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Masters Degrees (Stochastic Modelling)

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he contribution of mathematical and computational modelling to the understanding of biological systems has rapidly grown in recent years. Read more
he contribution of mathematical and computational modelling to the understanding of biological systems has rapidly grown in recent years. This discipline encompasses a wide range of life science areas, including ecology (e.g. population dynamics), epidemiology (e.g. spread of diseases), medicine (e.g. modelling cancer growth and treatment) and developmental biology.

This programme aims to equip students with the necessary technical skills to develop, analyse and interpret models applied to biological systems. Course work is supported by an extended and supervised project in life science modelling.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

Modelling and Tools;
Mathematical Ecology;
Dynamical Systems;
Mathematical Biology and Medicine.

Optional Courses

Optimization;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Stochastic Simulation;
Partial Differential Equations;
Numerical Analysis;
Geometry;
Climate Change: Causes and Impacts;
Biologically Inspired Computation;
Climate Change: Mitigation and Adaptation Measures.

Typical project subjects

Population Cycles of Forest Insects;
Modelling Invasive Tumour Growth;
The replacement of Red Squirrels by Grey Squirrels in the UK;
Wiring of Nervous System;
Vegetation Patterning in Semi-arid Environments;
Daisyworld: A Simple Land Surface Climate Model.

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Climate change is recognised as having potentially huge impacts on the environment and on human society. Read more
Climate change is recognised as having potentially huge impacts on the environment and on human society. This programme aims to provide an understanding of climate change causes, impacts, mitigation and adaptation measures from a life science perspective in conjunction with developing a wide variety of mathematical modelling skills that can be used to investigate the impacts of climate change.

The programme closely follows the structure of our Applied Mathematical Sciences MSc. Two of the mandatory courses will specifically focus on understanding the issues related to climate change and are taught by the School of Life Sciences.

Students will take a total of 8 courses, 4 in each of the 1st and 2nd Semesters followed by a 3-month Project in the summer. A typical distribution for this programme is as follows:

Core courses

Modelling and Tools;
Mathematical Ecology;
Climate Change: Causes and Impacts;
Climate Change: Mitigation and Adaptation Measures;
Dynamical Systems (recommended);
Stochastic Simulation (recommended)

Optional Courses

Optimization;
Mathematical Biology and Medicine;
Numerical Analysis of ODEs;
Applied Mathematics;
Statistical Methods;
Applied Linear Algebra;
Partial Differential Equations;
Numerical Analysis;
Geometry;
Bayesian Inference.

Typical project subjects

Population Cycles of Forest Insects;
Climate Change Impact;
The replacement of Red Squirrels by Grey Squirrels in the UK;
Vegetation Patterns in Semi-arid Environments;
Daisyworld: A Simple Land Surface Climate Model.

The final part of the MSc is an extended project in mathematical modelling the impacts of climate change on environmental systems, giving the opportunity to investigate a topic in some depth guided by leading research academics.

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The programme consists of a wide range of modules and three research projects and aims to develop deeper insights into non-equilibrium processes using theoretical modelling, simulation and data-driven analysis. Read more
The programme consists of a wide range of modules and three research projects and aims to develop deeper insights into non-equilibrium processes using theoretical modelling, simulation and data-driven analysis. Leads to PhD study or careers in teaching, industrial research or the financial sector.

Key benefits

- An intensive course covering a wide range of basic and advanced topics on Non-Equilibrium Systems.

- Taught by experts in the field.

- A full twelve-month course with three research methods modules to give a real introduction to research.

- Intimate class environment with small class sizes (typically fewer than twenty students on a module) allowing good student lecturer interactions.

- Unrivalled location at the centre of London.

Visit the website: http://www.kcl.ac.uk/study/postgraduate/taught-courses/non-equilibrium-systems-theoretical-modelling-simulation-and-data-driven-analysis-msc.aspx

Course detail

- Description -

The ultimate goal of the programme is to address interdisciplinary challenges e.g. How do we characterize, design and grow materials, and devices, with novel properties out of equilibrium? How do we control and exploit the stochastic processes inherent to biological systems? Can we use inference and information assimilation approaches from physics and biology to monitor and evaluate the state and direction of non-equilibrium environmental systems?

The programme consists of a wide range of taught modules and 3 research methods modules in the rapidly developing and exciting interdisciplinary field of Non-Equilibrium Systems. It covers scientific areas ranging from mathematics, physics, informatics and chemistry to biomedical and environmental sciences.

- Course purpose -

For graduates with excellent undergraduate or equivalent qualifications in any relevant discipline (including; mathematics, physics, chemistry, engineering, materials science, biophysics, geophysical sciences and computer science) who want to work in research and development in an academic or industrial environment. The programme aim is to develop deeper insights into non-equilibrium processes using theoretical modelling, simulation and data-driven analysis and prepare students ideally for active research.

- Course format and assessment -

The format and assessment of the MSc programme is primarily written examinations, some with coursework element, in six lecture modules, plus oral presentations and assessed report on three research modules.

How to apply: http://www.kcl.ac.uk/study/postgraduate/apply/taught-courses.aspx

About Postgraduate Study at King’s College London:

To study for a postgraduate degree at King’s College London is to study at the city’s most central university and at one of the top 20 universities worldwide (2015/16 QS World Rankings). Graduates will benefit from close connections with the UK’s professional, political, legal, commercial, scientific and cultural life, while the excellent reputation of our MA and MRes programmes ensures our postgraduate alumni are highly sought after by some of the world’s most prestigious employers. We provide graduates with skills that are highly valued in business, government, academia and the professions.

Scholarships & Funding:

All current PGT offer-holders and new PGT applicants are welcome to apply for the scholarships. For more information and to learn how to apply visit: http://www.kcl.ac.uk/study/pg/funding/sources

Free language tuition with the Modern Language Centre:

If you are studying for any postgraduate taught degree at King’s you can take a module from a choice of over 25 languages without any additional cost. Visit: http://www.kcl.ac.uk/mlc

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This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights and routing mobile phone calls to managing investments and minimising risks. Read more

Programme description

This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights and routing mobile phone calls to managing investments and minimising risks. Operational Research (OR) is an important skill that is in high demand.

Our intensive programme allows you to specialise in an area that best suits your career goals. In addition to this general MSc in Operational Research, the following degrees are offered:

-Operational Research with Risk
-Operational Research with Computational Optimization

Programme structure

This programme involves two taught semesters of compulsory and option courses followed by your dissertation project.

Compulsory courses:

Computing for Operational Research and Finance
Fundamentals of Optimization
Fundamentals of Operational Research
Methodology, Modelling and Consulting Skills
Probability and Statistics
Simulation
Stochastic Modelling

Optional courses are generally grouped into the following areas:

Finance
Industry
Optimization
Statistics

Career opportunities

The skills you will learn are in demand by a vast range of high-profile organisations including consultancy firms, companies with operational research departments such as airlines or telecommunications providers, financial firms and the public sector.

Recent graduates have joined Capgemini, British Airways, Orange, Barrie & Hibbert and HM Revenue & Customs.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.

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This programme is designed to kick-start your career as an actuary, preparing you to take a leading role in managing risk in financial institutions worldwide. Read more
This programme is designed to kick-start your career as an actuary, preparing you to take a leading role in managing risk in financial institutions worldwide. Ranked top job in 2013 (as reported by Wall Street Journal), actuaries are in high demand in light of the need for sound decision making in the ever-changing financial markets. The rewards in terms of job satisfaction and earning potential make this an excellent career choice.

Established in 1972, we were the first UK university to introduce a dedicated programme in Actuarial Science, and have since evolved to become highly renowned as a world-leading centre in actuarial and financial teaching and research.
Exemptions

The programme is fully accredited by the UK Institute and Faculty of Actuaries, offering a valuable opportunity to gain exemptions from the Core Technical (CT1-CT8) examinations. There are 12 courses available which correspond in total to CT1-CT8 of the actuarial professional syllabus. To meet university award requirements you must pass at least 8 of the 12 listed below. To achieve exemption from all of CT1-CT8 you must pass all 12 courses.

Financial Mathematics - CT1
Finance and Financial Reporting - CT2
Economics - CT7
Statistical Methods - CT3
Life Insurance Maths 1 & 2 - CT5
Stochastic Modelling/Survival Models - CT4
Risk Theory/Time Series Analysis - CT6
Financial Economics 1 & 2 - CT8

Our expert staff, many of whom are qualified actuaries, will guide and support you throughout your studies. You will benefit from their extensive business knowledge and research expertise, whilst gaining hands-on experience of solving real-life financial problems through interactive lectures, tutorial sessions and practical coursework. The MSc summer project gives you the opportunity to explore in greater depth the hot topics currently facing business, such as Solvency II and pensions autoenrolment. Our close links to industry through the Scottish Financial Risk Academy also creates the potential for undertaking a summer placement within Edinburgh's thriving financial sector.

We have an excellent record of preparing students for successful careers - recent statistics show that around 90% of our postgraduate students were either in full-time employment or further study within 6 months of graduation. Our students consistently rate us highly - the Sunday Times University Guide 2013 named us "UK University of the Year for Student Experience" as well as "Scottish University of the Year" for the second year running.

We are very proud of our award-winning Students' Actuarial Society which is entirely managed, enthusiastically and professionally, by our students. As well as arranging a series of topical presentations by industry professionals, and popular social events, the Society's highly anticipated Annual Actuarial Conference attracts speakers and attendees from around the world.

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Mathematics is the science of structures, including mathematics itself. Discovery of new patterns and relations, and the construction of models with predictive power are the core of mathematics. Read more

Mathematical Sciences

Mathematics is the science of structures, including mathematics itself. Discovery of new patterns and relations, and the construction of models with predictive power are the core of mathematics.

Frequently, we see an interaction between fundamental and applied research. This versatility is reflected in the Master's programme Mathematical Sciences, which a broad range of courses is offered. Both students who want to specialise and students who aim for a wider background in mathematics.

[Tracks]]

You can tailor your programme by selecting one of the following seven tracks:
-Algebraic Geometry and Number Theory
-Applied Analysis
-Complex Systems
-Differential Geometry and Topology
-Logic
-Probability, Statistics, and Stochastic Modelling
-Pure Analysis
-Scientific Computing
-You can also choose to do a Research project in History of Mathematics.

This Master's programme offers a broad scope in a stimulating international environment which is renowned for its excellent research. Students who prefer to research subjects in depth will feel particularly at home at Mathematical Sciences.

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This MSc programme gives you the analytical skills essential to support data analysis, decision making and planning. Founded over 40 years ago, it is regarded by many employers as the UK’s premier degree in the field. Read more
This MSc programme gives you the analytical skills essential to support data analysis, decision making and planning. Founded over 40 years ago, it is regarded by many employers as the UK’s premier degree in the field. This programme is ideal if you wish to work in business analytics, decision support, industrial engineering, operational research and management science.

Our strong connections to industry and government ensure that what you learn on this MSc has a highly practical focus, both in teaching and in the three-month MSc summer projects. Graduates from the programme are in high demand, and recruited to organisations in many sectors, including roles in financial institutions, insurance, industry, retail, government, and consultancies.

Modules
• Applying Statistical Models in Business
• Computer Simulation
• Forecasting
• Introduction to Operational Research and Management Science
• Optimisation and Heuristics
• Problem Solving Skills for Consultants
• Problem Structuring
• Stochastic Modelling
• Spreadsheet Modelling

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Our Computer Science MPhil and PhD programme gives you an opportunity to make a unique contribution to computer science research. Read more
Our Computer Science MPhil and PhD programme gives you an opportunity to make a unique contribution to computer science research. Your research will be supported by an experienced computer scientist within a research group and with the support of a team of advisers.

Research supervision is available under our six research areas, reflecting our strengths, capabilities and critical mass.

Advanced Model-Based Engineering and Reasoning (AMBER)

The AMBER group aims to equip systems and software engineering practitioners with effective methods and tools for developing the most demanding computer systems. We do this by means of models with well-founded semantics. Such model-based engineering can help to detect optimal, or defective, designs long before commitment is made to implementations on real hardware.

Digital Interaction Group (DIG)

The Digital Interaction Group (DIG) is the leading academic research centre for human-computer interaction (HCI) and ubiquitous computing (Ubicomp) research outside of the USA. The group conducts research across a wide range of fundamental topics in HCI and Ubicomp, including:
-Interaction design methods, eg experience-centred and participatory design methods
-Interaction techniques and technologies
-Mobile and social computing
-Wearable computing
-Media computing
-Context-aware interaction
-Computational behaviour analysis

Applied research is conducted in partnership with the DIG’s many collaborators in domains including technology-enhanced learning, digital health, creative industries and sustainability. The group also hosts Newcastle University's cross-disciplinary EPSRC Centre for Doctoral Training in Digital Civics, which focusses on the use of digital technologies for innovation and delivery of community driven services. Each year the Centre awards 11 fully-funded four-year doctoral training studentships to Home/EU students.

Interdisciplinary Computing and Complex BioSystems (ICOS)

ICOS carries out research at the interface of computing science and complex biological systems. We seek to create the next generation of algorithms that provide innovative solutions to problems arising in natural or synthetic systems. We do this by leveraging our interdisciplinary expertise in machine intelligence, complex systems and computational biology and pursue collaborative activities with relevant stakeholders.

Scalable Computing

The Scalable Systems Group creates the enabling technology we need to deliver tomorrow's large-scale services. This includes work on:
-Scalable cloud computing
-Big data analytics
-Distributed algorithms
-Stochastic modelling
-Performance analysis
-Data provenance
-Concurrency
-Real-time simulation
-Video game technologies
-Green computing

Secure and Resilient Systems

The Secure and Resilient Systems group investigates fundamental concepts, development techniques, models, architectures and mechanisms that directly contribute to creating dependable and secure information systems, networks and infrastructures. We aim to target real-world challenges to the dependability and security of the next generation information systems, cyber-physical systems and critical infrastructures.

Teaching Innovation Group

The Teaching Innovation Group focusses on encouraging, fostering and pursuing innovation in teaching computing science. Through this group, your research will focus on pedagogy and you will apply your research to maximising the impact of innovative teaching practices, programmes and curricula in the School. Examples of innovation work within the group include:
-Teacher training and the national Computing at School initiative
-Outreach activities including visits to schools and hosting visits by schools
-Participation in national fora for teaching innovation
-Market research for new degree programmes
-Review of existing degree programmes
-Developing employability skills
-Maintaining links with industry
-Establishing teaching requirements for the move to Science Central

Research Excellence

Our research excellence in the School of Computing Science has been widely recognised through awards of large research grants. Recent examples include:
-Engineering and Physical Sciences Research Council (EPSRC), Centre for Doctoral Training in Cloud Computing for Big Data Doctoral Training Centre
-Engineering and Physical Sciences Research Council (EPSRC), Centre for Doctoral Training in Digital Civics
-Wellcome Trust and Engineering and Physical Sciences Research Council (EPSRC) Research Grant: a £10m project to look at novel treatment for epilepsy, confirming our track record in Systems Neuroscience and Neuroinformatics.

Accreditation

The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.

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Take advantage of one of our 100 Master’s Scholarships to study Stochastic Processes. Theory and Application at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Stochastic Processes: Theory and Application at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

The MRes in Stochastic Processes: Theory and Application is delivered through optional modules for the taught element followed by a large research project that contributes to the field in an explicit way, rather than merely applying existing knowledge.

The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.

The Department’s research groups include:

Algebra and Topology Group
Areas of interest include: Noncommutative geometry, Categorical methods in algebra and topology, Homotopy theory and homological algebra and others.

Analysis and Nonlinear Partial Differential Equations Group
Areas of interest include: Reaction-diffusion and reaction-diffusion-convection equations and systems, Navier–Stokes equations in fluid dynamic, Complexity in the calculus of variations and others.

Stochastic Analysis Group
Areas of interest include: Functional inequalities and applications, Lévy-type processes, Stochastic modelling of fractal, multi-fractal and multi-scale systems, Infinite dimensional stochastic analysis and others.

Mathematical Methods in Biology and Life Sciences Group
Areas of interest include: Mathematical pharmacology; heat and mass transfer models for plant cooling; modelling cellular signal transduction dynamics; mathematical oncology: multi-scale modelling of cancer growth, progression and therapies, and modelling-optimized delivery of multi-modality therapies; multi-scale analysis of individual-based models; spreading speeds and travelling waves in ecology; high performance computing.

Key Features

The Department of Mathematics hosts one of the strongest research groups in probability theory, especially in stochastic processes, in the UK. The senior members of this group are world leaders in their fields.

Course Content

As a student on the MRes Stochastic Processes programme you will study a range of topics for the taught element including:

Stochastic Calculus based on Brownian Motion
Levy processes and more general jump processes
The advanced Black-Scholes theory
Theory and numerics of parabolic differential equations
Java programming

The Stochastic Processes: Theory and Application course consists of a taught part (60 credits) and a research project (120 credits). Students will have a personal supervisor for their research project from the start of their studies.

Research projects could be of a theoretical mathematical nature, or they could be more applied, for example in financial mathematics or actuarial studies. Some of the research projects will be of an interdisciplinary character in collaboration with some of Swansea's world class engineers. For such projects it is likely that EPSRC funding would be available.

Facilities

The Aubrey Truman Reading Room, located in the centre of the Department of Mathematics, houses the departmental library and computers for student use. It is a popular venue for students to work independently on the regular example sheets set by their lecturers, and to discuss Mathematics together.

Our main university library, Information Services and Systems (ISS), contains a notably extensive collection of Mathematics books.

Careers

The ability to think rationally and to process data clearly and accurately are highly valued by employers. Mathematics graduates earn on average 50% more than most other graduates. The most popular areas are the actuarial profession, the financial sector, IT, computer programming and systems administration, and opportunities within business and industry where employers need mathematicians for research and development, statistical analysis, marketing and sales.

Some of our students have been employed by AXA, BA, Deutsche Bank, Shell Research, Health Authorities and Local Government. Teaching is another area where maths graduates will find plenty of career opportunities.

Research

The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Department supports research staff and students) and the impact of our research (its value to society) were both judged to be 100% world leading or internationally excellent.

All academic staff in Mathematics are active researchers and the department has a thriving research culture.

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Take advantage of one of our 100 Master’s Scholarships to study Mathematics at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Read more
Take advantage of one of our 100 Master’s Scholarships to study Mathematics at Swansea University, the Times Good University Guide’s Welsh University of the Year 2017. Postgraduate loans are also available to English and Welsh domiciled students. For more information on fees and funding please visit our website.

As an MSc by Research in Mathematics student you will be guided by internationally leading researchers and will carry out a large individual research project.

You will be fully integrated into one of our established research groups and participate in research activities such as seminars, workshops, laboratories, and field work.

Key Features

Swansea is a research-led University and the Mathematics Department makes a significant contribution, meaning that as a postgraduate Mathematics student you will benefit from the knowledge and skills of internationally renowned academics.

In the Department of Mathematics at Swansea you will find friendly teaching staff that are fully committed to providing you with a supportive teaching and learning environment. This includes outstanding student support.

All postgraduate Mathematics programmes at Swansea will equip you with skills relevant for a rewarding career in a range of diverse fields. You will also further develop your communication, presentation and analytical skills.

The Mathematics Department’s research groups include:

Algebra and Topology Group

Areas of interest include: Noncommutative geometry, Categorical methods in algebra and topology, Homotopy theory and homological algebra and others.

Analysis and Nonlinear Partial Differential Equations Group

Areas of interest include: Reaction-diffusion and reaction-diffusion-convection equations and systems, Navier–Stokes equations in fluid dynamic, Complexity in the calculus of variations and others.

Stochastic Analysis Group

Areas of interest include: Functional inequalities and applications, Lévy-type processes, Stochastic modelling of fractal, multifractal and multiscale systems, Infinite dimensional stochastic analysis and others.

Mathematical Methods in Biology and Life Sciences Group

Areas of interest include: Mathematical pharmacology; heat and mass transfer models for plant cooling; modelling cellular signal transduction dynamics; mathematical oncology: multi-scale modelling of cancer growth, progression and therapies, and modelling-optimized delivery of multi-modality therapies; multi-scale analysis of individual-based models; spreading speeds and travelling waves in ecology; high performance computing

Employability

The ability to think rationally and to process data clearly and accurately are highly valued by employers. Mathematics graduates earn on average 50% more than most other graduates. The most popular areas are the actuarial profession, the financial sector, IT, computer programming and systems administration, and opportunities within business and industry where employers need mathematicians for research and development, statistical analysis, marketing and sales.

Facilities

The Aubrey Truman Reading Room, located in the centre of the Department of Mathematics, houses the departmental library and computers for student use, and is a popular venue for students to work independently on the regular exercise sheets set by their lecturers, and to discuss mathematics together.

The main university library, the Learning and Information Centre (LIC), contains a notably extensive collection of mathematics books.

As part of our expansion, we are building the Computational Foundry on our Bay Campus for computer and mathematical sciences. This development is exciting news for Swansea Mathematics who are part of the vibrant and growing community of world-class research leaders drawn from computer and mathematical sciences.

Research

The results of the Research Excellence Framework (REF) 2014 show that our research environment (how the Mathematics Department supports research staff and students) and the impact of our research (its value to society) were both judged to be 100% world leading or internationally excellent.

All academic staff in Mathematics are active researchers and the department has a thriving research culture.

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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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This programme gives you a flexible syllabus to suit the demands of employers that use modern financial tools and optimization techniques in areas such as the financial sector and energy markets. Read more

Programme description

This programme gives you a flexible syllabus to suit the demands of employers that use modern financial tools and optimization techniques in areas such as the financial sector and energy markets.

We will give you sound knowledge in financial derivative pricing, portfolio optimization and financial risk management.

We will also provide you with the skills to solve some of today’s financial problems, which have themselves been caused by modern financial instruments. This expertise includes modern probability theory, applied statistics, stochastic analysis and optimization.

Adding depth to your learning, our work placement programme puts you at the heart of financial organisations such as Aberdeen Asset Management, Barrie & Hibbert and Lloyds Banking Group.

Programme structure

This programme involves two taught semesters of compulsory and option courses, followed by a dissertation project.

Compulsory courses:

Discrete-Time Finance
Finance, Risk and Uncertainty
Fundamentals of Optimization
Optimization Methods in Finance
Research-Linked Topics
Risk-Neutral Asset Pricing
Simulation
Stochastic Analysis in Finance I
Stochastic Analysis in Finance II

Option courses:

Advanced Time Series Econometrics
Combinatorial Optimization
Credit Scoring
Fundamentals of Operational Research
Financial Risk Management
Computing for Operational Research and Finance
Large Scale Optimization for Data Science
Microeconomics 2
Nonlinear Optimization
Numerical Partial Differential Equations
Parallel Numerical Algorithms
Programming Skills
Risk Analysis
Stochastic Modelling
Stochastic Optimization

Career opportunities

Graduates have gone on to work in major financial institutions or to continue their studies by joining PhD programmes.

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This programme will show you how to use mathematical techniques to model and solve real-life financial problems. Operational research is an important skill that is in high demand in the finance industry. Read more

This programme will not be delivered in 2016/17.

Programme description

This programme will show you how to use mathematical techniques to model and solve real-life financial problems. Operational research is an important skill that is in high demand in the finance industry.

Programme structure

This programme involves two taught semesters of compulsory and optional courses followed by your dissertation project.

Compulsory courses

Computing for Operational Research and Finance
Fundamentals of Operational Research
Financial Mathematics and Investment
Financial Risk Management
Methodology, Modelling and Consulting Skills
Simulation
Stochastic Modelling

Optional courses are generally grouped into the following areas:

Finance
Industry
Optimization
Statistics

Learning outcomes

By studying Operational Research you will develop a highly marketable combination of mathematical, modelling, analytical, computing, interpersonal and communication skills.

Career opportunities

The skills you will learn are in demand by a vast range of organisations such as professional consultancy firms, big companies with operational research departments like airlines or telecommunications providers, smaller financial firms and the public sector.

Recent graduates have joined Capgemini, British Airways, Orange, Moody's and HM Revenue & Customs.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.

Read less
This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights and routing mobile phone calls to managing investments and minimising risks. Read more

Programme description

This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights and routing mobile phone calls to managing investments and minimising risks. Operational Research (OR) is an important skill that is in high demand.

This MSc will give an Operational Research perspective on computational optimization.

Programme structure

This programme involves two taught semesters of compulsory and option courses followed by your dissertation project.

Compulsory courses:

Computing for Operational Research and Finance
Fundamentals of Optimization
Fundamentals of Operational Research
Methodology, Modelling and Consulting Skills
Probability and Statistics
Simulation
Stochastic Modelling

As part of your option course choices, Operational Research with Computational Optimization requires you to study a combination from:

Stochastic Optimization
Combinatorial Optimization
Nonlinear Optimization
Large Scale Optimization for Data Science.

Career opportunities

The skills you will learn are in demand by a vast range of high-profile organisations including consultancy firms, companies with operational research departments such as airlines or telecommunications providers, financial firms and the public sector.

Recent graduates have joined British Airways, the Government OR Service, Barclays, Deloitte, Capgemini and smaller specialised OR, finance and energy companies.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.

Read less
This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights and routing mobile phone calls to managing investments and minimising risks. Read more

Programme description

This programme will show you how to use mathematical techniques to tackle real-life problems ranging from scheduling flights and routing mobile phone calls to managing investments and minimising risks. Operational Research (OR) is an important skill that is in high demand.

This MSc will give an Operational Research perspective on risk and its management.

Programme structure

This programme involves two taught semesters of compulsory and option courses followed by your dissertation project.

Compulsory courses:

Computing for OR and Finance
Fundamentals of Optimization
Fundamentals of OR
Methodology, Modelling and Consulting Skills
Probability and Statistics
Simulation
Stochastic Modelling

Option courses are generally grouped into the following areas:

Finance
Industry
Optimization
Statistics

As part of your option course choices Operational Research with Risk requires you to study a combination from:

Credit Scoring
Financial Risk Management
Stochastic Optimization
The Analysis of Survival Data
Statistical Modelling
Risk Analysis

Career opportunities

The skills you will learn are in demand by a vast range of high-profile organisations including consultancy firms, companies with operational research departments such as airlines or telecommunications providers, financial firms and the public sector.

Recent graduates have joined British Airways, the Government OR Service, Barclays, Deloitte, Capgemini and smaller specialised OR, finance and energy companies.

Industry-based dissertation projects

The dissertation projects of approximately half the students on this programme take place in public and private sector organisations. Other students choose a University-based project.

Read less

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