • Develop targeted, customer-centric digital marketing campaigns across a range of digital interfaces
  • Design marketing programs that account for the unique user experience needs of mobile consumers
  • Implement digital storytelling and content marketing strategies that connect consumers with brands across all major social media platforms
  • Use their knowledge of digital consumer behaviors and trends to design marketing programs that motivate consumers to engage and remain loyal to a brand

Data Analytics

  • Develop consumer personas and segments that provide the framework to deploy targeted and personalized marketing treatments
  • Build predictive models that forecast individual consumer behaviors and enable proactive marketing communications
  • Use web and social media analytic tools to evaluate online interactions and identify new opportunities to generate consumer leads and build even stronger customer relationships
  • Incorporate best practice digital campaign testing and measurement approaches that accurately assess the ROI of marketing investments

Emerson Advantage

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.



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Learn to interpret financial results and leverage predictive tools to guide action plans, forecasts and strategies for maximum performance. Read more

Learn to interpret financial results and leverage predictive tools to guide action plans, forecasts and strategies for maximum performance.

Learn to guide your employer's company to successful growth using the latest analytics. Interpret financial results and use predictive tools to guide action plans, forecasts and strategies for maximum performance. You also examine the latest analytical techniques that industry executives use to shape their companies' future plans. Further instruction enables you to pursue a concentration in either accounting or planning.

Required Courses

Sample Elective Courses



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This course aims to provide a broad-based understanding of the subject and then a study of in-depth topics covering modern technology for Power Systems, Power Electronics and related subjects. Read more
This course aims to provide a broad-based understanding of the subject and then a study of in-depth topics covering modern technology for Power Systems, Power Electronics and related subjects. It will prepare students for a career as a professional engineer working in research, design or industrial applications.

The modular structure of the MSc in Electrical Engineering offers students a great deal of flexibility, allowing them to choose the
modules that most reflect their interests and feed into their research project. The modules cover the following subjects; power electronics, drives, power systems (including distributed generation and wind power), design of single and multi-variable control systems, motor and generator design, instrumentation and measurement. This course is suitable for graduates of related disciplines who wish to convert to electrical engineering.

Students will develop:
up-to-date knowledge of electrical engineering, including design and modelling techniques and applications
the ability to plan and undertake an individual project
interpersonal, communication and professional skills
the ability to communicate ideas effectively in written reports
the technical skills to equip them for a leading career in electrical engineering, especially in the areas of power electronics, power systems, electrical machines and control

Following the successful completion of the taught modules, an individual research project is undertaken during the summer term.

Previous research projects on this course have included:
Modular converter topologies for power system applications
Predictive control for an uninterruptable power supply
Power systems stability enhancement using Static Converter (STATCOM)
Sensorless permanent magnet motor drives for more electric aircraft applications

Scholarship information can be found at http://www.nottingham.ac.uk/graduateschool/funding/index.aspx

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