Learn how to build an amortization dashboard in spreadsheets with financial and conditional formulas.

Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.

In this course you'll learn to use and present logistic regression models for making predictions.

Learn the language of data, study types, sampling strategies, and experimental design.

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

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

Learn to perform linear and logistic regression with multiple explanatory variables.

Using Python and NumPy, learn the most fundamental financial concepts.

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

In this course, you'll learn how to implement more advanced Bayesian models using RJAGS.

Learn how to access financial data from local files as well as from internet sources.

Prepare for your next coding interviews in Python.

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.