Class Overview
Are you ready to master Python quickly and easily—without confusion or frustration? Python, Visually Explained is the ultimate beginner-friendly course that simplifies programming basics through clear, concise explanations and practical, real-world examples. Whether you’re new to programming or looking to enhance your skills, this course teaches you how to think like a coder and solve problems using Python, one of the most versatile and in-demand programming languages today.
Class Resources
All notebooks shown in lecture videos, exercise notebooks, and exercise solutions notebooks can be found on our course GitHub page: <a href="https://github.com/Visually-Explained/Python-Visually-Explained" rel="nofollow noreferrer noopener" target="_blank">https://github.com/Visually-Explained/Python-Visually-Explained</a>
What You Will Learn
By taking this course, you’ll gain hands-on experience and foundational knowledge in the following topics:
<ul>
<li>Getting Started with Google Colab: Your first step into Python, made easy.</li>
<li>Numeric Operations: Understand how numbers work in programming.</li>
<li>Data Types &amp; Variables: Learn how to store and manipulate data like a pro.</li>
<li>Strings &amp; Text Manipulation: Handle text and characters with confidence.</li>
<li>Built-in Functions &amp; Methods: Simplify your code with Python’s built-in tools.</li>
<li>Booleans &amp; Comparisons: Learn the logic behind decision-making in programming.</li>
<li>Conditionals &amp; Loops: Write efficient programs that can make decisions and repeat tasks.</li>
<li>Data Structures (Lists, Tuples, Sets, and Dictionaries): Master Python’s most useful data structures.</li>
<li>User Input &amp; Error Handling: Build interactive programs and handle errors like a pro.</li>
<li>Functions, Namespaces, and Scope: Create reusable code with confidence.</li>
<li>Modules &amp; Libraries: Unlock Python’s full potential by using external libraries.</li>
<li>Visualization with Matplotlib &amp; Data Analysis with Pandas: Work with real data and bring it to life.</li>
</ul>
Why You Should Take This Class
<ul>
<li>Clear and engaging explanations: Topics are broken down into bite-sized lessons, ensuring you never feel overwhelmed.</li>
<li>Hands-on exercises: Apply what you learn through practical, real-world coding challenges.</li>
<li>Beginner-friendly: No prior programming experience is required—perfect for complete beginners.</li>
<li>Flexible learning: Self-paced, so you can learn whenever and wherever it suits you.</li>
</ul>
By the end of this course, you’ll confidently write Python code, solve practical problems, visualize data, and perform basic data analysis. Whether you aim to start a new career, automate everyday tasks, or learn a valuable skill, this course will set you up for success.
Who This Class is For
This course is perfect for:
<ul>
<li>Complete beginners who have no prior experience with coding or Python.</li>
<li>Professionals or students looking to build foundational programming skills.</li>
<li>Anyone interested in learning Python for automation, data analysis, or career development. No prior coding knowledge is required to take this class.</li>
</ul>
Materials/Resources
To take this course, you will need:
<ul>
<li>A computer with internet access.</li>
<li>A Google account to use Google Colab (free online coding environment).</li>
<li>No additional software or setup is required.</li>
</ul>
Resources provided in the course:
<ul>
<li>Example code snippets.</li>
<li>Step-by-step exercises.</li>
<li>Templates and starter files to practice along with the lessons.</li>
</ul>

Course Introduction

Getting Started with Colab

Numeric Operations

Numeric Operations - Guided Examples

Introduction to Data Types

Numeric Operations and Data Types - Exercise Solutions

Strings

Strings  - Guided Examples

Strings - Exercise Solutions

Variables

Variables - Guided Examples

Variables - Exercise Solutions

Built-in Functions

Built-in Functions - Guided Examples

Built-in Functions - Exercise Solutions

Built-in Type Methods

Built-in Type Methods - Guided Examples

Built-in Type Methods - Exercise Solutions

Booleans and Comparison Operators

Booleans and Comparison Operators - Guided Examples

Booleans and Comparison Operators - Exercise Solutions

Conditionals

Conditionals - Guided Examples

Conditionals - Exercise Solutions

Lists

Lists - Guided Examples

Lists - Exercise Solutions

Tuples

Sets

Collections - Guided Examples

Collections - Exercise Solutions

For Loops

For Loops - Guided Examples

For Loops - Exercise Solutions

Dictionaries

Dictionaries - Guided Examples

Dictionaries - Exercise Solutions

User Input

Error Handling

User Input and Error Handling - Guided Examples

User Input and Error Handling - Exercise Solutions

While Loops

While Loops - Guided Examples

While Loops - Exercise Solutions

User-defined Functions

User-defined Functions - Guided Examples

User-defined Functions - Exercise Solutions

Namespace and Scope

Namespace and Scope - Guided Examples

Namespace and Scope - Exercise Solutions

Modules and Libraries

Modules and Libraries - Guided Examples

Python Standard Library - Exercise Solutions

Matplotlib - Exericse Solution

Pandas - Exercise Solution

Language Translator App - Project Introduction

Language Translator App - Project Solution

Python, Visually Explained

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