Why study Modern Applications of Engineering Mathematics?

In the current climate employers are looking for graduates with a broader range of skills, able to meet the latest needs of an industry where technology is changing in unpredictable ways. Due to their inherently strong mathematical background, engineers are ideally placed to thrive in such a rapidly evolving environment where the focus shifts more and more towards the efficient analysis of a large amount of data in order to forecast future behavior (of processes, markets, prices among others). It is predicted that big data will play a major role in shaping the design of materials, products, systems, innovations from heavy industry to energy, from environmental engineering to genomics and healthcare.

The aim of this Minor is to provide students with a broad set of tools that will strengthen and diversify their engineering skills and enhance their employability prospects across multiple business sectors. Invited lectures from guest speakers will complement the course by providing their real-world perspective and views on how mathematical tools are used in different businesses.

What will you learn?

On completion of this Minor, you will be able to:

  • Understand the basic concepts underpinning financial engineering
  • Perform calculations using Quantitative Finance techniques
  • Handle large datasets (Big Data) from a variety of applications
  • Identify appropriate dimensionality reduction techniques to apply depending on the nature of the data being analysed
  • Understand the concepts and relevance of stochastic calculus
  • Be able to solve high-dimensionality problems using appropriate Monte Carlo techniques
  • Understand the concept of uncertainty in the model output, identify and use appropriate sensitivity analysis methods to study the allocation of uncertainty

Information for Current Students

For current module breakdown and syllabus, please have a look at the Minor page on the IEP Central Moodle (current students ONLY, login required).

Exclusions

Students who have NOT successfully completed ENGS103P or MATH6301 (for CS students) and an appropriate Intermediate level (Year 2) Mathematics or Statistics module.

Lead Academics

Dr Alexandros Kiparissides and Dr Vasos Pavlika
Dept Biochemical Engineering
Email: ku.ca1568636790.lcu@1568636790sedis1568636790sirap1568636790ik.xe1568636790la1568636790 and/or: ku.ca1568636790.lcu@1568636790akilv1568636790ap.v1568636790

Choose your IEP Minor

Please select your preferred Minor via IEP Minors Moodle Poll