Course Content
Getting Started with Python
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Why Python for Data Analysis?
Setting up Google Colab (no installations needed)
Writing your first Python line
Comments and Code Blocks
Python Basics for Analysts
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Variables and Data Types (int, float, string, boolean)
Type casting and basic functions: len(), type()
Arithmetic & Comparison Operators
Lists, Tuples, and Dictionaries
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Creating and modifying lists
Dictionary basics (key-value pairs for real-life data)
Why these are useful for structured data
Introduction to Pandas
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What is Pandas? Why it’s key for analysts
Creating Series and DataFrames
Reading a CSV file
head(), info(), describe()
Selecting columns and rows
Simple filtering
Basic Data Cleaning
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Handling null values
Changing column names
Mini Project – Quick EDA
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Apply all learned steps on one dataset
Wrap-Up and What’s Next
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Recap of skills learned
Tools to practice: Kaggle, Google Colab
Learn Complete EDA or Power BI
Python for Data Analysts – Quick Start
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