Computing and Actuarial Science
Overview
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Duration
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Program Description
Computing and Actuarial Science blends mathematics, statistics and computing to measure and manage risk and to analyse scientific data. Students study calculus, probability and statistics, programming, data analysis, financial mathematics and research methods. You will learn to build predictive models, run simulations, and use software tools to solve real problems in insurance, finance, environment and research. Graduates can become actuaries, data analysts, risk modelers, research scientists, quality control analysts, or continue to professional actuarial exams and computing careers. This program suits SHS students who enjoy numbers, logical thinking and using computers to answer real world questions.
Aims & Objectives
Develop strong foundations in calculus, probability and statistics, measured by successful completion of core modules and assignments.
Master programming for data analysis, demonstrated by building and presenting data projects using Python or R.
Understand actuarial models and financial mathematics, shown by solving real life risk and insurance problems.
Create and document reproducible analyses, assessed through lab reports and a final project using scientific methods.
Why Choose This Program?
High demand for analytical skills
Employers in insurance, finance, data science and research seek graduates who combine maths and computing, increasing job prospects in Ghana and internationally.
Clear professional pathway
You can progress to actuarial professional exams while working, or move into data science and research with recognized certification and degree options.
Practical, real world learning
The program emphasises hands on projects, case studies and internship opportunities with insurers, banks and research centres, building workplace experience.
Transferable technical skills
Skills in programming, statistics and modelling apply across industries, from environmental science to quality control and fintech.
Skills & Tools
Skills You'll Develop
Formulate and fit models for risk and uncertainty, including survival models, regression and time series, used in pricing and forecasting.
Use libraries such as pandas, NumPy, and tidyverse to clean, visualise and analyse datasets for decision making.
Apply present value, compound interest, annuities and basic loss modelling to evaluate insurance products and financial scenarios.
Build reproducible models in Microsoft Excel, use VBA for automation, and prepare reports for stakeholders.
Tools & Resources
R and RStudio
Python with Anaconda distribution
Microsoft Excel with VBA
Challenges & Tips
Challenges
High level mathematics and probability
Rigorous actuarial exam preparation
Tips & Advice
Build foundations early, attend tutorials, practise past questions and use online courses to strengthen weak areas.
Start exam study early, follow a study schedule, use past papers and join study groups to stay on track.
Video Guide
Frequently Asked Questions
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