Module 1:Excel for business data analytics

• Data Quality checks with conditional logics.
• Cleaning and transformation using power query.
• Data modeling and relationship
• Pivot tables for reporting.
• Chart-Based data visualization.
• DAX Basics and measures.
• Interactive excel dashboards.
• Project – Education Dashboard.

Module 2: Python for data cleaning and automation

• Python foundation
• Data wrangling with pandas.
• Advance data cleaning
• Custom functions & Automation scripts
• EDA with Matplotlib and seaborn.
• Interactive dashboard using streamlit.
• Project: Automated cleaning + EDA

Module 3: Statistics for Data Driven Insights

• Descriptive Statistics: Mean, Median, Variance, Std. Dev
• Probability & Distribution.
• Hypothesis testing (t-test, chi-square, ANOVA)
• Correlation, Covariance, Regression.
• Real world statistics application.
• Lab: Statistical testing on Business data.

Module 4: R for statistical computing

• R basics: Variable, Functions, Data Structures.
• Filtering & Data Manipulation with dplyr.
• Visualization with ggplot2 (custom theme & adv. charts)
• Performing statistical analysis
• Building interactive dashboard with shiny.
• Professional reports with R Markdown.
• Project: Statistical analysis + shiny dashboard.

Module 5: R for statistical computing

• SQL fundamentals: Select, where, order by.
• Aggregation: SUM, Count, Avg, Min, Max.
• Joins and Data Relationship
• Subqueries and CTE.
• Data cleaning and warehousing in SQL.
• Project – EDA, Data warehouse

Module 6: Power BI for business intelligence

• Data import and power query.
• Data modeling and star schema design.
• Calculated columns and Advanced DAX Measures.
• Visual elements: Cards, Tables, Charts, Maps.
• Interactive reports & Advanced Dashboard.
• Project –Business Intelligence Dashboard.

Module : Final Major Project