A short, crash course to understand and deploy your first smart contract in a blockchain

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Learn how to tune your model's hyperparameters to get the best predictive results.

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

Learn how to plan, implement, and interpret different kinds of hypothesis tests in Python.

Learn how to plan, implement, and interpret different kinds of hypothesis tests in Python.

Learn how to use hypothesis testing to evaluate the associations between different variables.

Learn how to use hypothesis testing to evaluate the associations between different variables.

Learn how to set up experiments to both address research questions and weigh the trade off between resources and errors.

Learn how to evaluate statistical significance and the best thresholds to use.

Learn how to evaluate statistical significance and the best thresholds to use.