Python for Beginners- Learn Python with Practical Exercises!
- Development
- Apr 28, 2025

Python for Beginners: Learn Python with Practical Exercises!, available at $34.99, has an average rating of 3.75, with 47 lectures, 1 quizzes, based on 266 reviews, and has 9865 subscribers.
You will learn about Practise coding in the most popular Python development environments for data scientists and developers alike Solid understanding of Python Programming Fundamentals Object Oriented Programming Build a Python Game Run Fully Functioning Python Game in your Terminal like a real Python Developer! This course is ideal for individuals who are For People Who want to learn Python Fundamentals and later transition into Data Science, Web Development or Big Data or For Complete Programming Beginners or For People New to Python or Not Intended for Seasoned Developers It is particularly useful for For People Who want to learn Python Fundamentals and later transition into Data Science, Web Development or Big Data or For Complete Programming Beginners or For People New to Python or Not Intended for Seasoned Developers.
Enroll now: Python for Beginners: Learn Python with Practical Exercises!
Summary
Title: Python for Beginners: Learn Python with Practical Exercises!
Price: $34.99
Average Rating: 3.75
Number of Lectures: 47
Number of Quizzes: 1
Number of Published Lectures: 47
Number of Published Quizzes: 1
Number of Curriculum Items: 48
Number of Published Curriculum Objects: 48
Original Price: A$29.99
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
Hi I’m Sam, a big data engineer and full stack web developer teaching you to program in Python in the most efficient and down to earth approach. I will not only teach you to code but also the environment used to develop python code used by everyday data scientists and big data engineers.
This course is streamlined into 3 hours to fit into a busy schedule. All content in this course will be highly reusable in a real world situation. This course is strictly no ‘fluff’ which means we will get into the core of programming straight away without going through hours of theory which you will never apply on real projects.
So if you want to learn python programming to transition into data science, or the big dataspace and don’t have the luxury of time you have come to the right place!
Course is split up into sections as below:
Environment Setup – Here you learn and install the most popular environments used by data scientists and developers
Data Types and Methods– The abc’s of the coding language.
Control and Looping?– Learn how to control the flow of the program and repeat tasks
Functions– Help Automate your tasks
Error Handling– Handles errors in real world applications
Object Oriented Programming – Learn OOP to be even better at programming
File Structure & Running in Terminal – Learn how Python modules work and run in Terminal
Course Curriculum
Chapter 1: Introduction & Environment Setup
Lecture 1: Course Introduction
Lecture 2: Iterm2 Installation
Lecture 3: Installing Python 3
Lecture 4: Installing Jupyter Notebook
Chapter 2: Data Types and Methods
Lecture 1: Data Types
Lecture 2: Int and Float
Lecture 3: Retrieving From a List
Lecture 4: List Methods
Lecture 5: Tuples
Lecture 6: String Methods
Lecture 7: Dictionary Methods
Lecture 8: Print Method
Chapter 3: Control and Looping
Lecture 1: If Else Statements Syntax
Lecture 2: If Else Control Logic Part 1
Lecture 3: If Else Control Logic Part 2
Lecture 4: For Loop and While Loop Syntax and Logic
Lecture 5: For Loop Logic and Quick Exercise
Lecture 6: While Loops Logic
Lecture 7: While Loops with If, Else Statements
Lecture 8: Break and Continue Methods
Lecture 9: Looping Exercise
Lecture 10: Looping Exercise Solution
Chapter 4: Functions
Lecture 1: Function Concept
Lecture 2: Function Examples and Quick Exercise
Lecture 3: Function Scoping
Lecture 4: Function Exercises
Lecture 5: Function Exercise Solution Part 1
Lecture 6: Function Exercise Solution Part 2
Chapter 5: Error Handling
Lecture 1: Error Handling Concept
Lecture 2: Error Handling Examples
Lecture 3: Using While Loops with Error Handling
Lecture 4: Error Handling Exercise
Lecture 5: Error Handling Exercise Solution
Chapter 6: Object Oriented Programming (OOP)
Lecture 1: OOP Concepts
Lecture 2: OOP Examples
Lecture 3: OOP Important Usage
Lecture 4: OOP Exercise and Solution
Chapter 7: Building Game Project
Lecture 1: Game Project Explanation and Hints
Lecture 2: Game Project Solution Part 1
Lecture 3: Game Project Solution Part 2
Lecture 4: Game Project Solution Part 3
Chapter 8: File Structure, Modules and Running in Terminal
Lecture 1: Installing VSCode incl. tips
Lecture 2: Installing Pylint
Lecture 3: File Structure and Modules Explained
Lecture 4: Using Python in VSCode
Lecture 5: Running Python Program in the Terminal
Chapter 9: Bonus Section
Lecture 1: My Other Courses
Instructors

Samuel Lee
Big Data Engineer|Cloud Engineer|ML and AI Enthusiast
Rating Distribution
Frequently Asked Questions
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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