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Python Essentials for Data Analytics

Beginner

Start simple. Build strong foundations. Learn the Python every analyst needs. Clean, analyse, and explore data like a pro.

Python Essentials for Data Analytics

Duration

4 weeks

Content

4 modules, 44 lessons

Students

33

Total Time

~5 hours

100% Free Structured Micro Course

All video lessons, coding exercises, and quizzes are completely free with zero gatekeeping. Start learning right away!

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Course Curriculum

1

PYTHON SETUP & ENVIRONMENTFREE PREVIEW

Learn how to install Python, set up Jupyter Notebook, and prepare a clean, professional development environment for data analytics.

15 min3 lessons

Installing Python

Installing Jupyter Notebook

Setting Up Your Python Environment (VS Code, venvs & pip)

2

PYTHON FUNDAMENTALSFREE PREVIEW

Master the foundational building blocks of Python—variables, datatypes, loops, conditions, strings, functions, and more.

90 min19 lessons

Python Variables

Python Basic Datatypes

QUIZ: Variables & Datatypes

Python Dictionaries

List Comprehensions & Advanced Collections

QUIZ: Lists & Dictionaries

ASSIGNMENT: Lists & Dict

Python For Loops

Python While Loops

QUIZ: For & While Loops

Python If Conditions

Python Functions

ASSIGNMENT: Loops, if conditions & functions

Text Wrangling Essentials: split, join, and formatting

Python Regular Expressions (Regex)

QUIZ: Python Fundamentals

ASSIGNMENT: Python Fundamentals

3

NUMPY FOUNDATIONSFREE PREVIEW

Learn NumPy—the backbone of numerical computation in Python—to perform fast, vectorized operations on data.

90 min8 lessons

NumPy vs Python Lists

QUIZ: Numpy Basics

NumPy Broadcasting

NumPy Aggregations

NumPy Vectorization, Boolean Masks & Statistical Aggregations

QUIZ: Numpy Foundations

ASSIGNMENT: NumPy Foundations

4

PANDAS FOR DATA ANALYTICSFREE PREVIEW

Master pandas—the most important Python library for data cleaning, manipulation, and exploration.

90 min14 lessons

DataFrame & Series Basics: Selecting Rows and Columns

Reading & Writing Data

Filtering & Sorting

Handling Missing Values

Mastering Pandas Data Cleaning: dropna, fillna, and Type Casting

Working with Date & Time

QUIZ: Basic Filtering, etc.

ASSIGNMENT: Pandas Basics

Combining DataFrames: SQL-Style Relational Merges

Groupby & Aggregations

Essential Pandas Wrangling: Merging, GroupBy Best Practices & reset_index

QUIZ: Pandas Module

ASSIGNMENT: Pandas Module

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