Data, AI, and Cloud Courses

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

Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.

Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.

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

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Learn to solve increasingly complex problems using simulations to generate and analyze data.

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

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

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

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.

Are you curious about the inner workings of the models that are behind products like Google Translate?

Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.

Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.

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

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

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

Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Learn to process sensitive information with privacy-preserving techniques.

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

Discover how to talk to your data using text-to-query AI agents with MongoDB and LangGraph.

Learn how to visualize time series in R, then practice with a stock-picking case study.

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.

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

In this course youll learn techniques for performing statistical inference on numerical data.

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

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

You will use Net Revenue Management techniques in Google Sheets for a Fast Moving Consumer Goods company.