Data, AI, and Cloud Courses

Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.

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

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

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

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

Learn to use the Bioconductor package limma for differential gene expression analysis.

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

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

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

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

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

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

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

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

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

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

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

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

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

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

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

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

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

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

Learn to process sensitive information with privacy-preserving techniques.

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

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

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 prepare and organize your data for predictive analytics.