Data, AI, and Cloud Courses

Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training

Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.

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

GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.

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.

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

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

Learn to analyze, plot, and model multivariate data.

Learn to process sensitive information with privacy-preserving techniques.

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.

Explore HR data analysis in Tableau with this case study.

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

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

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

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

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

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

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

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

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

Enhance your Tableau skills with this case study on inventory analysis. Analyze a dataset, create calculated fields, and create visualizations.

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

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

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

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

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.