Specialised MSc Degrees

NFQ Level 9, Major Award

Entry Requirements - Direct Entry
Candidates must have obtained at least a Second Class Honours degree or equivalent in a subject(s) related to that/those of the MSc programme. Candidates must be approved by the Head of Department and/or the Co-ordinator of the MSc programme. The number of places is limited and selection will be made on the basis of the candidate's performance in his/her primary degree. Bridging courses may be assigned as a prerequisite depending on the background of the individual candidate.

Entry Requirements - via the Higher Diploma in Applied Science
Candidates who have completed the Higher Diploma in Applied Science in a subject closely related to that of the MSc will be considered for entry into the MSc programme. Unless otherwise stated (see below), candidates must have achieved a mark of at least Second Class Honours, Grade II at the first attempt in the Higher Diploma in Applied Science programme. The MSc will be by Research or Taught as appropriate to the subject for at least 12 months from the date of first registration for the programme. Candidates will not be allowed to repeat the Higher Diploma examinations to gain entry to the MSc degree programme. If necessary, additional coursework will be specified for a student at the discretion of the Head of Department and/or the Co-ordinator of the MSc Programme.

The MSc may be taken full-time over 12 months or part-time over 24 months from the date of first registration for the programme. It consists of (i) lectures, (ii) laboratory work on set experiments and (iii) a dissertation based on individual research and development in the selected field of modern analytical science, under the supervision of an expert staff member. Candidates may need to secure appropriate day release from industry. Part of the lecture course will also be available through online blended e-learning.

Entry Requirements - Direct Entry
Candidates must have obtained at least a Second Class Honours degree or equivalent in a subject(s) related to that of the MSc programme. The number of places is limited and selection will be made on the basis of the candidate's performance in his/her primary degree. Graduates with equivalent qualifications in related areas of science and technology, or with proven and relevant industrial experience can be considered for places following interview and assessment. Candidates must be approved by the Professor of Analytical Chemistry and/or the Co-ordinator of the MSc Programme, and by the College of Science, Engineering and Food Science. Bridging courses may be assigned as a prerequisite depending on the background of the individual candidate. Part-time candidates with sufficient day release time can sit for the written examinations after 12 months from the date of first registration for the programme, provided that they have completed all required coursework.

Entry Requirements - via the Postgraduate Diploma
Candidates having obtained at least a Second Class Honours, Grade I at the first attempt in a Postgraduate Diploma course in a cognate area of science and technology are eligible to apply. Candidates having obtained at least a Second Class Honours, Grade I at the first attempt in the Postgraduate Diploma course (in any of these analytical science programmes offered at UCC), can qualify to convert to the MSc programme in the same year, and be permitted to undertake the Research Dissertation Module, as directed by the Professor of Analytical Chemistry or the Programme Co-ordinator.

Programme Requirements
The MSc Degree is awarded to successful candidates after passing written examinations across all taught modules, including the continuously assessed practical module CM6015, and the research project (from CM6020-22), which has to be written up in the form of a dissertation and approved by the external examiner.

Students take 90 credits as follows:

Part I
CM6012 Modern Analytical Techniques, Chemical Data Analysis and GLP (10 credits)
CM6013 Separation Science, Sensors and Process Analytical Technology (10 credits)
CM6014 Materials, Pharmaceutical and Bio-analysis (10 credits)
CM6015 Practice of Analytical Chemistry (10 credits)
CM6026 Industry Led Workshops (5 credits)
CM6027 Taught Postgraduate Transferable Skills Development (5 credits)

Plus 10 credits from the following areas of application:
EV4002 Environmental Monitoring (10 credits)
or
PF6301 Biopharmaceuticals: Formulation Design, Secondary Processing and Regulatory Compliance (10 credits)

Part II
Plus ONE of the following Research Projects:
CM6020 Research Project and Dissertation in Analytical Chemistry (30 credits)
CM6021 Research Project and Dissertation in Environmental Analytical Chemistry (30 credits)
CM6022 Research Project and Dissertation in Pharmaceutical Analysis (30 credits)

NOTE: The choice of Research Project informs the choice of MSc programme.

Analysis of Pharmaceutical Compounds
Module Semester Information may be found here. Module Descriptions may be found here.
Analytical Chemistry
Module Semester Information may be found here. Module Descriptions may be found here.
Environmental Analytical Chemistry
Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2019/2020 Book and for each module in the Book of Modules, 2019/2020.

Learning Outcomes for MSc (Analysis of Pharmaceutical Compounds) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Identify, formulate, analyse and solve problems in the analysis of pharmaceutical compounds;
• Outline fundamental and applied aspects of pharmaceutical analysis;
• Design and carry out a method of pharmaceutical analysis, including instrumental analysis;
• Prepare written laboratory reports that provide a description of the experiment, explain the experiment and reasoning clearly, and provide an appropriate conclusion;
• Communicate effectively with the chemistry and pharmaceutical communities;
• Carry out research and method development in pharmaceutical analysis;
• Prepare a written research report in the form of a dissertation.

Learning Outcomes for MSc (Analytical Chemistry) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Identify, formulate, analyse and solve analytical chemistry problems;
• Outline fundamental and applied aspects of analytical chemistry;
• Design and carry out a method of chemical analysis, including instrumental analysis;
• Prepare written laboratory reports that provide a description of the experiment, explain the experiment and reasoning clearly, and provide an appropriate conclusion;
• Communicate effectively with the chemistry and analytical science communities;
• Carry out research and method development in analytical science;
• Prepare a written research report in the form of a dissertation.

Learning Outcomes for MSc (Environmental Analytical Chemistry) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Identify, formulate, analyse and solve environmental analytical chemistry problems;
• Outline fundamental and applied aspects of environmental analytical chemistry;
• Design and carry out a method of environmental chemical analysis, including instrumental analysis;
• Prepare written laboratory reports that provide a description of the experiment, explain the experiment and reasoning clearly, and provide an appropriate conclusion;
• Communicate effectively with the chemistry and environmental science communities;
• Carry out research and method development in environmental analytical science;
• Prepare a written research report in the form of a dissertation.

The MSc (Biotechnology) is a full-time intensive course running for 12 months from the date of first registration for the programme.

Entry Requirements - Direct Entry

Applicants must have obtained at least a Second Class Honours, Grade I degree in the biological sciences, pharmaceutical sciences or equivalent in a subject(s) related to that of the MSc programme. Candidates with Second Class Honours, Grade II will be considered on a case-by-case basis. Graduates with equivalent qualifications in related areas of science and technology, or with proven and relevant industrial experience can be considered for places following interview and assessment by the Director of the MSc (Biotechnology) Programme. Candidates must be approved by the MSc (Biotechnology) course team and/or the Director of the MSc (Biotechnology) Programme. The number of places is limited and selection will be made on the basis of the candidate's performance in his/her primary degree or interview.

Programme Requirements
The programme will consist of lectures, tutorials, and set practical sessions, with the emphasis on training in modern techniques of biotechnology. The MSc Degree (Biotechnology) is awarded to successful candidates after passing written examinations across all eight taught modules, the continuous assessment of practical work and a six-month research project (BT6002), which has to be written up in the form of a dissertation and approved by the external examiner.

Students take 90 credits as follows:

BC6001 Cell and Molecular Biology (5 credits)
BT6001 Genetic Engineering (5 credits)
CM6011 Modern Methods in Analytical Chemistry (5 credits)
MB6003 Functional Foods for Health (5 credits)
MB6004 Advanced Molecular Microbial Biotechnology (5 credits)
PF6301 Biopharmaceuticals: Formulation Design, Secondary Processing and Regulatory Compliance (10 credits)
PS6001 Plant Genetic Engineering (5 credits)
either PE6008 Bioprocess Engineering (10 credits)* or
BT6003 Advanced Case Studies in Biotechnology (10 credits)*
BT6002 Dissertation in Biotechnology* (40 credits)

*Students opting to complete BT6002 in a research setting can select either PE6008 or BT6003 in consultation with the course Director. Students opting to complete BT6002 in an industrial setting must complete PE6008. In the case of a student who has previously passed the content covered in PE6008 the student will complete BT6003 subject to the agreement of the course Director.

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2019/2020 Book and for each module in the Book of Modules, 2019/2020.

Postgraduate Certificate in Biotechnology
Students who attain a pass (40%) across the taught modules, but do not reach the 50% threshold required to progress to the research dissertation will be conferred with a Postgraduate Certificate in Biotechnology. Similarly, students who pass the taught modules and do not wish to complete the research dissertation may opt to be conferred with a Postgraduate Certificate in Biotechnology.

Learning Outcomes for MSc (Biotechnology) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Discuss the theory and practice of bio analytical Chemistry;
• Review Molecular Biotechnology, Eukaryotic-, Prokaryotic- and Plant-Biotechnologies, recombinant DNA technologies and their application in the Biotechnology and Biopharmaceutical Industries;
• Apply fundamentals in Process and Biochemical Engineering to the Biotechnology sector;
• Outline the role of Process Validation and Quality Assurance in pharmaceutical industry;
• Discuss the latest trends in good manufacturing, laboratory and validation practices;
• Assess the principles of Food and Industrial Microbiology;
• Complete a body of independent research in a biotechnology-related area and present research findings in a minor dissertation.

Learning Outcomes for Postgraduate Certificate in Biotechnology (NFQ Level 9, Minor Award)
On successful completion of this programme, students should be able to:

• Discuss the theory and practice of bio analytical Chemistry;
• Review Molecular Biotechnology, Eukaryotic-, Prokaryotic- and Plant-Biotechnologies, recombinant DNA technologies and their application in the Biotechnology and Biopharmaceutical Industries;
• Apply fundamentals in Process and Biochemical Engineering to the Biotechnology sector;
• Outline the role of Process Validation and Quality Assurance in pharmaceutical industry;
• Discuss the latest trends in good manufacturing, laboratory and validation practices;
• Assess the principles of Food and Industrial Microbiology.

The MSc (Bioinformatics and Computational Biology) may be taken full-time over 12 months or part-time over 24 months from the date of first registration for the programme. The MSc programme has four different streams: for Biology, Mathematics, Statistics and Computer Science graduates, respectively [for graduates of cognate disciplines, the assignment to a particular stream will be decided by the Programme Director].

Entry Requirements
Entrants to the programme must be holders of an Honours Bachelor degree, or equivalent qualification, in a discipline with a significant element of Mathematics, Statistics, Engineering, Computer Science or Biology, with a minimum of Second Class Honours Grade 1. In addition, candidates with Second Class Honours Grade 2 may also be considered for places, following assessment by the Programme Director if they are also proficient in mathematics as evident from grades in Higher Leaving Cert maths or Undergraduate maths modules, and have at least one year of proven and relevant Biological, Mathematical or Computational work or Postgraduate experience.

Note: Admission to the MSc course will be based on compliance with prerequisites to the individual modules or permission given by a module co-ordinator when an applicant is deemed to have taken a module that is considered to be equivalent to the prerequisite(s).

Programme Requirements
Part-time students take between five and seven of their twelve taught modules in each academic year and undertake the project in the second academic year. The modules to be taken by the part-time students in each of their two academic years are specified by the course director.

Note: Students cannot choose a module that they have already completed (for example, as part of their undergraduate degree). Evidence for this would be the production of a transcript showing all modules taken in their previous degree programme(s).

Stream for Biological Science Graduates
Students take 90 credits as follows:
AM6014 Mathematical Modelling for Biological and Environmental Sciences (5 credits)
CS5002 Web Development 1 (5 credits)
CS6503 Introduction to Relational Databases (5 credits)
CS6405 Datamining (5 credits)
CS6501 Programming for Bioscientists I (5 credits)
CS6502 Programming for Bioscientists II (5 credits)
MB6300 Computational Systems Biology (5 credits)
MB6301 Genomic Data Analysis (5 credits)
MB6303 Dissertation in Bioinformatics and Computational Biology (30 credits)
MS6005 Discrete Mathematics (5 credits)
ST3300 Data Analysis I (5 credits)
ST4400 Data Analysis II (5 credits)
ST5005 Introduction to Probability and Statistics (5 credits)

Stream for Computer Science Graduates
Students take 90 credits as follows:
ST5005 Introduction to Probability and Statistics (5 credits)
BC6002 Molecular Biology (5 credits)
BC6003 Biomolecules (5 credits)
BL6023 Cells, Biomolecules, Genetics and Evolution (5 credits)
CS6405 Datamining (5 credits)
CS6501 Programming for Bioscientists I (5 credits)
CS6502 Programming for Bioscientists II (5 credits)
MB6300 Computational Systems Biology (5 credits)
MB6301 Genomic Data Analysis (5 credits)
MB6303 Dissertation in Bioinformatics and Computational Biology (30 credits)
MS6005 Discrete Mathematics (5 credits)
ST3300 Data Analysis I (5 credits)
ST4400 Data Analysis II (5 credits)

Stream for Mathematics Graduates
Students take 90 credits as follows:
Choice of ST3300 Data Analysis I (5 credits)
or ST4400 Data Analysis II (5 credits)
AM6014 Mathematical Modelling for Biological and Environmental Sciences (5 credits)
BC6002 Molecular Biology (5 credits)
BC6003 Biomolecules (5 credits)
BL6023 Cells, Biomolecules, Genetics and Evolution (5 credits)
CS5002 Web Development 1 (5 credits)
CS6405 Datamining (5 credits)
CS6501 Programming for Bioscientists I (5 credits)
CS6502 Programming for Bioscientists II (5 credits)
CS6503 Introduction to Relational Databases (5 credits)
MB6300 Computational Systems Biology (5 credits)
MB6301 Genomic Data Analysis (5 credits)
MB6303 Dissertation in Bioinformatics and Computational Biology (30 credits)

Stream for Statistics Graduates
Students take 90 credits as follows:
AM6014 Mathematical Modelling for Biological and Environmental Sciences (5 credits)
BC6002 Molecular Biology (5 credits)
BC6003 Biomolecules (5 credits)
BL6023 Cells, Biomolecules, Genetics and Evolution (5 credits)
CS5002 Web Development 1 (5 credits)
CS6503 Introduction to Relational Databases (5 credits)
CS6405 Datamining (5 credits)
CS6501 Programming for Bioscientists I (5 credits)
CS6502 Programming for Bioscientists II (5 credits)
MB6300 Computational Systems Biology (5 credits)
MB6301 Genomic Data Analysis (5 credits)
MB6303 Dissertation in Bioinformatics and Computational Biology (30 credits)
MS6005 Discrete Mathematics (5 credits)

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2019/2020 Book and for each module in the Book of Modules, 2019/2020.

Postgraduate Diploma in Bioinformatics and Computational Biology
Students who do not reach the average mark of 50% threshold required to progress to the research dissertation will be conferred with a Postgraduate Diploma in Bioinformatics and Computational Biology. Similarly, students who pass the taught modules and do not wish to complete the research dissertation, may opt to be conferred with a Postgraduate Diploma in Bioinformatics and Computational Biology.

Learning Outcomes for MSc (Bioinformatics and Computational Biology) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Have a solid background in the theory behind bioinformatics methods and tools so that they can critically evaluate research in bioinformatics;
• Use existing bioinformatics methods and tools and rapidly learn to apply new methods and tools;
• Organise and analyse large data sets generated by genomics and systems biology approaches;
• Understand the role of modelling and simulation of biological systems;
• Have a deep knowledge of the aspect of bioinformatics in which they carried out their three-month research project. This experience will prepare them for a future research career in the bioinformatics field.

The MSc in Geographical Information Systems and Remote Sensing is a full-time programme running for 12 months from the date of first registration for the programme.

Entry Requirements
Candidates must have obtained at least a Second Class Honours degree or equivalent in a subject related to that of the MSc programme, e.g. Geography, Geology, Environmental Sciences, Computer Science, Physics, Maths, Engineering or a cognate discipline. Graduates with equivalent qualifications in related areas of science and technology can be considered for places following inteview and/or assessment by the Director of the MSc in Geographical Information Systems and Remote Sensing programme. The programme Director and/or the College of Science, Engineering and Food Science, UCC must approve candidates. The number of places is limited and selection will be based on academic achievement, relevant work experience, a personal statement from the applicant and/or an interview. Where relevant, candidates will have to prove their proficiency in the English language (spoken and written) by achieving at least a score of 6.5 or higher in an IELTS test (International English Language Testing System).

Programme Requirements
The programme will consist of two parts. Part I will consist of eleven taught modules to the value of 60 credits involving lectures, practicals, seminars and workshops. Part II will be a substantial research dissertation to the value of 30 credits (GG6511) for those meeting progression requirements of Part I of the programme. Each of the prescribed taught modules will be examined by a written paper and/or continuous assessment. Each candidate progressing to Part II of the programme must submit the research dissertation (GG6511) in an area of Geoinformatics by September 1st in the academic year of registration for the programme. Research dissertations can be carried out in the university or with the support of a commercial placement.

Students take 90 credits as follows:

Part I
GG6501 Introduction to Geographical Information Systems (5 credits)
GG6502 Introduction to Remote Sensing (5 credits)
GG6503 Cartography and Visualisation (5 credits)
GG6504 Digital Image Processing (5 credits)
GG6505 Application of Geoinformatics (10 credits)
GG6507 Implementation of Geoinformatics (5 credits)
GG6509 Spatial Data Analysis (5 credits)
GG6529 Geoinformatics Data Collection and Analysis (10 credits)
GG6530 GeoComputation (5 credits)
GG6531 Computer Programming for GIS Applications (5 credits)

Part II
GG6511 Dissertation in Geoinformatics (30 credits)

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2019/2020 Book and for each module in the Book of Modules, 2019/2020.

Postgraduate Diploma in Geographical Information Systems and Remote Sensing
Candidates who obtain an average mark of at least 40% across the taught modules, and pass all modules at 40% or more in Part I but do not achieve a mark of 40% in the dissertation or do not wish to complete Part II may opt to be conferred with a Postgraduate Diploma in Geographical Information Systems and Remote Sensing.

Learning Outcomes for MSc (Geographical Information Systems and Remote Sensing) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Describe the theoretical and practical principles and concepts that underpin technologies of Geographical Information Systems (GIS), Remote Sensing, and related areas of Geoinformatics;
• Evaluate the potential of different Geoinformatics approaches for application to spatial problems in a variety of sectors, at scales from the local to the global;
• Identify and assess appropriate Geoinformatics methods and technologies for the resolution of these problems;
• Demonstrate skills and knowledge in the application, integration and use of geoinformatics technologies including computational analysis, fieldwork, numerical modelling and computer programming, using different software and programming packages;
• Write reports and prepare cartographic materials to a professional standard;
• Prepare and present seminars to a professional standard;
• Design, implement and manage a Geoinformatics-based project, from conception of ideas to the generation of final output products;
• Discuss issues of good practice, and understand key policies, strategies and infrastructures that apply to the effective and appropriate use of these technologies, and the implications of their use for society at large.

Learning Outcomes for Postgraduate Diploma in Geographical Information Systems and Remote Sensing (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Describe the theoretical and practical principles and concepts that underpin technologies of Geographical Information Systems (GIS), Remote Sensing, and related areas of Geoinformatics;
• Evaluate the potential of different Geoinformatics approaches for application to spatial problems in a variety of sectors, at scales from the local to the global;
• Identify and assess appropriate Geoinformatics methods and technologies for the resolution of these problems;
• Demonstrate skills and knowledge in the application, integration and use of geoinformatics technologies including computational analysis, fieldwork, numerical modelling and computer programming, using different software and programming packages;
• Write reports and prepare cartographic materials to a professional standard;
• Prepare and present seminars to a professional standard;
• Discuss issues of good practice, and understand key policies, strategies and infrastructures that apply to the effective and appropriate use of these technologies, and the implications of their use for society at large.

The MSc in Marine Biology is a full-time multidisciplinary degree running for 12 months from the date of first registration for the programme.

Entry Requirements
A candidate for the MSc in Marine Biology must have obtained at least a Second Class Honours, Grade II degree in any Biological or Environmental Science or relevant equivalent area. In addition, NFQ Level 8 graduates with relevant professional qualifications or relevant experience but not the relevant degree classification may also apply for entry and each case will be judged on a case-by-case basis as to their suitability for the programme, subject to the approval of the Programme Director. Where relevant, candidates will have to prove their proficiency in the English language (spoken and written) by achieving at least a score of 7.0 overall, 7.0 for the written category and at least 6.5 in the remaining categories (International English Language Testing System).

Programme Requirements
This programme will consist of Part I and Part II. Part I will consist of eight taught modules to the value of 60 credits involving lectures, practicals, seminars and fieldwork. Part II will be a substantial Research Dissertation (BL6017) to the value of 30 credits for those meeting progression requirements of Part I of the programme. Each of the prescribed taught modules will be examined by a written paper and/or continuous assessment. Each candidate progressing to Part II of the programme must submit the Research Dissertation (BL6017) in an area of Marine Biology by a date in August of the registration year as prescribed by the School of BEES.

Students take 90 credits as follows:

Part I
BL6012 Marine Megafauna (10 credits)
BL6013 Marine Fisheries and Aquaculture (10 credits)
BL6014 Marine Fieldwork and Survey Techniques (10 credits)
BL6015 Practical Marine Workplace Skills (5 credits)
BL6016 Marine Ecology and Conservation (10 credits)
BL6019 Ecological Applications of Geographical Information Systems (5 credits)
BL6020 Genetics and the Marine Environment (5 credits)
BL6025 Innovation and Ocean Sustainability (5 credits)

Part II
BL6017 Dissertation in Marine Biology (30 credits)

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2019/2020 Book and for each module in the Book of Modules, 2019/2020.

Postgraduate Diploma in Marine Biology
Students who achieve 40% in each individual taught module in Part I but fail to achieve the requisite grade of 50% across the taught modules, or students who pass Part I and do not wish to complete the Research Dissertation (Part II) may opt to be conferred with a Postgraduate Diploma in Marine Biology.

Learning Outcomes for MSc (Marine Biology) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Recall marine flora and fauna, the marine environment and its biological and physical properties and processes;
• Assess the sustainability of exploitation (fisheries and aquaculture) and assess the impact of other anthropogenic factors on the marine environment;
• Define the roles of management and conservation across the marine environment;
• Demonstrate a wide range of research skills (field and laboratory) including safety related and professional qualifications;
• Undertake independent research in the field of Marine Biology;
• Apply the skills acquired in this course in the working environment enabling the development of policy.

Learning Outcomes for Postgraduate Diploma in Marine Biology (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Recall marine flora and fauna, the marine environment and its biological and physical properties and processes;
• Assess the sustainability of exploitation (fisheries and aquaculture) and assess the impact of other anthropogenic factors on the marine environment;
• Define the roles of management and conservation across the marine environment;
• Demonstrate a wide range of research skills (field and laboratory) including safety related and professional qualifications;
• Apply the skills acquired in this course in the working environment enabling the development of policy.

*This programme is being phased out and replaced by the MSc (Mathematical Modelling and Self-Learning Systems). Students who entered prior to 2018/19 follow the curriculum detailed below. Students entering from 2018/19 onwards follow the curriculum detailed here.

The MSc in Mathematical Modelling and Scientific Computing is a full-time programme running for 12 months or part-time runnng for 24 months from the date of first registration for the programme. The programme may also be taken online.

Entry Requirements
Candidates must have obtained at least a Second Class Honours degree or equivalent in a numerate discipline (i.e. Science or Engineering). Candidates from Grandes Écoles Colleges are also eligible to apply if they are studying a cognate discipline in an ENSEA or EFREI Graduate School and are eligible to enter the final year (M2) of their programme. All candidates must ultimately be approved by the director of the MSc (Mathematical Modelling and Scientific Computing) programme. In the case of competition for places selection will be made on the basis of primary degree results and/or interview.

Programme Requirements

Students take 90 credits as follows:

AM6001 Introduction to Mathematica (5 credits) (not on offer in 2018/19)
AM6002 Numerical Analysis with Mathematica (5 credits) (not on offer in 2018/19)
AM6003 Cellular Automata (5 credits) (not on offer in 2018/19)
AM6004 Applied Numerical Analysis (5 credits)
AM6005 Modelling of Systems with Strong Nonlinearities (5 credits)
AM6006 Mathematical Modelling of Biological Systems with Differential Equations (5 credits) (not on offer in 2018/19)
AM6007 Object Oriented Programming with Numerical Examples (10 credits)
AM6008 Developing Windowed Applications and Web-based Development for Scientific Applications (5 credits) (not on offer in 2018/19)
AM6009 3D Computer Graphics and Animation for Scientific Visualisation (5 credits) (not on offer in 2018/19)
AM6010 Topics in Applied Mathematical Modelling (5 credits) (not on offer in 2018/19)
AM6011 Advanced Mathematical Models and Parallel Computing (5 credits) (not on offer in 2018/19)
AM6012 Dissertation in Mathematical Modelling and Scientific Computing (30 credits)

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2019/2020 Book and for each module in the Book of Modules, 2019/2020.

Part-time option
Part-time students take between 25 and 35 credits of the 60 taught credits in each academic year (AM6001 to AM6011) and undertake the 30 credit project (AM6012) in the second academic year provided they satisfy the pass and progression requirements set out in Marks and Standards. The modules to be taken by individual part-time students in each of their two academic years are specified in advance by the course director in consultation with the student.

Online option
Students wishing to take the programme online follow either the full-time or part-time programme as outlined above. The modules to be taken by individual online students are specified in advance by the course director in consultation with the student.

Learning Outcomes for MSc (Mathematical Modelling and Scientific Computing) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Apply their knowledge and understanding of the basic concepts, theories, principles and practical methods of mathematical modelling and scientific computing to analyse and solve theoretical and practical problems;
• Give clear and organized written and verbal explanations of ideas in the areas of mathematical modelling and scientific computing;
• Demonstrate mastery of the concepts and examples in several areas of mathematical modelling and scientific computing;
• Extend the given course material to solve original problems;
• Contribute effectively as members of project teams dealing with mathematical models and their computer implementation, including the delivery of oral presentations and written reports.

*This programme is replacing the (Mathematical Modelling and Scientific Computing) for students entering the programme from 2018/19 onwards. Students entering from 2018/19 onwards follow the curriculum detailed below. Students who entered prior to 2018/19 follow the curriculum detailed here

The MSc in Mathematical Modelling and Self-Learning Systems is a full-time, blended learning programme running for 12 months from the date of first registration for the programme.

Entry Requirements
Candidates must have obtained at least a Second Class Honours, Grade 2 (2H2) degree or equivalent in a numerate discipline (i.e. commensurate with science or engineering programmes). Candidates are expected to have taken courses in mathematics, applied mathematics or statistics at university level, and be familiar with calculus, vectors, matrices and elementary statistics. They are expected to have sufficient background in university-level mathematics as assessed by the course coordinator.

Candidates from Grandes Écoles Colleges are also eligible to apply if they are studying a cognate discipline in an ENSEA or EFREI Graduate School and are eligible to enter the final year (M2) of their programme. All candidates must ultimately be approved by the director of the MSc (Mathematical Modelling and Self-Learning Systems) programme.

In the case of competition for places selection will be made on the basis of primary degree results and/or interview.

All candidates must ultimately be approved by the director of the MSc (Mathematical Modelling and Self-Learning Systems) programme.

Programme Requirements

Students take 90 credits as follows:

Part I
AM6004 Numerical Methods and Applications (5 credits)
AM6005 Nonlinear Dynamics (5 credits)
AM6007 Scientific Computing with Numerical Examples (10 credits)
AM6013 Statistical, Dynamical and Computational Modelling (10 credits)
AM6015 Computational Techniques with Networks (5 credits)
AM6016 Dynamic Machine Learning with Applications (5 credits)
AM6017 Complex and Neural Networks (5 credits)
AM6020 Open Source Infrastructure for Mathematical Modelling and Big Data Applications (5 credits)
ST4060 Statistical Methods for Machine Learning I (5 credits)**
ST4061 Statistical Methods for Machine Learning II (5 credits)**

**Students who have taken ST4060 or ST4061 in a previous degree must select alternative modules (subject to availability and timetabling) from list A and list B of fourth year of the BSc (Mathematical Sciences) in consultation with the Programme Coordinator.

Part II
AM6018 Dissertation in Mathematical Modelling and Self-Learning Systems (30 credits)

Module Semester Information may be found here. Module Descriptions may be found here.

Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards 2019/2020 Book and for each module in the Book of Modules, 2019/2020.

Postgraduate Diploma in Mathematical Modelling and Machine Learning
Students who pass Part I but who fail to achieve a minimum aggregate of at least 50% across all modules in Part I at the first attempt, or who choose not to progress to Part II and exit the programme, will be conferred with the Postgraduate Diploma in Mathematical Modelling and Machine Learning.

Learning Outcomes for MSc (Mathematical Modelling and Self-Learning Systems) (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Apply the basic concepts, theories, principles and practical methods of mathematical modelling and self-learning systems to analyse and solve theoretical and practical problems;
• Give clear and organized written and verbal explanations of ideas in the areas of mathematical modelling and self-learning systems;
• Critically discuss and evaluate the concepts and examples in several areas of mathematical modelling and self-learning systems;
• Extend the given course material to solve original problems and develop associated computer codes;
• Contribute effectively as members of project teams dealing with mathematical models and their computer implementation, including the delivery of oral presentations and written reports.

Learning Outcomes for Postgraduate Diploma in Mathematical Modelling and Machine Learning (NFQ Level 9, Major Award)
On successful completion of this programme, students should be able to:

• Apply the basic concepts, theories, principles and practical methods of mathematical modelling and self-learning systems to analyse and solve theoretical and practical problems;
• Give clear and organized written and verbal explanations of ideas in the areas of mathematical modelling and self-learning systems;
• Critically discuss and evaluate the concepts and examples in several areas of mathematical modelling and self-learning systems;
• Use the given course materials and computer code to solve problems;
• Contribute effectively as members of project teams dealing with mathematical models and their computer implementation, including the delivery of oral presentations and written reports.