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Applied Finance in Python

Updated 03/2026
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 hr14,236

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Track Description

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.

Prerequisites

There are no prerequisites for this track

  • 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 Courses
Track
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FAQs

Is this Track suitable for beginners?

Yes, the Applied Finance track is suitable for beginners. It covers the basics of portfolio risk management, credit risk modeling, quantitative risk management, and GARCH modeling in Python.

What is the programming language of this Track?

This track uses Python as the programming language.

Which jobs will benefit from this Track?

The Applied Finance track will give financial professionals the skills needed to analyze data and answer common questions faced by the industry. Some job titles that may benefit from this track include financial analysts, quantitative analysts, risk managers, and credit analysts.

How will this Track prepare me for my career?

The Applied Finance skills track offers practical Python knowledge and skills applicable to the financial industry. It allows users to learn through interactive coding exercises, understand risks, and make data-driven decisions. With this track, you will gain the confidence to use powerful libraries such as SciPy, statsmodels, scikit-learn, TensorFlow, Keras, and XGBoost.

How long does it take to complete this Track?

It is estimated that the Applied Finance track will take approximately 16 hours to complete.

What's the difference between a skills track and a career track?

DataCamp offers two types of learning experiences: skills tracks and career tracks. A skills track allows users to acquire new skills in a certain area (e.g., R, Python, SQL, etc.), while a career track provides users with an in-depth look into a certain field (e.g., Data Science, Data Analysis, Data Visualization, etc.). Each skills track and career track has multiple courses and interactive coding exercises.

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