🟢 Module 1: Introduction to Data Analytics

• What is Data Analytics & AI
• Types of Data (Structured & Unstructured)
• Data Analysis Lifecycle
• Applications of Data Analytics in industries

🟡 Module 2: Excel for Data Analysis

• Basics of Microsoft Excel
• Data Cleaning & Formatting
• Functions: IF, VLOOKUP/XLOOKUP, INDEX-MATCH
• Pivot Tables & Pivot Charts
• Data Visualization (Charts & Graphs)
• Introduction to Dashboards in Excel

🔵 Module 3: SQL for Data Analysis

• Introduction to Databases & SQL
• SELECT, WHERE, ORDER BY, LIMIT
• Aggregate Functions (SUM, COUNT, AVG)
• Joins (INNER, LEFT, RIGHT)
• Grouping & Filtering (GROUP BY, HAVING)
• Subqueries & Views
• Real-world Data Query Practice

🟣 Module 4: Python for Data Analysis

• Introduction to Python
• Data Types & Control Structures
• Libraries: NumPy & Pandas
• Data Cleaning & Transformation
• Exploratory Data Analysis (EDA)
• Data Visualization using Matplotlib & Seaborn

🟠 Module 5: Power BI for Visualization

• Introduction to Power BI
• Data Import & Transformation (Power Query)
• Data Modeling & Relationships
• DAX Basics
• Creating Interactive Dashboards
• Publishing & Sharing Reports

🔴 Module 6: Data Analysis with AI

• Introduction to AI in Data Analytics
• Basics of Machine Learning
• Supervised vs Unsupervised Learning
• Predictive Analytics Concepts
• Using AI Tools for Automation & Insights

⚫ Module 7: Capstone Project

• Real-world Dataset Analysis
• End-to-End Project (Excel + SQL + Python + Power BI)
• Dashboard Creation & Presentation

🎯 Outcome of the Course

• Work with real datasets using Excel, SQL, Python, and Power BI
• Build dashboards and reports
• Apply AI concepts in data analysis
• Solve business problems using data