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Quantitative finance is the methodology of applying disciplines from mathematics, statistics, scientific computing, and finance with computer programming to financial trading and investment work. Quantitative finance allows you to build financial models that can be used for pricing a range of financial assets, including financial derivative products. You can also automate trading processes using quantitative finance. Some models even allow for solo trading without a great deal of oversight. This is achieved by setting up risk inputs, and the computer program makes trades within the limits of the risk inputs.‎

It's valuable to learn quantitative finance as you can become knowledgeable about how to analyze investment decisions while balancing asset allocation with risk management. Having this basic understanding can help you with finances in your professional and personal life. Learning quantitative finance could put you into the major leagues of financial risk management. This knowledge may help you understand the price of securities and financial derivatives. Using concepts of quantitative analysis and quantitative finance can help investors and investment clients develop and make wise decisions about their investment strategies.‎

Typical careers that use quantitative finance include financial engineer, quantitative financial analyst, derivatives trader, asset manager, fund manager, and financial risk manager. Learning about quantitative finance might help you find work in commercial banks, investment banks, securities industry companies, wealth management firms, and hedge funds. Experts in quantitative finance are also highly sought by accountancy firms, insurance companies, management consulting firms, and financial software companies.‎

When you take online courses about quantitative finance on Coursera, you could learn the fundamentals of statistical financial models, including insights into asset pricing, credit risk modeling, investment theory, algorithmic trading, and financial institutions and markets. Some of the online courses are heavily geared to learning derivatives pricing, while others spend more time and substance on machine learning, data science, and object-oriented programming.‎