Day 1: Foundations of Data Analytics & Visualization

Module 1: Introduction to Data Analytics

Module 2: Understanding Data

Module 3: Fundamentals of Data Analysis & Statistics

Introduction to Descriptive Statistics (Mean, Median, Mode, Range)
Understanding Distributions (Basic Concepts)
Introduction to Correlation vs. Causation
Hands-on Activity: Calculating basic stats using sample data (e.g., in Excel/Google Sheets)

Module 4: Introduction to Data Visualization

Day 2: Applying Analytics & Communicating Insights

Module 4: Data Visualization & Dashboards (Continued)

Building Basic Dashboards: Concepts and Tools Overview (e.g., demonstrating simple dashboard creation in Excel/GoogleSheets or a tool like Tableau Public/Power BI Desktop)
Integrating multiple data sources conceptually
Activity: Designing a simple KPI dashboard layout for a given scenario

Module 5: Introduction to Predictive Analytics & Machine Learning Concepts

What is Predictive Analytics? How does it differ from descriptive?
Basic Concepts: Forecasting, Classification, Clustering (explained simply)
Introduction to Machine Learning: What it is, how it learns from data (conceptual overview)
Examples: Recommendation engines, spam filters, sales forecasting
Understanding limitations and biases

Module 6: Communicating Analytical Outcomes

Module 7: Designing Data-Driven Solutions

Framing Business Challenges as Data Questions
Case Study: Walking through a simplified business problem and how data analysis & visualization could provide solutions/insights
Group Activity: Brainstorming data approaches for sample business scenarios

ADAV-DO: Advanced Data Analytics And Visualization