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Applied Finance in Python

Uppdaterad 2026-03
Enhance your Python financial skills. Learn how to evaluate portfolios, calculate credit risk, and create GARCH models to forecast volatility.
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PythonApplied Finance16 timmar14,009

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Applied Finance in Python

Enhance your Python financial skills and learn how to manipulate data and make better data-driven decisions.You’ll begin this track by discovering how to evaluate portfolios, mitigate risk exposure, and use the Monte Carlo simulation to model probability. Next, you’ll learn how to rebalance a portfolio using neural networks. Through interactive coding exercises, you’ll use powerful libraries, including SciPy, statsmodels, scikit-learn, TensorFlow, Keras, and XGBoost, to examine and manage risk. You’ll then apply what you’ve learned to answer questions commonly faced by financial firms, such as whether or not to approve a loan or a credit card request, using machine learning and financial techniques. Along the way, you’ll also create GARCH models and get hands-on with real datasets that feature Microsoft stocks, historical foreign exchange rates, and cryptocurrency data. Start this track to advance your Python financial skills.

Förkunskapskrav

Det finns inga förkunskapskrav för detta spår
  • Course

    1

    Introduction to Portfolio Risk Management in Python

    Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

  • Course

    Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

  • Course

    Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

Applied Finance in Python
4 courses
Spår
klart

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Gå med över 19 miljoner elever och börja Applied Finance in Python idag!

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Genom att fortsätta accepterar du våra Användarvillkor, vår Integritetspolicy och att dina uppgifter lagras i USA.