Overview

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Discover the power of data visualization and analysis in this beginner-friendly course. Learn how to turn raw data into meaningful insights using R's visualization tools and Microsoft's development environment. Through hands-on practice, you'll learn to create engaging visualizations and understand basic statistical patterns, all while using AI assistance to enhance your learning. Learn to explore datasets, identify patterns, and communicate insights using ggplot2, Plotly, and R Markdown. Practice univariate, bivariate, and multivariate analysis. Discover the power of data visualization and analysis in this beginner-friendly course. Learn how to turn raw data into meaningful insights using R's visualization tools and Microsoft's development environment. Through hands-on practice, you'll learn to create engaging visualizations and understand basic statistical patterns, all while using AI assistance to enhance your learning.

Syllabus

Introduction to Exploratory Data Analysis (EDA)

Welcome to your first step in data exploration! In this module, you'll learn what Exploratory Data Analysis, EDA, is and why it matters. You'll get hands-on experience with essential data preprocessing techniques using R's tidyverse packages and learn how to clean and prepare data for analysis. Through practical, real-world datasets, you'll develop the fundamental skills needed to begin any data analysis project.

Univariate and Bivariate Analysis

In this module, you'll learn how to explore single variables and spot relationships between them. Using real healthcare data and ggplot2, you’ll practice creating clear, meaningful visualizations. You'll also get comfortable with concepts like distribution and correlation, tools that help you find and explain key patterns in your data.

Multivariate Analysis and Dimensionality Reduction

In this module, you’ll explore relationships across multiple variables and learn how to spot patterns in more complex, high-dimensional data. We’ll use tools like correlation heatmaps, scatter plot matrices, and PCA to help make sense of it all, especially when working with large datasets.

Advanced Visualization and Reporting

In this module, you’ll learn how to turn your analysis into something people can actually see and understand. We’ll show you how to create interactive visuals with plotly, build polished reports using R Markdown, and follow simple but effective data storytelling tips. By the end, you’ll know how to communicate your insights clearly, whether you’re sharing with a colleague or presenting to a broader team.

Final Project

In this final lab, you’ll work with a realistic healthcare dataset and apply everything you’ve practiced. You’ll explore and communicate with data using visualizations, Markdown, multivariate analysis, and data processing. It’s a chance to bring all your skills together in one place.