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Masters Degrees (Data Analytic)

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There is an established need for advanced analytical training in population health research, as explicitly stated by most funding bodies in medicine and in other disciplines. Read more

There is an established need for advanced analytical training in population health research, as explicitly stated by most funding bodies in medicine and in other disciplines. The emergence of ‘Big Data’ has focussed the minds of many on appropriate data analytic skills training. This programme which is a development from the MSc Epidemiology and Biostatistics is the only taught postgraduate programme in the UK that specialises in the analysis of observational studies, routine healthcare data, and that adopts a focus on causal inference.

The programme offers intensive training in data analytic techniques tailored to the needs of career enhancers and career changers with a focus on health. It can be studied full time over 12 months or part time over 24 months.

You will take compulsory modules, including our innovative Professional Skills for Health Data Analysts module, designed to give you the skills and experience to work effectively in research, public health or health services research. It includes, for example, ethics, academic writing for publication, consultancy, management and leadership skills.

The programme will train scientists in the cutting-edge quantitative skills needed for health research; with the proficient expertise required to be able to work in a variety of fields related to health, together with in-depth knowledge and nurtured in thinking that yields the ability to undertake robust scientific enquiry using health data of various kinds.

The programme will provide strong foundations in the skills and knowledge of data analytics with relevance to health; we will stretch students to acquire and implement advanced techniques through optional modules that will allow their learning to be tailored towards discipline-specific paths appropriate to their future planned career.

At graduation, students will find themselves at the forefront of the discipline of health data analytics, with advanced knowledge and skills appropriate to all and any careers involving observational health data.

Distinctive features include:

  • A focus on statistical methods for observational health and health services research;
  • State-of-the-art training in predictive modelling;
  • Cutting-edge training in causal inference modelling (unique for UK MSc programmes);
  • Leading expert training in the pitfalls and malpractices of observational data analysis (unique for PGT programmes world-wide);
  • Extensive access to practice and practice-derived datasets maintained within Leeds Institute of Data Analytics (LIDA);
  • Substantial scope for student choice across a range of optional modules to accommodate different interests and needs, including potential engagement with the health-orientated non-medical aspects of computing and geography (via modules and research projects);
  • A compulsory generic and transferable skills module to prepare graduates for professional careers as independent researchers;
  • Research projects using clinically-relevant data, supervised by research-active academics, leading to the production of journal papers suitable for publication;
  • The use of blended learning to meet the differing learning styles of individual students, and to provide student paced-learning for those with different aptitudes for quantitative skills training.

For more information on typical modules, read Health Data Analytics MSc Full Time in the course catalogue



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We offer a suite of Masters programmes at Stirling. This is a one year, full time taught MSc. designed to lead to a job in data science or analytics. Read more

Introduction

We offer a suite of Masters programmes at Stirling.
This is a one year, full time taught MSc. designed to lead to a job in data science or analytics.
Big Data skills are in high demand and they attract high salaries. The MSc Big Data at the University of Stirling is a taught advanced Master's degree covering the technology of Big Data and the science of data analytics.
The course is taught in the beautiful Stirling campus in the heart of Scotland with support from companies who recruit data scientists.
The course covers Big Data technology, advanced analytics and industrial and scientific applications. The syllabus includes:
- Mathematics for Big Data
- Python scripting
- Big Data theory and computing foundations
- Big databases and NoSQL
- Analytics, machine learning and data visualisation
- Optimisation and heuristics for big problems
- Hadoop and MapReduce
- Scientific and commercial applications
- Student projects

Key information

- Degree type: MSc
- Duration: One year
- Start date: September
- Course Director: Kevin Swingler

Course objectives

- An understanding of the issues of scalability of databases, data analysis, search and optimisation
- The ability to choose the right solution for a commercial task involving big data, including databases, architectures and cloud services
- An understanding of the analysis of big data including methods to visualise and automatically learn from vast quantities of data
- An appreciation of the size of search spaces in large problems and the ability to choose an appropriate heuristic to find a near optimal solution
- The programming skills to build simple solutions using big data technologies such as MapReduce and scripting for NoSQL, and the ability to write parallel algorithms for multi processor execution.

English language requirements

If English is not your first language you must have one of the following qualifications as evidence of your English language skills:
- IELTS: 6.0 with 5.5 minimum in each skill
- Cambridge Certificate of Proficiency in English (CPE): Grade C
- Cambridge Certificate of Advanced English (CAE): Grade C
- Pearson Test of English (Academic): 54 with 51 in each component
- IBT TOEFL: 80 with no subtest less than 17

For more information go to English language requirements https://www.stir.ac.uk/study-in-the-uk/entry-requirements/english/

If you don’t meet the required score you may be able to register for one of our pre-sessional English courses. To register you must hold a conditional offer for your course and have an IELTS score 0.5 or 1.0 below the required standard. View the range of pre-sessional courses http://www.intohigher.com/uk/en-gb/our-centres/into-university-of-stirling/studying/our-courses/course-list/pre-sessional-english.aspx .

Structure and content

Our Big Data MSc is a mix of practical technology such as Hadoop, NoSQL, and Map-Reduce, important maths and computing theory, and advanced computational techniques. The course will teach you what you need to know to collect, manage and analyse big, fast moving data for science or commerce

REF2014

In REF2014 Stirling was placed 6th in Scotland and 45th in the UK with almost three quarters of research activity rated either world-leading or internationally excellent.

Strengths

Stirling is a member of The Data Lab, which is an Innovation Centre with the aim of developing the data science talent and skills required by industry in Scotland. The data lab with facilitate industry involvement and collaboration and provide funding and resources for students.
The Stirling MSc in Big Data has been developed in partnership with global and local companies who employ data scientists. HSBC have a development centre in Stirling and have provided some very interesting Big Data projects to our students. Amazon’s development centre in Scotland is close by in Edinburgh. The course features a long summer project, generally in partnership with a company or technology provider, that provides students with a showcase of their skills to take to employers or launch online.
We also have a programme of invited speakers from industry who give the students a chance to ask questions of people who are doing data science every day. Recent companies have included MongoDB, SkyScanner and HSBC.

Career opportunities

Demand for people with big data skills is projected to grow rapidly in the coming years. Average salaries are higher in Big Data jobs than the IT average and the skills shortage will make that gap bigger.
The Stirling Big Data MSc is run in partnership with industry and is designed to produce graduates with the skills that companies need.
e-Skills UK estimate that:
- The number of Big Data jobs in the UK rose by 41% from 2012 - 2013
- By 2020 there will be 56,000 Big Data jobs in the UK alone
- Big Data professionals earn on average 31% more than other IT professionals
- 77% of companies say it is difficult to recruit people with the Big Data skill they need

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The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. Read more
The MSc in Data Science & Analytics, jointly offered by the Department of Computer Science and the Department of Statistics, provides an education in the key principles of this rapidly expanding area. The combination of sophisticated computing and statistics modules will develop skills in database management, programming, summarisation, modelling and interpretation of data. The programme provides graduates with an opportunity, through development of a research project, to investigate the more applied elements of the disciplines.

Visit the website: http://www.ucc.ie/en/ckr49/

Course Details

The MSc in Data Science and Analytics is a significant collaboration between the Departments of Computer Science and Statistics; designed to provide graduates with the skills and knowledge required to help companies and public bodies deal with ever increasing and complex data. The programme emphasises the application of Computer Science and Statistics methodologies helping transform data into useful information that can support decision making.

Format

A typical 5 credit module:
• 2 lecture hours per week
• 1–2 hours of practicals per week
• Outside these regular hours students are required to study independently by reading and by working in the laboratories and on exercises.

Structure

Students must attain 90 credits through a combination of:

- Core Modules (30 credits)
- Elective Modules (30 credits)
- Dissertation (30 credits)

Part 1 (60 credits)

- Core Modules (30 credits) -

CS6405 Data Mining (5 credits) - Dr. Marc Van Dongen
ST6030 Foundations of Statistical Data Analytics (10 credits)
ST6033 Generalised Linear Modelling Techniques (5 credits)

- Database Modules -

Students who have adequate database experience take:

CS6408 Database Technology (5 credits) - Mr. Humphrey Sorensen
CS6409 Information Storage and Retrieval (5 credits) - Mr. Humphrey Sorensen

- Students who have not studied databases take:

CS6503 Introduction to Relational Databases (5 credits)
CS6505 Database Design and Administration (5 credits)

Elective Modules (30 credits)

Students must take at least 10 credits of CS (Computer Science) modules and at least 10 credits of ST (Statistics) modules from those listed below:

CS6322 Optimisation (5 credits) - Dr. Steve Prestwich
CS6323 Analysis of Networks and Complex Systems (5 credits) - Prof. Gregory Provan
CS6509 Internet Computing for Data Science (5 credits)
ST6032 Stochastic Modelling Techniques (5 credits)
ST6034 Multivariate Methods for Data Analysis (10 credits)
ST6035 Operations Research (5 credits)
ST6036 Stochastic Decision Science (5 credits)

- Programming Modules -

Students who have adequate programming experience take:

CS6406 Large-Scale Application Development and Integration l (5 credits) - Professor Gregory Provan
CS4607 Large-Scale Application Development and Integration ll (5 credits) - Professor Gregory Provan

- Students who have not studied programming take:

CS6506 Programming in Python (5 credits)
CS6507 Programme in Python with Data Science and Applications (5 credits) - Dr. Kieran Herley

Part 2 (30 credits)

Students select one of the following modules:

CS6500 Dissertation in Data Analytics (30 credits)
ST6090 Dissertation in Data Analytics (30 credits)

Assessment

Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2015 Book and for each module in the Book of Modules 2015/2016 - http://www.ucc.ie/modules/

Postgraduate Diploma in Data Science and Analytics

Students who pass each of the taught modules may opt to exit the programme and be conferred with a Postgraduate Diploma in Data Science and Analytics.

Careers

This programme aims to prepare students to manage, analyse and interpret large heterogeneous data sources. Graduates will design, compare and select appropriate data analytic techniques, using software tools for data storage/management and analysis, machine learning, as well as probabilistic and statistical methods. Such abilities are at the core of companies that constantly face the need to deal with large data sets.

Companies currently seeking graduates with data analytics skills include: firms specialising in analytics, financial services and consulting, or governmental agencies.

Companies actively recruiting Computer Science graduates in 2014-15 include:

Accenture, Aer Lingus, Amazon, Apple, Bank of America Merrill Lynch, Bank of Ireland, BT, Cisco, CiTi-Technology, Cloudreach, Dell, Digital Turbine Asia Pacific, EMC, Enterprise Ireland, Ericsson, First Derivatives, Guidewire, IBM, Intel, Open Text, Paddy Power, Pilz, PWC, SAP Galway Transverse Technologies, Trend Micro, Uniwink, Version 1 (Software).

How to apply: http://www.ucc.ie/en/study/postgrad/how/

Funding and Scholarships

Information regarding funding and available scholarships can be found here: https://www.ucc.ie/en/cblgradschool/current/fundingandfinance/fundingscholarships/

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Data and information is recognised as a central to the economic, business and cultural life of our society today. This course will equip you with the advanced information and analytic skills to thrive in the digital knowledge economy. Read more

Data and information is recognised as a central to the economic, business and cultural life of our society today. This course will equip you with the advanced information and analytic skills to thrive in the digital knowledge economy.

Whether you are already working and looking to enhance your expertise in the area of data science or you have recently graduated and want to move into roles specifically aligned with data science and analytics, this course will help you develop a comprehensive understanding of the role of data within business. You will study data governance, considering how data can be sourced, consolidated and stored securely, responsibly and efficiently. You will also explore the techniques used to analyse data, discover how data can contribute to a company's business strategy and focus on the application of data science in a specific field such as health, education or fraud prevention.

Central to the course will be the themes of security, ethics, data governance and sustainability. You will graduate with a critical awareness of the current ethical and security problems associated with the exploitation of information services and resources in organisations, enabling you to support collection, sorting and ordering of data, big data and information across a range of sectors.

Course Benefits

In the ever changing technological world, the skills required to successfully manage and share an organisations' data, require employees that have good understanding of data issues, technology, people and business. All of these skills are addressed by modules on this course, placing you at the forefront of the emerging digital economy.

You will be encouraged to undertake projects and volunteering opportunities with outside organisations, and our expert staff will ensure your learning is highly relevant to the workplace. Industry experts and leaders in their field will further fine tune your knowledge by sharing their expertise and professional insights during regular guest lectures. Past speakers have included computing, forensic and engineering experts from KPMG, Hermes Innovation Lab and Premier Farnell. Goranka Bjedov, Performance and Capacity Engineer at Facebook, visited the School to talk about her work in ensuring Facebook's worldwide data centres are able to deliver a 24/7 service to users.

The University is home to four research institutes and 14 research centres, including the Cybercrime & Security Innovation Centre and the New Technology Institute. Findings from our research will feed into your learning to equip you with the latest thinking and industry insights.

Indicative core modules

  • Dissertation / Masters Project
  • Research Practice
  • Data Analysis & Visualisation
  • Project Management
  • Critical Perspectives on Information
  • Database Systems

Indicative option modules

  • Cloud Computing
  • Data Warehouse Models & Approaches
  • Business Intelligence
  • Green Computing Strategies
  • Digital Security
  • Negotiated Skills Development
  • Managing Information in the Digital & Global Environment

Job prospects

With your combination of business awareness, management skills, technology knowledge and understanding of data science, you will be well prepared to pursue a career as a data manager across a range of sectors. The option modules available on the course will allow you to follow a route that suits your skills, aspirations and interests. Recent students from the School have secured roles with the NHS and local councils in data management and business intelligence, while others have gone on to start their own consultancy businesses. Further study for a PhD in the area of data science is also an option.

  • Database engineer
  • Data quality controller
  • Data scientist
  • Retail / fraud / health / business data analyst


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‌Policy-making in all sectors has become more data driven and advanced training in issues of data use, data sharing, transparency, and accountability are important for both the public and private sectors. Read more
‌Policy-making in all sectors has become more data driven and advanced training in issues of data use, data sharing, transparency, and accountability are important for both the public and private sectors. ‌ Unlocking the potential of collecting, sharing and analysing massive amounts of administrative and economic, social and political information to bring economic and social benefits requires individuals trained in both policy analysis and data analytics.

The MSc in Policy Analytics provides training for graduates who want to develop the ability to apply data analysis techniques to a range of substantive and policy related questions.

The MSc in Policy Analytics offers rigorous data analytic training alongside a specialisation in a policy subfield (e.g. social and family policy, economic and public policy, environment, criminal justice, security). It equips students with the technical understanding of a range of data analytic techniques and the practical software and programming skills to implement these methods to address their own research questions. The programme is designed to enable students to carry out their own research and to equip them to pursue other professional research activities subsequently.

This MSc is an extension of the successful Q-Step programme training social scientist undergraduates in quantitative methods and is one of three data science MSc delivered at Exeter.

Employability and work placements

All students enrolled on our Q-Step undergraduate and postgraduate programmes have the opportunity to undertake a work placement with one of our industry partners. A work placement will allow you to get hands-on analysis experience for a period of 2 to 11 weeks.

Work placements students will also receive a bursary of up to £2,000 to support them during the placement.

There are wide variety of placements to choose from locally, nationally and in Europe with a variety of public sector organisations, non-governmental organisations (NGOs) and industry.

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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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This course produces specialist Data Scientists who can design and implement computer-analytics and visualisation solutions for industry. Read more

This course produces specialist Data Scientists who can design and implement computer-analytics and visualisation solutions for industry. With an emphasis on Big Data, you will gain an understanding of the needs of businesses and how to manage requirements in this emerging international area of focus for companies, governments and economies.

The course focuses on Big Data, traditional and unconventional data management, including acquisition, storage, warehousing, analytics and visualisation tools and techniques. You’ll put these skills into practice in our state-of-the-art facilities.

Importantly, the course satisfies industry’s demand for Data Scientists who have the ability to relate key performance indicators, and contribute to business decision-making at a high level – giving you an advantage in the job market.

What you will study

Throughout the course, content is complemented by practical work, allowing you to support your theoretical knowledge with practical experience in data storage, mining, warehousing, visualisation and analysis as well as transferrable skills.

The individual project provides an opportunity for applying specialist knowledge together with analytic, problem-solving, managerial and communication skills to a particular area of interest within data science. Working with the full support and guidance of an allocated Project Supervisor, you will propose, plan, specify, develop, evaluate, and present a substantial project.

Teaching and assessment

You will be taught through a mixture of lectures, tutorials, labs. You will be invited to attend talks presented by highly-experienced researchers, speakers from industry, and members of the BCS (British Computer Society) on a wide range of industry-related topics. You will also be supported through our online virtual learning environment where you can access a wide variety of resources and other support materials.

Part-time September start students

  • A) Part-time September start students who would like to work on their project during the summer start their project in May of their second year and complete in December of their third year. (Approximately 28 months)
  • B) Part-time September start students who would like to avoid working on their project during the summer start their project in September of their third year and complete in May that year.  (Approximately 33 months)

Part-time January start students

  • C) Part-time January start students who would like to work on their project during the summer will start their project in January of their third year complete their project in August that year. (Approximately 32 months)
  • D) Part-time January start students who would like to avoid working on their project during the summer will start their project in January of their third year, have a break during the summer semester and continue their project September-December that year. (Approximately 36 months)

ACTIVITY SUMMARY

  • Lectures - 30 students per group, 24 hours over two months
  • Tutorial - 30 students per group, 24 hours over two months

INDEPENDENT STUDY

A significant portion of this courses is underpinned by independent learning, and you will be expected to be responsible for managing your coursework, reading and other learning activities appropriately.

STAFF DELIVERING ON THIS COURSE

Our staff members feature in the annual Support and Teaching staff with Appreciation and Recognition (STAR) awards voted by the students and organised by RGU:Union. Recently we have been awarded two Lecturer of the Year awards and an award for Continued Excellence.

Many of our academic staff are Fellows or Senior Fellows of the Higher Education Academy or are working towards this accolade. This is a professional recognition of practice, impact and leadership of teaching and learning.

Staff on this course could also include: visiting lecturers, visiting Distinguished Researchers, library staff and industry experts and postgraduate researchers.

ASSESSMENT

Typically students are assessed each year:

Year 1

  • 4 written exams, typically for 3-4 hours
  • 2 reports
  • 1 dissertation (final year project)
  • 1 oral assessment
  • 8 practical skills assessment
  • 1 group critique

Placements

Students who perform particularly well during their first semester of studies will be invited to apply for any long-term placement opportunities (40-45 weeks) found by the Placement Office. Alternatively, you can seek your own long placement or a short placement. Note that permission to undertake a placement is at the discretion of the School and students who optionally go on placement also need to pay a £1000 fee.

Job prospects 

The opportunity to exploit Big Data is recognised world-wide, and it is included in government economic strategies. The UK Government and Scottish Governments highlight it as an emerging opportunity for growth. The course prepares you for a career in Data Science or in Big Data. Job openings include: Data Scientist, Data Analyst, Data Visualisation Specialist, Data Manager, Database Designer/Manager, Data Mining Expert and Big Data Scientist. The course also prepares students for research careers by providing the skills necessary of an effective researcher. Suitable MSc graduates may continue to PhD programmes within the school.

Aberdeen is home to many multinational oil and gas companies and associated suppliers such as mainstream software houses, IT providers to major oil-related companies, specialist software consultancies, and venture capital start-ups, so graduates can seek employment locally. RGU is also involved in a number of commercial collaborations on a local, national and international scale with organisations such as BP, British Geological Survey, Wood Group PSN, Accenture, WIPRO and many Aberdeen-based software development companies, and you may benefit from the university’s links with some of these companies when it comes to securing placements or employment.

Please visit the website to find out how to apply.



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This programme is ideal if you wish to use your analytic skills to derive and obtain useful insights from large amounts of data. Read more
This programme is ideal if you wish to use your analytic skills to derive and obtain useful insights from large amounts of data. By equipping you with the rigorous modelling and consulting skills needed to understand, manage and communicate useful insights from ‘big data’, it prepares you to inform business decisions or government policies.

Taught modules are delivered by our group of internationally recognised management scientists who are actively working with business, government and non-profit organisations to tackle routine, strategic or policy problems.

Our industry advisory board ensures that the focus of our taught modules is of both academic and practical relevance. IBM, our partner, has jointly developed with us two modules (Customer Analytics and Leading Analytics Initiatives), and sponsors a student prize.

During the summer, you will undertake a supervised consulting or research project. This will give you the opportunity to apply powerful tools such as data mining, forecasting, optimisation, simulation and decision analysis to a particular area of business or policy, equipping you with skills highly prized by employers.

Core study areas include consulting for analytics, discovery analytics, decision analytics, managing big data, customer analytics, leading analytics initiatives, operations analytics, policy and strategy analytics, and a consulting or research project.

See the website http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/business-analytics-consulting/

Programme modules

Semester 1:
- Consulting for Analytics
You will learn the craft and skills required by analytic consultants, and which employers look for but often find lacking. It will cover process aspects of analytics projects, as well as skills in client interaction, problem structuring and data elicitation (with individuals and/or groups, and with hard/soft data), presenting data-driven analyses, report writing, and developing simple bespoke decision support systems.

- Discovery Analytics
You will be introduced to common statistical methods to explore and visualise cross sectional and temporal data. You will also learn about the design and conduct of data collection efforts, together with methods for dealing with data outliers and missing data. Industry-leading tools that are in high demand from employers (e.g. SAS and SPSS) will be used.

- Decision Analytics
Your will be introduced to common operational research techniques to help determine the best course of action for a given decision or problem. Topics covered include optimisation, simulation and decision and risk analysis.

- Managing Big Data
Your will learn about the challenges and opportunities derived from the increased volume, variety, velocity and value of data that is available today. A range of big data topics will be covered including data type, data integration, data technologies, and data security.

Semester 2:
- Customer Analytics
You will focus on analytics techniques that can help organisations gain a deeper insight into customers’ behaviour and attitudes towards their products and services. It will cover approaches designed to provide a profile of customer segments, such as those grounded in data mining and multivariate statistical analysis. Industry-leading tools that are in high demand from employers (e.g. SAS and SPSS) will be used. There is an IBM sponsored student prize on this module.

- Leading Analytics Initiatives
You will learn about the issues associated with implementing an analytics capability in organisations. It will cover topics on how to develop an analytics strategy, how to embed analytics in organisational processes to ensure they deliver value, and how to deploy analytics throughout the organisation to improve decision making. There is an IBM sponsored student prize on this module.

- Operations Analytics
You will focus on analytics techniques that can help organisations to develop a better understanding of operational processes, and identify efficiency and cost reduction opportunities. Topics covered include advanced optimisation and simulation techniques.

- Policy and Strategy Analytics
You will focus on analytics techniques designed to tackle complex policy and strategic issues. It will cover approaches designed to explain the behaviour of complex social systems or assess the consequences of complex decisions, in order to provide the levers for policy and strategy making in a variety of sectors.

Summer:
- Consulting or Research Project

Assessment

Taught modules are assessed by a mixture of coursework and examinations.
The summer project is assessed via a written dissertation.

Careers and further study

Business analytics is a new and rapidly developing field, and individuals with analytics skills are in short supply.
Graduates from this programme can expect to work as management consultants, business analysts, policy analysts, marketing researchers, operations researchers, and data scientists.
We have developed two modules - Customer Analytics and Leading Analytics Initiatives - in close collaboration with our partner IBM, who also sponsor a student prize.

Why choose business and economics at Loughborough?

Loughborough’s School of Business and Economics is a thriving forward-looking centre of education that aims to provide an exceptional learning experience.

Consistently ranked as a Top-10 UK business school by national league tables, our graduates are highly employable and enjoy starting salaries well above the national average.

The rich variety of postgraduate programmes we offer ranges from taught masters, MBA and doctoral programmes, to short courses and executive education, with subjects spanning Management, Marketing, Finance and Economics, Work Psychology, Business Analytics, International Crisis Management and Information Management. New for 2016, we are also launching two exciting new programmes in Human Resource Management. All of this contributes to a lively and supportive learning environment within the School.

- Internationally Accredited
The School of Business and Economics is one of less than 1% of business schools in the world to have achieved accreditation from all three major international accrediting bodies: The Association to Advance Collegiate Schools of Business (AACSB International), EQUIS accreditation from the European Foundation for Management Development (EFMD) and the Association of MBAs (AMBA).

- Career Prospects
Our graduates are in great demand. Over 94% of our postgraduate students were in work and/or further study six months after graduating.* As such, you will be equipped with skills and knowledge that will serve you well in your career or enable you to pursue further study and research.

*Source: DLHE

Find out how to apply here http://www.lboro.ac.uk/study/postgraduate/programmes/departments/business-economics/business-analytics-consulting/

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The Medicine MRes is a strongly research-based programme, which gives you the training and opportunity to develop as a scientist or scientifically-literate clinician. Read more

The Medicine MRes is a strongly research-based programme, which gives you the training and opportunity to develop as a scientist or scientifically-literate clinician.

It can help you to gain:

  • a comprehensive understanding of the concepts and techniques relevant to medical research
  • the ability to critically and creatively evaluate current issues in medicine and health.

You’ll get experience in formulating new hypotheses and exploring the causes and consequences of diseases by conducting rigorous scientific research in a laboratory or with patients.

A nine-month research project helps you to develop specialised knowledge, as well as design and undertake a substantial piece of publishable research. You’ll be based in one of our internationally-renowned institutes and be supervised by leading experts in their field. You can choose from a range of research opportunities in applied health, cancer and pathology, cardiovascular, genes and development, medical education and musculoskeletal topics.

More information

The School of Medicine is a major international centre for research and education. Our ambition is to improve health and reduce health inequalities, locally and globally, through excellent research and its translation into healthcare practice, and the education of future scientific and clinical leaders who will advocate and practise an evidence-based approach.

Course content

The taught modules are designed to stimulate a deep and critical knowledge of research. The optional modules allow you to develop a comprehensive knowledge of different approaches to medical research.

The Paper Criticism module enables you to develop subject-specific skills, such as an understanding of the ethical issues of medicine and knowledge of the current requirements for the governance of medical research and its publication. You apply your knowledge of research methods to published papers and enhance your critical skills.

The Analytic Research module provides a critical awareness of research planning and methods and develops your research skills. It includes topics on the structure of analytic research investigations; the analysis of the data obtained in analytic studies, especially the metrics used; the problems resulting from bias and confounding and how they are dealt with; basic statistics of precision and comparison;dealing with unequal duration of follow-up in cohort studies; and critical appraisal of published research.

The Capturing and Handling Data in Research module is an introduction to the collection and handling of health research data. It will include topics on: social inclusion in research; sampling from populations; types of data; collecting data through questionnaires; how scales and tests are used to collect data; and how data are collected and described using various fractions such as rates, ratios, risks and odds; recording quantitative and qualitative data in suitable formats; using computers in the analysis of data; the importance of the statistics that summarise quantitative data; and an introduction to the analysis of quantitative and qualitative data. Critical appraisal of published research will underpin theory.

Course structure

Compulsory modules

  • Analytic Research 15 credits
  • Intervention Research 15 credits
  • Capturing and Handling Data in Research 15 credits
  • Research Project in Medicine 120 credits

For more information on typical modules, read Medicine MRes in the course catalogue

Learning and teaching

There are few formal lectures in the MRes programme. Most of your time is devoted to planning and conducting the research project, usually working with a small team of researchers or healthcare professionals.

Interactive tutorial sessions are shared with students on other Masters programmes in the School of Medicine, intercalating medical students and health professionals.

Assessment

There is one examination in May for the Paper Criticism module. Other modules are assessed by the submission of coursework, workbooks, reports and reviews.

Exit awards of Postgraduate Diploma in Medical Research (120 credits) or Postgraduate Certificate in Medical Research (60 credits) are available for this programme.

Career opportunities

The Master of Research in Medicine is for people who want to pursue a lifelong career in academic medicine research.

For medical students, the addition of the Medicine MRes on your CV is an advantage when applying for Academic Foundation Posts and Specialist Training Posts in the NHS.

Careers support

We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.

The Careers Centre and staff in your faculty provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.



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At the local, national and global level, we are witnessing an intense period of social transformation and fragmentation. Within this context, there is growing political and policy recognition of the need to better understand and thereby address social inequalities. Read more

At the local, national and global level, we are witnessing an intense period of social transformation and fragmentation. Within this context, there is growing political and policy recognition of the need to better understand and thereby address social inequalities. The social sciences have an important role to play in mapping and understanding how inequalities arise and in tackling their causes and consequences. Innovative developments in the social sciences are offering new methodological, theoretical and empirical insights into entrenched and emerging inequalities of status, resource, outcome and opportunity. This has inspired us to create an interdisciplinary programme focusing on inequality in all its forms and its social, political and economic implications.

This Masters programme equips students with the necessary knowledge and skills to engage in and contribute towards work that tackles the realities and effects of social inequality. Capitalising on academic and applied expertise in the School of Sociology and Social Policy and the Leeds Inequalities Research Network, this programme harnesses leading analytical approaches combining qualitative, quantitative and data analytic methods (in close collaboration with the School of Geography).

In addition to offering an advanced understanding of rising material inequality, the programme encourages an intersectional approach to understanding socio-economic stratification and how this links with physical (dis) ability, race, ethnicity, nationality, gender, sexuality, class and age. It provides a stimulating intellectual environment and cutting edge methodological approaches to comparing and contrasting the formation and consequences of inequalities across a range of national and international contexts. Through an examination of geopolitical and socioeconomic shifts, such as urbanisation and globalisation, students are actively supported to critically interrogate the contemporary character and extent of social inequality.

Research insight

Whilst undertaking this programme, students will join a vibrant and dynamic research led teaching and learning environment in the School of Sociology and Social Policy. You will benefit from the interdisciplinary expertise and extra-curricular activities hosted by the School and its research centres including those in Disability Studies, Ethnicity and Racism Studies, Interdisciplinary Gender Studies and Research into Families, the Life Course and Generations. You will also access events through the Leeds Social Sciences Institute (LSSI), which fosters cross-departmental collaboration, learning and impact, Students will also benefit from workshops on global inequalities by academic leaders from across campus and research seminars with external speakers; along with career development opportunities and events. As such, students can take advantage of academic and applied expertise both within and beyond the University whilst also developing specialist knowledge and transferable skills for their future career development in the public, private or third sector.

Course content

The programme bridges disciplinary divides to provide a detailed understanding of the ways in which social inequality manifests across diverse communities and contexts at the national and international level. It offers insight into the character, causes and consequences of social inequality, as well as forms of resistance and policy responses. It has a strong and innovative methodological focus, including traditional qualitative and quantitative approaches to the social analysis of inequality, as well as new approaches to data visualisation and analytics from across the social sciences. The programme uses a range of teaching methods, including lectures, seminars and workshops, complemented by a range of co-curricular activities partly facilitated through the Leeds Inequalities Research Network.

Course structure

The core modules of the programme introduce students to contemporary research on global inequalities of social difference and disadvantage, emphasizing a diversity of theoretical and research design strategies, including international evidence surrounding the shifting nature and extent of inequality. Students are able to tailor the programme according to their interests and needs by choosing from a specially selected range of optional modules, which address major social and economic inequalities across diverse social science subjects and substantive issues. As such, students can choose to develop in-depth specialist knowledge on a particular area and/or focus more generally on the social processes and arrangements that give rise to inequalities.

Compulsory modules

  • Inequalities: Exploring causes, Consequences and Interventions 30 credits
  • Geographic Data Analysis and Visualisation 15 credits
  • Dissertation 60 credits

PLUS TWO OF THE BELOW:

  • Quantitative Research Methods 15 credits
  • Qualitative Research Methods 15 credits
  • Applied Population and Demographic Analysis

For more information on typical modules, read Inequalities and Social Science MSc Full Time in the course catalogue

Learning and teaching

We use a range of teaching and learning methods including presentations, seminars, workshops, tutorials and lectures. However, independent study is crucial to this degree – it allows you to prepare for taught sessions, develop your research interests and build a range of skills. This is particularly the case for the dissertation/applied project module of this programme.

Supported through workshops and supervision, students develop their research dissertation or an applied project in partnership with external organisations. This offers students an exciting opportunity to gain experience of applying their knowledge and skills to policy and practice.

Assessment

Your core modules will be assessed using essays. Optional modules may use other forms of assessment that reflect the diversity of the topics you can study, including presentations, book and literature reviews, research proposals and reports among others.

Career opportunities

This programme prepares students for policy, research and applied careers across the private, public and third sectors. The interdisciplinary and dynamic nature of the programme equips students with the critical, analytical and methodological skills to deploy their specialist expertise in a clear, efficient and effective manner. You will develop transferable skills in research, analysis and communication, as well as in-depth knowledge that can be applied across a range of domains and contexts.

Due to the rigorous and applied nature of our teaching, graduates might pursue careers across a diverse range of organisational settings such as in government, NGOS, charities, think tanks, social enterprises and business. The programme also offers excellent development opportunities to pursue a career in social research or undertake research at PhD level.

Irrespective of your future career intentions, we offer tailored guidance and support through ESSL Faculty staff and the Leeds Careers Centre.



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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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This exciting new course is the first in Scotland to be run in partnership with SAS, a global leader in business analytic solutions. Read more

This exciting new course is the first in Scotland to be run in partnership with SAS, a global leader in business analytic solutions. It has been developed in close collaboration with leading financial services organisation HSBC and The Data Lab, to produce graduates with the skills that industry needs.

The course addresses the acknowledged shortage of business leaders and managers with a detailed working knowledge of data analytics. It provides students with a deep understanding of the industrial and scientific relevance of advanced analytics and their application in strategic and operational decision making. In doing so it develops graduates with highly sought after blend of data analytics, business acumen and advanced management skills.

The course gives you the opportunity to develop specialist skills by choosing elective modules from finance, marketing, data science and management. You’ll work in real life consultancy-style projects alongside industry leaders in data analytics. Our extensive network of external organisations across all sectors provides opportunities to build your knowledge, skills and experience for a successful career in business analytic roles.

Key information

-Degree type: MSc

-Study methods: Full time, Campus based

-Duration: 12 months

-Start date: September

-Location: Stirling Campus

Structure and content

Begin your course in the best possible way, with our unique Flying Start Leadership programme. It’s exclusively for new students about to start one of our postgraduate courses. You’ll take part in a wide range of group and individual activities, workshops and information sessions to help you prepare for the year ahead, and make the most of your time at the University of Stirling Management School.

Attend the Flying Start Leadership programme and you will:

-Discover more about the exciting period of learning ahead.

-Understand what is expected of you in your course.

-Get to know the teaching and support staff.

-Learn more about a diverse range of approaches to learning.

-Work as part of a successful team.

-Develop your personal goals for the year ahead.

Activities range from practical skills – such as effective public speaking – to developing ways to work in groups with other students. The programme is also a chance to discover all that the University and the vibrant city of Stirling has to offer, and to make new friends.

About the Faculty

The University of Stirling Management School is recognised as a centre of academic excellence that offers innovative scholarship and widespread engagement with a variety of stakeholders to improve and transform business, society and lives.

The rigour and relevance of the School’s research is represented in the way projects are sponsored and funded by leading domestic research institutes as well as international bodies who value the research expertise offered.

Other admission requirements

If you don’t meet the required criteria for this course, you can complete the Graduate Diploma in Business, Finance and Sport to gain a guaranteed entry onto this Master's degree.

INTO University of Stirling offers a Graduate Diploma for those students who do not meet the required criteria for this course. If you successfully complete the Graduate Diploma in Business, Finance and Sport and meet the required progression grades, you will be guaranteed entry onto this Master's degree.

If English is not your first language you must have one of the following qualifications as evidence of your English language skills:

-IELTS: 6.0 with 5.5 minimum in each skill.

-Cambridge Certificate of Proficiency in English (CPE): Grade C or above.

-Cambridge Certificate of Advanced English (CAE): Grade C or above.

-Pearson Test of English (Academic): 54 with 51 in each component.

-IBT TOEFL: 80 with no subtest less than 17.



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This Research Methods in Psychology (RMP) Master’s programme was developed to conform to the guidelines for ESRC recognition of postgraduate training. Read more
This Research Methods in Psychology (RMP) Master’s programme was developed to conform to the guidelines for ESRC recognition of postgraduate training.

The programme provides advanced training in a variety of research methods and data analytic techniques.
The main aim is to equip you to conduct research in your chosen field that is of high quality and impact. In order to promote self-motivated learning we have designed a programme in which you apply the skills you are taught to your own research questions. Therefore, in addition to classroom instruction, you will receive structured support as you develop your research questions, plan and execute the research, analyze the data, and prepare reports describing your findings.

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This MSc Research Methods in Psychology (RMP) Master’s programme is designed to equip you with a wide range of methodological skills to enable you to become a successful PhD student or professional researcher in psychology. Read more

This MSc Research Methods in Psychology (RMP) Master’s programme is designed to equip you with a wide range of methodological skills to enable you to become a successful PhD student or professional researcher in psychology. The programme provides advanced training in a variety of research methods and data analytic techniques. The main aim of this master's in research methods in psychology is to equip you to conduct research in your chosen field that is of high quality and impact. We have designed a programme in which you apply the skills you are taught to your own research questions. Therefore, in addition to classroom instruction, you will receive structured support as you develop your research questions, plan and execute the research, analyse the data, and prepare reports describing your findings.

Introducing your course

This is the course page for MSc Research Methods in Psychology at the University of Southampton. Find out everything about Research Methods in Psychology and what studying here involves.

In this course page we explain a range of key information about the course. This includes typical entry requirements, modules you can take and how assessment works. We also suggest career opportunities open to you as a University of Southampton graduate of MSc Research Methods in Psychology.

If you still have questions, please get in touch and we’ll be happy to answer any enquiries. See our contact us page for our telephone, email and address information.

Overview

All master's in research methods in psychology students complete eight modules in two semesters (eight months), which cover the theory, practice and context of a wide range of research approaches, using a combination of lectures, workshops, small group discussions, collaborative group research projects, and independent study. Students receive personal guidance and feedback from experts in the methods used and the research topics in which the student wishes to specialise. Assessment on this MSc Research Methods in Psychology programme is based entirely on substantive pieces of research-related work carried out on in the student's area(s) of interest. Students taking the MSc then complete a further piece of independent research (four months). 

View the programme specification document for this course



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The focus of this programme is on contemporary substantive issues in criminology and criminal justice and on criminological research methods. Read more
The focus of this programme is on contemporary substantive issues in criminology and criminal justice and on criminological research methods. It is particularly appropriate for those engaged in criminal justice policy analysis and development or similar work in allied fields.

The programme develops a theoretical, policy and technical understanding of key issues within criminology, criminal justice and research methods. More specifically, it aims to develop an advanced understanding of the complex nature of crime, harm and victimisation together with an appreciation of the role of the state/criminal justice system in the regulation of human behaviour, deviance and crime. The programme will equip you to design and implement social scientific research using a broad range of methodologies, consider research ethics, analyse and present the material such research generates.

Through combining criminology and research methods, the programme enables you to think logically and in an informed manner about criminological issues. The programme fosters a critical awareness of the relationship between theory, policy and practice and enables you to utilize your research knowledge of research skills and translate these into research practice in the field of criminology and broader social science research professions.

Modules

You'll undertake modules from a broad base of subject areas including:

Criminological theory
Crime, harm and victimisation
Responding to crime: justice, social control and punishment
Criminological research in practice
Methods for social research and evaluation: philosophy, design and data collection
Data analytic techniques for social scientists
Dissertation

Study hours

Year 1 class contact time is typically 6 hours per week part time and 12 hours per week full time plus individual tutorial and independent study.

Placements

Our criminology programme also has a strong voluntary work scheme.You're encouraged to undertake voluntary work in a variety of criminal justice related agencies. Recent positions have been within the police service, the prison service, legal advice, victim support, domestic violence and child abuse agencies and youth offending and youth mentoring schemes.

Professional links

The Crime and Criminal Justice Research Group, (CCJRG), at LSBU has developed a strong national and international reputation for delivering high quality and real life impact research. It has worked closely with a range of government agencies, including the Office for Criminal Justice Reform (Ministry of Justice); Government Office for London; the Scottish Executive, Northern Ireland Office and the Equalities and Human Rights Commission. It has also undertaken extensive research in collaboration with various London local authorities together with a range of voluntary and charity-based agencies.

Employability

This MSc will enable you to pursue a range of professional careers in criminal justice related work in statutory, commercial or community voluntary sectors and operating at central, regional and local government levels, for example, the Home Office; police forces; local government; crime and disorder reduction partnerships and their equivalencies throughout the world.

The acquisition of specific criminological and research methods knowledge will also enhance the career opportunities if you are currently working in the field. The specialist focus on research methods also offers an excellent foundation for those interested in undertaking subsequent doctoral research in the field.

LSBU Employability Services

LSBU is committed to supporting you develop your employability and succeed in getting a job after you have graduated. Your qualification will certainly help, but in a competitive market you also need to work on your employability, and on your career search. Our Employability Service will support you in developing your skills, finding a job, interview techniques, work experience or an internship, and will help you assess what you need to do to get the job you want at the end of your course. LSBU offers a comprehensive Employability Service, with a range of initiatives to complement your studies, including:

• Direct engagement from employers who come in to interview and talk to students
• Job Shop and on-campus recruitment agencies to help your job search
• Mentoring and work shadowing schemes.

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