Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Learn how to analyze a SQL table and report insights to management.

Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

In this interactive Power BI course, you’ll learn how to use Power Query Editor to transform and shape your data to be ready for analysis.

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in R.

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Data Analysis Expressions (DAX) allow you to take your Power BI skills to the next level by writing custom functions.