Whether you’re new to programming or a seasoned developer looking to pick up a new language, Just Enough Python is the perfect starting point. This guide provides a streamlined, practical approach to Python, giving you the essential skills without overwhelming you with unnecessary details. You’ll learn how to write clean, effective Python code that solves real-world problems, automates tedious tasks, and helps you build projects from scratch.

With Python’s simplicity, readability, and versatility, it has become one of the most popular languages in the world. This guide is designed to help you navigate Python’s most important concepts, including variables, functions, data structures, and libraries, so you can confidently apply them in your own work. Whether you’re aiming to enter the world of data science, web development, or simply automate tasks, Just Enough Python will equip you with the tools and knowledge to get started quickly and efficiently, making it ideal for both beginners and experienced programmers looking to enhance their skills.

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Course Progress

Course Details

General Note

  • Exercise Environment Overview
  • Course Exercises


Running Python Scripts and Statements in the REPL

  • Using the Interpreter
  • Executing a Program
  • Executing Statements in the REPL


Creating Virtual Environments and Using pip for Managing Dependencies

  • Creating a Virtual Environment
  • Installing a Library

Working with Variables

  • Variables in Python


Controlling Program Flow

  • Controlling Program Flow Using if
  • Controlling Program Flow Using while
  • Controlling Program Flow Using for


Creating Functions and Modules

  • Creating Functions
  • Built-in Functions
  • Modules and Libraries



Using Data Structures

  • Working with Lists
  • Working with Tuples
  • Working with Dictionaries
  • Working with Sets
  • Using Flow Statements with Collections


Working with Files

  • Working with Files


Essential & Data Science Libraries

  • Using the Python Standard Library
  • Using numpy for Working with Numerical Data
  • Using pandas, the Data Analysis Library
  • Using matplotlib to Visualize Data


Using Lambda Functions and Method Chaining

  • Using Lambda Functions
  • Method Chaining