Core Skills:

• Data Entry, Validation & Cleaning Techniques
  
• Flash Fill, Text-to-Columns, Conditional Formatting
  
• Removing Duplicates, Handling Missing Data
  

Advanced Functions:

• Lookup: VLOOKUP, HLOOKUP, XLOOKUP, INDEX-MATCH
  
• Logical: IF, IFS, AND, OR, Nested formulas
  
• Text, Date & Financial Functions
  
• Dynamic Arrays & What-If Analysis
  

Business Intelligence in Excel:

• Pivot Tables & Pivot Charts (Advanced Case Studies)
  
• Power Query for Data Transformation
  
• Power Pivot & Data Modeling
  
• Dashboard Design & Reporting Automation
  
• Introduction to DAX within Excel
  

Outcome: Excel as a complete data analytics and reporting platform.

MySQL (Database Management & SQL Mastery)

Core Topics:

• Installing MySQL & Workbench
  
• Understanding Databases, Schemas & Tables
  
• CRUD Operations: SELECT, INSERT, UPDATE, DELETE
  

Advanced SQL Skills:

• JOINs, UNION, GROUP BY, HAVING
  
• Functions: String, Numeric, Date
  
• Constraints, Indexes, Views
  
• Stored Procedures & Query Optimization
  

Outcome: Ability to build, manage, and query relational databases with MySQL.

Power BI (Business Intelligence & Data Visualization)

Key Areas:

• Data Import & Cleaning
  
• Power Query for Data Transformation
  
• Building Interactive Dashboards
  
• Data Relationships & Modeling
  
• DAX for Calculated Columns & Measures
  
• Publishing & Sharing Reports
  

Outcome: Create dynamic dashboards for real-time business decision-making.

Tableau (Advanced Data Visualization & Storytelling)

Key Areas:

• Connecting Multiple Data Sources
  
• Interactive Visual Analytics
  
• Calculated Fields & Parameters
  
• Dashboard Customization & User Interactivity
  
• Storyboarding & Insight Presentation

Outcome: Master Tableau for enterprise-level data storytelling and analytics.

 Python & Generative AI

Python Programming Foundations:

• Variables, Functions, Data Structures
• Pandas for Data Manipulation
• NumPy for Numerical Computing
• Matplotlib for Data Visualization

Machine Learning & AI with Python:

• Supervised & Unsupervised Learning
• Deep Learning Basics (ANN, CNN, RNN)
• Building AI Applications with Streamlit

Generative AI Integration:

• Understanding LLMs (Large Language Models)
  
• Prompt Engineering & AI Automation
  
• Creating Chatbots & AI Assistants
  
• Real-World Applications of Generative AI in Business

Outcome: Build AI-driven applications and deploy intelligent solutions.

Machine Learning with R (Bonus / Optional Module)

Topics Covered:

• R Basics & RStudio Environment
  
• Data Manipulation & Visualization in R
  
• Hypothesis Testing & Statistical Inference
  
• Regression & Time Series Modeling
  
• Introduction to Machine Learning in R

Outcome: Gain statistical depth & machine learning skills using R as an optional value-adding tool.

R&D Project (Capstone)–> Internship

Project Scope:

• Choose a real-world industry dataset or AI application
  
• Perform data collection, analysis, modeling, and visualization
  
• Deploy a Predictive Model or AI-driven System
  
• Optional: Prepare research paper or publishable project

Outcome: Create a professional portfolio project showcasing your end-to-end expertise.