Data, AI, and Cloud Courses

Learn to set up a secure, efficient book recommendation app in Azure in this hands-on case study.

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.

Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.

Learn how to write effective tests in Java using JUnit and Mockito to build robust, reliable applications with confidence.

Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.

Automate data manipulation with KNIME, mastering merging, aggregation, database workflows, and advanced file handling.

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

Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.

Learn the bag of words technique for text mining with R.

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

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.

Use survival analysis to work with time-to-event data and predict survival time.

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

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

Learn to use the Census API to work with demographic and socioeconomic data.

Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.

In this course youll learn how to perform inference using linear models.

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

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

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Practice Tableau with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

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

Learn how to pull character strings apart, put them back together and use the stringr package.

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

Learn to build AI applications using Snowflake Cortexs built-in LLM functions for text analysis, generation, and multi-step workflows.

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