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DRPS : Course Catalogue : Business School : Common Courses (Management School)

Postgraduate Course: Programming for Risk Analytics (CMSE11590)

Course Outline
SchoolBusiness School CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits20 ECTS Credits10
SummaryThe aim of the course is to provide the students with the knowledge and skills to work with datasets using programming languages extensively used in the banking industry. The practical use of coding to support advanced risk modelling and data analysis is of key interest in the banking and financial industry.
Course description The course develops computational skills essential to make decisions when working in a bank. The course provides the basic knowledge needed to perform risk analytics: to input and manipulate data, combining and modifying datasets and running statistical procedures, and finally delivering actionable visualisations.

Outline Content

- Introduction to programming
- Input and output format management
- Variable creation and transformation
- Merging datasets
- Help and General syntax
- Loops
- Conditional execution
- Data Wrangling
- Data analysis
- Data Visualisations

Student Learning Experience

During the course, the students will be experiencing a real contact with programming tools such as SAS, R and/or Python. The program is introduced using a mixture of demonstration, self-learning and practice. Each lecture will consist of a mini project of increasing difficulty.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Course Delivery Information
Academic year 2023/24, Not available to visiting students (SS1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 20, Seminar/Tutorial Hours 10, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 166 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 100% coursework (individual) - assesses all course Learning Outcomes
Feedback Formative: Feedback will be provided throughout the course.

Summative: Feedback will be provided on the assessment within agreed deadlines.

No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Translate risk analysis problems into mathematical formulation
  2. Write small code snippets to tackle risk analytics problems
  3. Produce insightful visual explanations
  4. Draft critical reports that leverage data-driven decision-making
Learning Resources
Additional Information
Graduate Attributes and Skills Communication, ICT, and Numeracy Skills

After completing this course, students should be able to:

Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts

Knowledge and Understanding

After completing this course, students should be able to:

Demonstrate a thorough knowledge and understanding of contemporary organisational disciplines; comprehend the role of business within the contemporary world; and critically evaluate and synthesise primary and secondary research and sources of evidence in order to make, and present, well informed and transparent organisation-related decisions, which have a positive global impact.

Identify, define and analyse theoretical and applied business and management problems, and develop approaches, informed by an understanding of appropriate quantitative and/or qualitative techniques, to explore and solve them responsibly.
KeywordsNot entered
Course organiserDr Ben Moews
Tel: (01316) 508074
Course secretaryMiss Aoife McDonald
Tel: (0131 6)50 8074
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