Overview
Status: Active
National Framework Of Qualifications (NFQ) Level: 8
NFQ Award Class: Major Award
Duration Full Time: 4 Academic Year(s)
Total Credits: 240
Delivery Method: In-Person
Connected Curriculum: - Employability
- Global Reach
- Inter-and Transdisciplinary
- Research Based Teaching
- Sustainability
Sustainable Development Goals (SDGs): - Quality Education
- Decent Work and Economic Growth
- Industry, Innovation, and Infrastructure
- Climate Action
Graduate Attributes: - Creator, evaluator and communicator of knowledge
- Digitally Fluent
- Effective global citizen
- Independent and creative thinker
- Socially Responsible
Work-Integrated Learning (Including Placement): No
Regulations and Programme Requirements
Students enter the Single Honours BSc (Hons) Mathematical Sciences through CK407 (Mathematical Sciences) Area of Study.
Notes:
- The final set of electives and 'project-related' modules offered is subject to the availability of adequate staff resources and therefore may need to be a subset of those indicated.
Eligibility for Entry to Second Year Programmes
Students from the Mathematical Sciences Area of Study (CK407) who pass First Science may opt to enter the Single Honours Mathematical Sciences.
BSc Ordinary Degree - NFQ Level 7, Major Award
Students who pass Third Year may choose not to proceed to Fourth Year and may opt instead to be conferred with a BSc Ordinary Degree.
Programme Requirements
For information about modules, module choice, options and credit weightings, please go to Programme Requirements.
Programme Requirements
Module List
| Code |
Title |
Credits |
| |
| AM1052 | Introduction to Mechanics | 5 |
| AM1053 | Introduction to Mathematical Modelling | 5 |
| AM1054 | Mathematical Software | 5 |
| MA1057 | Introduction to Abstract Algebra | 5 |
| MA1058 | Introduction to Linear Algebra | 5 |
| MA1059 | Calculus | 5 |
| MA1060 | Introduction to Analysis | 5 |
| ST1051 | Introduction to Probability and Statistics | 5 |
| 20 |
| Investment in Capital Assets | |
| Introduction to Valuation and Risk | |
| Habitats and Ecosystems | |
| Introduction to Chemistry for Physicists and Mathematicians | |
| Programming in C | |
| Network and Internet Technologies | |
| Geometry | |
| Principles of Market Analysis | |
| Introductory Physics I | |
| Introductory Physics II | |
| Statistical Programming in R | |
| |
| AM2052 | Mathematical Modelling | 5 |
| AM2060 | Object Oriented Programming with Applications | 5 |
| AM2061 | Computer Modelling and Numerical Techniques | 5 |
| AM2071 | Transform and Variational Methods | 5 |
| MA2051 | Mathematical Analysis I | 5 |
| MA2054 | Ordinary Differential Equations | 5 |
| MA2055 | Linear Algebra | 5 |
| MA2071 | Multivariable Calculus | 5 |
| ST2053 | Introduction to Regression Analysis | 5 |
| MA2072 | Complex Analysis | 5 |
| ST2054 | Probability and Mathematical Statistics | 10 |
| |
| MA3064 | Measure Theory and Integration | 5 |
| AM3051 | Vector and Tensor Methods | 5 |
| AM3063 | Partial Differential Equations with Applications I | 5 |
| AM3064 | Topics in Applied Mathematics | 5 |
| MA3052 | Ring and Field Theory | 5 |
| ST3061 | Statistical Theory of Estimation | 5 |
| ST3055 | Generalised Linear Models | 5 |
| 25 |
| Introduction to Fluid Mechanics and Wave Theories (5) | |
| Dynamical Systems and Bifurcation Theory (5) | |
| Metric Spaces and Topology (5) | |
| Introduction to Modern Algebra (5) | |
| Introduction to Differential Geometry (5) | |
| Stochastic Modelling I (5) | |
| Survival Analysis (5) | |
| Statistical Methods for Machine Learning I (5) | |
| 1 | |
| MS4090 | Mathematical Sciences Project | 10 |
| |
| Introduction to Fluid Mechanics and Wave Theories (5) | |
| Dynamical Systems and Bifurcation Theory (5) | |
| Metric Spaces and Topology (5) | |
| Stochastic Modelling I (5) | |
| Survival Analysis (5) | |
| Statistical Methods for Machine Learning I (5) | |
| |
| Partial Differential Equations with Applications II (5) | |
| Perturbation and Asymptotic Methods (5) | |
| Network Science with Applications (5) | |
| Machine Learning with Applications (5) | |
| Functional Analysis (5) | |
| Measure Theory and Martingales (5) | |
| Topics in Modern Algebra (5) | |
| Topics in Differential Geometry (5) | |
| Stochastic Analysis (5) | |
| Statistical Methods for Machine Learning II (5) | |
| Time Series (5) | |
| Gravitation and Cosmology (5) | |
| Total Credits | 240 |
Examinations
Full details and regulations governing Examinations for each programme will be contained in the Marks and Standards Book and for each module in the Book of Modules.
Programme Learning Outcomes
Programme Learning Outcomes for BSc in Mathematical Sciences (NFQ Level 8, 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 the mathematical sciences to analyse and solve theoretical and practical problems;
- Give clear and organized written and verbal explanations of mathematical and statistical ideas;
- Demonstrate mastery of the core concepts of several areas of pure mathematics, applied mathematics and statistics;
- Extend course material to solve original problems;
- Recognize the interdependency of different areas of the mathematical sciences;
- Contribute effectively as members of project teams dealing with mathematical/statistical topics, including the delivery of oral presentations and written reports.
