Course Catalogue

Finance Programming in Python and Databases ACCFIN5277

  • Academic Session: 2026-27
  • School: Adam Smith Business School
  • Credits: 15
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 1
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

The modern financial world is driven by evidence-based financial monitoring and decision-making. The role of data in informing financial insights is expanding, requiring a more advanced understanding of data, along with the ability to process and communicate it effectively. Computational methods sit in an important crossroad of business intelligence and scientific methods and is considered one of the most relevant skills for various stages of careers in finance.

Timetable

6 x 2 hour practical classes and workshops (delivered via a mix of campus and live sessions)

10 hours of programming tutorials

Requirements of Entry

Students must be registered on one of the associated programmes listed in this course specification.

Excluded Courses

None

Co-requisites

None

Assessment

1. Portfolio, Individual, 1,000 words and objective questions, 100%, ILOs 1-4.

Course Aims

The aims of this course are:

■ Provide software-based data analysis frameworks to finance applications.

■ Assess statistical model insights for academic and professional contexts.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

1. Create software solutions for financial data acquisition and processing.

2. Create financial models in software to apply to investment, risk, and valuation analysis.

3. Evaluate the accuracy and suitability of complex financial datasets using advanced software tools.

4. Create data visualisation outputs to communicate financial insights effectively.

Minimum Requirement for Award of Credits

No exceptions