R

Enhance your Power BI reports and analysis with R's visualization, text analysis and statistical modeling capabilities.

Dive deeper into using ChatGPT for data science tasks. Explore techniques for data preprocessing, feature engineering, model training, and deploying ChatGPT models for specific data analysis and prediction tasks.

Amplify your Power BI visualizations with R's comprehensive statistical analysis and graphics language

The second part of the preparation course for the Microsoft's DP-500 Exam Certification

Learn valid inference techniques for two-sample and two-variable data questions.

A practical guide to recognizing, understanding, and managing uncertainty in data 

The first of the two-part preparation course for the Microsoft's DP-500 Exam Certification

This path is designed to build the broad range of expert-level knowledge necessary to confidently pass the PL-300 Data Analyst certification exam (replacement for DA-100).

This path is designed to help you harness the full power of Power BI in combination with R and Python. You will learn how to conduct advanced statistical analyses, text and sentiment analysis, leverage machine learning techniques, and other key methods commonly used to gain insight into complex business questions.

R is a programming language and free software environment for statistical computing and graphics. It is widely used among statisticians and data miners for developing statistical software and data analysis.  R provides a wide variety of statistical and graphical techniques including linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, clustering, and more.

Introduction to Statistics for Data Analysts Review Questio

Explore possibilities for supercharging Power BI with R’s modeling and visualization capabilities.

This session will cover which Python and R packages and examples can facilitate functionalities found in Power BI

Creating basic tables and figures with R to check assumptions and communicate findings

Create basic pipelines for data cleaning, visualization and modeling in R

WORKOUTS is an innovative approach that combines hands-on exercises, practical applications, and collaborative learning to help data practitioners master data skills effectively.