Datacamp – Applied Finance in Python 2024-8

Datacamp – Applied Finance in Python 2024-8 Downloadly IRSpace

Datacamp – Applied Finance in Python 2024-8
Datacamp – Applied Finance in Python 2024-8

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.

What you’ll learn

  • Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
  • Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.
  • Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
  • Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

Specificatoin of Applied Finance in Python

  • Publisher : Datacamp
  • Teacher : Dakota Wixom
  • Language : English
  • Level : All Levels
  • Number of Course : 4
  • Duration: 16h

Content of Applied Finance in Python

Applied Finance in Python

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Applied Finance in Python

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Subtitle : English

Quality: 720p

Download Links

Credit Risk Modeling in Python

Download – 71 MB

GARCH Models in Python

Download – 74 MB

Introduction to Portfolio Risk Management in Python

Download – 92 MB

Quantitative Risk Management in Python

Download – 103 MB

File size

341 MB