Data, AI, and Cloud Courses

In this course youll learn how to leverage statistical techniques for working with categorical data.

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

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

Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.

Learn to easily summarize and manipulate lists using the purrr package.

Learn to process sensitive information with privacy-preserving techniques.

Learn to analyze, plot, and model multivariate data.

In this course youll learn how to use data science for several common marketing tasks.

Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.

Streamline your AI projects by building modular models and mastering advanced optimization with PyTorch Lightning!

Explore HR data analysis in Tableau with this case study.

Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.

In this course youll learn how to apply machine learning in the HR domain.

Learn strategies for answering probability questions in R by solving a variety of probability puzzles.

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

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

Learn how to prepare and organize your data for predictive analytics.

This course will show you how to combine and merge datasets with data.table.

Learn how to design, automate, and monitor scalable forecasting pipelines in Python.

Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.

Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.