Data Analysis using Python

Syllabus

Curriculum / Syllabus

Structured modular learning flow designed to take you from absolute basics to job readiness.

Detailed Program Overview & Curriculum

🖥️ Module 1: Python Fundamentals

> Introduction to Python
> Python Installation & IDE Setup
> Variables, Data Types & Operators
> Input & Output
> Conditional Statements
> Loops (For & While)
> Functions
> Lists, Tuples, Sets & Dictionaries

📊 Module 2: NumPy Fundamentals

> Introduction to NumPy
> Creating Arrays
> Array Indexing & Slicing
> Mathematical Operations
> Broadcasting
> Array Manipulation
> Statistical Functions

📋 Module 3: Pandas Fundamentals

> Introduction to Pandas
> Series & DataFrames
> Reading CSV & Excel Files
> Writing Data to Files
> Data Selection & Filtering
> Sorting Data
> Handling Missing Values

🧹 Module 4: Data Cleaning

> Handling Null Values
> Removing Duplicates
> Data Type Conversion
> String Operations
> Detecting Outliers
> Data Standardization
> Data Validation

🔄 Module 5: Data Wrangling

> Filtering Data
> Sorting Data
> GroupBy Operations
> Aggregation Functions
> Merge & Join
> Concatenate DataFrames
> Pivot Tables

📈 Module 6: Data Visualization

> Introduction to Matplotlib
> Line Chart
> Bar Chart
> Pie Chart
> Histogram
> Scatter Plot
> Seaborn Basics
> Heatmaps
> Distribution Plots

🔍 Module 7: Exploratory Data Analysis (EDA)

> Data Inspection
> Descriptive Statistics
> Correlation Analysis
> Feature Analysis
> Finding Trends & Patterns
> Data Storytelling
> Business Insights

🤖 Module 8: Introduction to Machine Learning

> What is Machine Learning?
> Types of Machine Learning
> Scikit-Learn Overview
> Train-Test Split
> Simple Linear Regression
> Model Evaluation Basics

💼 Module 9: Industry Capstone Project

> Import Real-World Dataset
> Data Cleaning & Transformation
> Exploratory Data Analysis (EDA)
> Data Visualization Dashboard
> Business Insights
> Report Generation
> End-to-End Analytics Project
> Final Project Presentation

Program Details

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