Compare Our Computational Finance Programs
Compare Our Computational Finance Programs

Excited about a career in modern finance?

Whether you want to build on your experience, or get your career started, UW Professional & Continuing Education offers a variety of programs to help you level up your skills in computational finance. Get the knowledge you need to work in this field that brings together the power of computing and statistical analysis with the principles of finance and investment management.

Compare our programs in computational finance and find the right one for you. Take one or more — you can apply credits you earn in the Certificate in Computational Finance or the Certificate in Financial Data Analytics to the Master of Science in Computational Finance & Risk Management.

Certificate in Computational Finance

Combine computing power and statistical analysis to build your career in finance. Learn classic methods, modern theories and programming skills you’ll use to optimize portfolios, manage assets and build models of risk and return.

Key Skills:

  • Mathematics of fixed income, interest rates and terms structure
  • Introduction to forwards, futures, hedging and options pricing
  • The R statistical programming language, used for financial modeling and analysis

Duration: 9 months

Good for: Experienced computational finance professionals seeking a higher level of technical and financial mastery, or students in related fields seeking graduate-level study

Prep for Roles Like: Quantitative trader, investment manager, portfolio analyst, power analyst

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Certificate in Financial Data Analytics

Use data science to make financial decisions and calculate risk. You’ll learn about powerful financial data analytics, modeling, programming languages and statistical techniques.

Key Skills:

  • Analytical tools and numerical algorithms of machine learning
  • How to apply statistical techniques when analyzing financial data
  • How to leverage popular programming languages, such as R, for financial data modeling and analysis

Duration: 10 months

Good for: Finance professionals with a background in basic statistics, probability and programming who are seeking graduate-level coursework in machine learning and financial data science

Prep for Roles Like: Data analyst, quantitative model developer, quantitative researcher

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Master of Science in Computational Finance & Risk Management

Learn fundamental quantitative finance theory and computational methods. Build a next-generation skill set over the course of a 42-credit program, including financial data science, machine learning, portfolio optimization, quantitative risk management and R programming.

Key Skills:

  • Mathematical and statistical foundations of quantitative finance
  • Open source R-programming and cutting-edge R finance packages
  • Methods for risk management, trading, price modeling and data analytics

Duration: 18 months–3 years

Good for: Working professionals with demonstrated skills in calculus, probability, statistics and programming; students who are seeking intensive graduate-level study in computational finance

Prep for Roles Like: Quantitative risk management analyst, global data analyst, data scientist, business intelligence analyst, credit risk analyst

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