Python Programming, EDA & Data Visualization – Syllabus (Headings Only)

Module 1: Python Programming

Introduction

Core Python Fundamentals

• Variables and Operators

• Data Types

• Data Structures

Control Flow

• Conditional Statements

• Loops

• Comprehensions

Functions & Modules

• Function Definitions

• Lambda Functions

• map(), filter(), reduce()

• Modules and Imports

Object-Oriented Programming

• Classes & Objects

• Constructors

• Inheritance

• Polymorphism

• Encapsulation & Abstraction

File Handling

• File Operations

• Error Handling

Module 2: NumPy

Numerical Python

• Arrays

• Array Operations

• Mathematical Functions

• Indexing & Slicing

• Vectorization

• Advanced NumPy

• Descriptive Statistics

Module 2: Pandas Data Manipulation

Data Structures

• Series

• DataFrames

Data Handling

• Reading/Writing Files

• Indexing & Filtering

• Missing Values

• Duplicates

• Outlier Handling

Data Operations

• GroupBy

• Pivot & Crosstab

• Merge & Join

• Date-Time Processing

• Window Functions

Module 2: Exploratory Data Analysis (EDA)

Univariate Analysis

Bivariate Analysis

Multivariate Analysis

Full EDA Workflow

Module 2: Data Visualization (Matplotlib + Seaborn)

Matplotlib

• Basic Plots

• Subplots

• Line, Bar, Pie, Histogram

Seaborn

• Distribution Plots

• Box & Violin Plots

• Category Plots

• Joint Plots

• Pairplots

• Heatmaps

Regular Expressions for Data Cleaning

Regex Basics

Meta Characters

Pattern Matching

Cleaning Text with Regex

Capstone Project

Web Scraping

Data Cleaning

Preprocessing

Visualization

EDA

Insights Generation