Course co-ordinator(s): Dr Seva Shneer (Edinburgh).
Aims:
To carry out a sustained and intensive piece of independent work on topics involving actuarial management and data science and to write a substantial report or reports that communicates the results of this work to others interested in actuarial mathematics and practice.
Detailed Information
Pre-requisites: none.
Location: Edinburgh.
Semester: 3.
Syllabus:
Students can carry out projects on a variety of topics in Actuarial Management and Data Science. The project or projects should take the student beyond the courses they have already been taught and examined in on the MSc.
Learning Outcomes: Subject Mastery
On completion of this course students should:
- be able to access, use and demonstrate an understanding of the appropriate research literature
- have broadened their knowledge of actuarial management and data science
- have improved their skills in reading research papers in actuarial management and data science
- be able to demonstrate detailed and critical understanding of a selected recent development in actuarial management or data science
- be able to demonstrate expertise in applying a variety of actuarial techniques in the context of the problems contained within the project(s).
Learning Outcomes: Personal Abilities
• Demonstrate the ability to learn independently.
• Manage time, work to deadlines and prioritise workloads.
• Conduct a sustained and intensive piece of independent work on topics in actuarial management and data science over a period of weeks.
• Discuss the detail of their project(s) with their supervisor(s).
• Perform numerical calculations using a suitable computer language or package as required for the project(s).
• Write well-structured and coherent reports on their work in a way which can be easily be understood by their examiners,
• Work as part of a team, if required, to analyse issues arising in the project.
Assessment Methods: Due to covid, assessment methods for Academic Year 2021-22 may vary from those noted on the official course descriptor. Please see the Computer Science Course Weightings and the Maths Course Weightings for 2020-21 Semester 1 assessment methods.
SCQF Level: 11.
Other Information
Help: If you have any problems or questions regarding the course, you are encouraged to contact the lecturer
Canvas: further information and course materials are available on Canvas