Data analytics

Module 1: Introduction to Data Analytics

• Overview of Data Analytics & AI

• Real-world applications and career scope

Module 2: Statistics & Probability for Data Analysis

• Descriptive & Inferential Statistics

• Probability distributions and hypothesis testing

Module 3: Core Python for Data Science

• Python basics and syntax

• Functions, loops, and data structures

Module 4: Advanced Excel for Analytics

• Pivot tables, charts, and formulas

• Data cleaning and visualization in Excel

Module 5: SQL for Data Management

• Writing queries and joins

• Aggregations, subqueries, and optimization

Module 6: Data Visualization Tools

• Tableau fundamentals and dashboards

• Storytelling with data

Module 7: Python Libraries for Analysis

• NumPy: arrays and operations

• Pandas: data frames and manipulation

• Matplotlib & Seaborn: data visualization

Module 8: AI and Data Analytics Integration

• Basics of AI and Machine Learning

• Predictive modeling and insights

Module 9: Capstone Project

• End-to-end data analysis project using Python, SQL, and Tableau

• Presenting results with visual dashboards