Computer Science with Economics
Overview
Projected Job Growth
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Program Description
Computer Science with Economics blends computing and economic thinking to prepare you to design and manage technological systems that solve real-world problems. You will study programming, data analysis, algorithms, database systems, microeconomics, macroeconomics, and econometrics, plus project work and systems design. The course develops skills in software development, data-driven decision making, and understanding how technology impacts markets and businesses. Graduates can work as software engineers, data analysts, IT support specialists, fintech developers, policy analysts, or pursue postgraduate study in computing, economics, or engineering fields. This program is practical and future-focused, ideal if you enjoy mathematics, logical problem solving, and ideas that change how society uses technology.
Aims and Objectives
Develop practical programming skills in languages such as Python and Java, measured by completing project-based assignments and code repositories.
Master core economic concepts and econometric methods, demonstrated through data analyses and written reports.
Understand design and deployment of software systems and databases, verified by building and documenting functioning applications.
Create data-driven solutions for real problems, evidenced by capstone projects that combine modelling and software implementation.
Why Choose This Program?
Strong job market fit
Combines high-demand computing skills with economic reasoning, opening roles in tech, finance, and government where both skills are needed.
Practical, project-based learning
Coursework emphasizes hands-on projects, internships, and real data work, helping you build a portfolio employers value.
Pathway to fintech and policy roles
Equips you for emerging fields like mobile money, digital payments, and tech policy where economics and programming meet.
Accessible tools and open resources
Many course tools are open-source and low-cost, so you can practice and build skills outside campus without heavy expenses.
Skills Students Will Acquire
Writing, testing, and maintaining code in languages like Python, Java, or JavaScript to build applications and automate tasks.
Using tools such as R or Python libraries to clean data, run statistical models, and interpret results for economic and business questions.
Designing and querying relational databases with SQL, and understanding how backend systems support applications and services.
Using Git for collaboration, and basic deployment techniques or cloud services to publish and maintain applications.
Tools and Resources Students Will Use
Python and libraries (Pandas, NumPy, scikit-learn)
R and RStudio
VS Code or other code editor
MySQL or PostgreSQL
Challenges Students Face and Helpful Tips
Challenges
Steep mathematical and statistical content
Balancing programming and economics coursework
Tips & Advice
Start with core maths revision, use online tutorials, and attend study groups to practise concepts regularly.
Plan a weekly schedule, tackle coding exercises incrementally, and link assignments across subjects where possible.
Video Guide
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