Data, AI, and Cloud Courses

Learn to streamline your machine learning workflows with tidymodels.

Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.

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

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

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

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

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

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