Learn about ARIMA models in Python and become an expert in time series analysis.

In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.

Develop the skills you need to go from raw data to awesome insights as quickly and accurately as possible.

Discover how to make better business decisions by applying practical data frameworks—no coding required.

This course focuses on feature engineering and machine learning for time series data.

Learn about string manipulation and become a master at using regular expressions.

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

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.