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Applied Finance in Python

更新时间 2026年3月
Enhance your Python financial skills. Learn how to evaluate portfolios, calculate credit risk, and create GARCH models to forecast volatility.
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学习路径描述

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.

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  • 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

    3

    Credit Risk Modeling in Python

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

  • Course

    4

    GARCH Models in Python

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

Applied Finance in Python
4 课程
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