Exploratory Data Analysis and Visualization

Advance your data analysis skills by learning how to turn messy business questions into clear, structured exploratory analysis. In this course, you’ll build practical exploratory data analysis (EDA) skills used in roles like data analyst, business analyst, product analyst, marketing analyst, and operations analyst. You’ll practice framing an analysis plan, exploring relationships between business metrics, building scatter plots, adding trend lines, measuring correlation, and using multivariate analysis to uncover deeper patterns. This is a non-traditional, skill-based learning experience organized around real workplace tasks rather than a fixed lecture sequence. The course is designed to mirror responsibilities you may see in job descriptions, such as analyzing KPI relationships, investigating drivers of performance, and generating hypotheses for further research. You can personalize your path based on what you already know, spend more time on the skills you need, and skip content when it’s not necessary. The course brings together high-quality lessons from expert instructors, selected for the strongest coverage of each skill so you can build practical, career-relevant EDA experience. This course is a strong fit if you already have basic experience with data analysis, spreadsheets, or introductory statistics. By the end of the course, you’ll be able to turn business questions into a structured exploratory data analysis plan for reports and metric investigations. You’ll use scatter plots, trend lines, and correlation to analyze relationships between variables, then extend your analysis with multivariate techniques, identify possible confounding variables, and generate testable hypotheses for deeper research.

Strengthen your core data analysis skills by learning how to summarize, profile, and explore datasets in ways that support real business questions. In this course, you’ll build practical experience used in roles such as data analyst, business analyst, reporting analyst, operations analyst, and marketing analyst. You’ll work with common analysis techniques to examine distributions, summarize categorical and numeric data, compare variables, and support segmentation through filtering and exploratory visuals. This is a non-traditional, skill-based learning experience organized around real workplace tasks instead of a fixed lecture sequence. It’s designed to reflect responsibilities you may see in job descriptions, from profiling datasets and building summary tables to exploring variable relationships and helping stakeholders investigate data by segment. You can personalize your path based on what you already know, focus on the skills you need most, and skip content when it’s not necessary. The course curates high-quality lessons from expert instructors, selecting the strongest content for each skill so you can build practical, career-relevant data analysis experience. By the end, you’ll be able to use aggregation, cross-tabulation, frequency analysis, and measures of central tendency and dispersion to summarize data, apply charts and graphical methods to understand distributions and relationships, and use filtering and correlation techniques to support segmentation and exploratory analysis. This course is a strong fit if you already have basic experience with spreadsheets, data analysis, or working with tables and charts.

In Data Visualization and Reporting, you’ll learn to turn raw data into clear charts, dashboards, and reports that people actually use. This course is organized around workplace skills and job tasks, mirroring responsibilities you’ll see in real job descriptions. Start by checking what you already know, then focus on the areas you want to strengthen. If you’re confident, skip ahead. If a topic is new, review targeted lessons curated from multiple expert instructors. You’ll practice choosing the right chart for an analytical purpose, applying visual design for clarity and impact, and building visuals in Tableau and Excel. Then you’ll assemble them into readable dashboards and reports, format layouts for consistency, and add titles and annotations that surface the “so what.” Each module culminates in a graded, job-task assessment to help you validate progress. By the end, you’ll be ready to perform common tasks in roles like Data Analyst, Business Intelligence Analyst, Reporting Analyst, Operations Analyst, or Dashboard Developer.