Learn Python Programming Masterclass
This Python For Beginners Course Teaches You The Python Language Fast. Includes Python Online Training With Python 3
This Python For Beginners Course Teaches You The Python Language Fast. Includes Python Online Training With Python 3
Whether you want to:
- build the skills you need to get your first Python programming job
- move to a more senior software developer position
- get started with Machine Learning, Data Science, Django or other hot areas that Python specialises in
- or just learn Python to be able to create your own Python apps quickly.
…then you need a solid foundation in Python programming. And this course is designed to give you those core skills, fast.
This course is aimed at complete beginners who have never programmed before, as well as existing programmers who want to increase their career options by learning Python.
The fact is, Python is one of the most popular programming languages in the world – Huge companies like Google use it in mission critical applications like Google Search.
And Python is the number one language choice for machine learning, data science and artificial intelligence. To get those high paying jobs you need an expert knowledge of Python, and that’s what you will get from this course.
By the end of the course you’ll be able to apply in confidence for Python programming jobs. And yes, this applies even if you have never programmed before. With the right skills which you will learn in this course, you can become employable and valuable in the eyes of future employers.
Here’s what a few students have told us about the course after going through it.
“I had very limited programming experience before I started this course, so I have really learned a lot from the first few sections. It has taken me from essentially zero programming skill to a level where I'm comfortable using Python to analyze data for my lab reports, and I'm not even halfway done the course yet. There are other courses out there which focus on data analysis, but those courses are usually targeted at people who already know how to program which is why I chose this course instead. “ – Christian DiMaria
“I have been puttering through your Python course . In that time, though, and without finishing it yet I've been able to automate quite a bit at my work. I work in a school system and unifying data from our various student information systems can be incredibly frustrating, time consuming, and at times challenging. Using your course, I've learned enough to write applications that turn massive text files into dictionaries that get "stitched" together like a database and output to properly formatted CSV files and then uploaded via SFTP to various systems for secure processing. Our teachers, students, and the tech department have greatly benefitted from this automation. I just wanted to drop you a note thanking you for helping me learn this skill.” – Keith Medlin
“This course was great. Within 3 weeks I was able to write my own database related applications.” – Theo Coenen
And there are many more students who love the course – check out all the reviews for yourself.
Will this course give you core python skills?
Yes it will. There are a range of exciting opportunities for Python developers. All of them require a solid understanding of Python, and that’s what you will learn in this course.
Will the course teach me data science, machine learning and artificial intelligence?
No, it won’t do that – All of these topics are branches of Python programming. And all of them require a solid understanding of the Python language.
Nearly all courses on these topics assume that you understand Python, and without it you will quickly become lost and confused.
This course will give you that core, solid understanding of the Python programming language.
By the end of the course you will be ready to apply for Python programming positions as well as move on to specific areas of Python, as listed above.
Why should you take this course?
There are a lot of Python courses on Udemy – Your instructors, Tim and Jean-Paul are pretty unique in that between them they have around 70 years of professional programming experience. That’s more than a lifetime of skills you get to learn Python from.
You can enrol in the course safe in the knowledge that they are not just teachers, but professional programmers with real commercial programming experience, having worked with big companies like IBM, Mitsubishi, Fujitsu and Saab in the past.
As such you will not only be learning Python, but you will be learning industry best practices for Python programming that real employers demand.
And if that’s not enough take a read of some of the many reviews from happy students – there are around 100,000 students who have left around 19,000 reviews.
This is one of the most popular courses on Python programming on Udemy.
Here’s just some of what you’ll learn
(It’s okay if you don’t understand all this yet, you will in the course)
· All the essential Python keywords, operators, statements, and expressions needed to fully understand exactly what you’re coding and why - making programming easy to grasp and less frustrating
· You will learn the answers to questions like What is the Python For Loop, what is Python used for, how Python switch the traditional syntax of code, and more.
· Complete chapters on object-oriented programming and many other aspects of Python, including tKInter (for building GUI Interfaces) and using databases with Python.
· Although this is primarily a Python 3 course, a python developer will need to work with Python 2 projects from time to time – We’ll show the difference in both versions to make sure you understand how things work differently in each version.
· How to develop powerful Python applications using one of the most powerful Integrated Development Environments on the market, IntelliJ IDEA! - Meaning you can code functional programs easier. IntelliJ has both a FREE and PAID version, and you can use either in this course. PyCharm will also work just fine.
(Don’t worry if you want to use another IDE. You’re free to use any IDE and still get the most out of this course).
Does the course get updated?
It’s no secret how technology is advancing at a rapid rate. New, more powerful hardware and software are being released every day, meaning it’s crucial to stay on top with the latest knowledge.
A lot of other courses on Udemy get released once, and never get updated. Learning from an outdated course and/or an outdated version of Python can be counter productive and even worse it could teach you the wrong way to do things.
For example if you apply some parts of Python 2 to Python 3 code, you will get completely different results.
We cover differences like this in the course and also continually update the course as well.
What if you have questions?
As if this course wasn’t complete enough, we offer full support, answering any questions you have 7 days a week (whereas many instructors answer just once per week, or not at all).
This means you’ll never find yourself stuck on one lesson for days on end. With our hand-holding guidance, you’ll progress smoothly through this course without any major roadblocks.
That’s just one reason why Tim was voted top 10 in the Udemy instructor awards (out of a whopping 18,000 instructors), and quickly became a top-rated, bestselling instructor on the Udemy site.
Student Quote: “Tim and JP are excellent teachers and are constantly answering questions and surveying students on new topics they will like to learn. This isn't a Python course it’s THE Python course you need.” – Sean Burger
There’s no risk either!
This course comes with a full 30 day money-back guarantee. Meaning if you are not completely satisfied with the course or your progress, simply let Tim or J-P know and they will refund you 100%, every last penny no questions asked.
You either end up with Python skills, go on to develop great programs and potentially make an awesome career for yourself, or you try the course and simply get all your money back if you don’t like it…
You literally can’t lose.
Ready to get started, developer?
Enrol now using the “Add to Cart” button on the right, and get started on your way to creative, advanced Python brilliance. Or, take this course for a free spin using the preview feature, so you know you’re 100% certain this course is for you.
See you on the inside (hurry, your Python class is waiting!)
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Welcome to the Python Masterclass: Meet Your Expert Instructors
122 Xem trướcCourse Enhancements: Updates, Larger Fonts, and Downloadable Slides
124 Xem trướcOptimizing Video Playback: Achieving Crisp 1080p Resolution on Udemy
68 Xem trướcEnhance Comprehension: Enabling and Using Hand-Edited English Subtitles
80Mastering Python Support: Utilizing the Q&A for Effective Assistance
286 Xem trướcMaximize Learning: The Importance of Hands-On Coding and Source Code Access
175What is an IDE?
145 Xem trướcStep-by-Step Python Installation for Windows 10 and 11: Download to Setup
152Installing IntelliJ IDEA on Windows: A Quick and Easy Guide for Beginners
346MacOS Python Installation: Downloading and Setting Up Python on Your Mac
203Get Started with IntelliJ IDEA on macOS: Download and Installation Guide
281 Xem trướcInstalling Python on Linux (Ubuntu 22.04): Terminal Commands & Pip Setup
265 Xem trướcInstalling IntelliJ IDEA Community Edition on Linux: Step-by-Step Ubuntu Guide
225Configure IntelliJ IDEA for Python: Essential Setup for Windows, Mac, Linux
748Optimize IntelliJ IDEA: Customize Settings for Enhanced Python Development
260Introduction to Python: What is Python and Why Learn It?
136Creating Your First Python Program: The Classic "Hello World" Example
233Mastering the Print Function in Python: Outputting Text and Calculations
435Displaying a String: "My Hovercraft is Full of Eels
0Python Calculations: Print the Result of 6 times 7
0Working with Strings in Python: Concatenation, Quotes, and Input
443Escape Characters in Python Strings: Newlines, Tabs, and Quotes (\n, \t)
456Formatting Output with Tabs: Aligning Text in Python
0Advanced String Manipulation: Handling Backslashes and Special Characters
229Understanding Variables and Data Types in Python: Int, String, and More
445Strong Typing in Python: Understanding Data Type Compatibility and Errors
290Exploring Python's Numeric Data Types: Int, Float, and Complex Numbers
227Performing Calculations in Python: Understanding Numeric Operators
332What are Expressions in Python? Understanding Calculations and Values
317Integer Division: Calculate Whole Number Results in Python
0Mastering Operator Precedence and Understanding Order of Operations in Python
434Comprehensive Guide to the str String Data Type: Sequence of Characters in Pytho
354Unlocking Negative Indexing: Accessing String Characters from the End in Python
247String Slicing: Extracting Substrings with Start, Stop, and Step Values in Pytho
596Advanced String Slicing: How to Effectively Use Negative Numbers in Python Code
161Mastering Step Slicing: Extracting Characters with Intervals from Python Strings
437Backwards Slicing Techniques: Using Negative Steps to Reverse Python Strings
305Solving the Slicing Challenge Plus Common Python Slicing Idioms Explained
314Understanding String Operators: Concatenation, Multiplication, and 'in' in Pytho
508Mastering String Replacement Fields: Enhancing Output with .format() in Python 3
663Advanced String Formatting: Controlling Field Width, Alignment, and Precision
650Exploring Python 3.6 f-strings: A Modern Approach to String Formatting
218Understanding Python 2 String Interpolation: Legacy String Formatting Techniques
321Recap of Python Fundamentals: Key Concepts from the Stepping into Python Section
59Mastering the Basics of Python - Test Your Knowledge on Core Concepts
Getting Started with Code Blocks and Understanding Python Statements
613Mastering if Statements: Controlling Program Flow with Conditional Logic
577Enhancing Conditional Logic: Using elif for Multiple Condition Checks in Python
293Leveraging the Debugger in IntelliJ or PyCharm for Efficient Python Code
620Building a Simple Guessing Game: Practicing if, elif, and else in Python
299Debugging the Guessing Game: Step-by-Step Execution with if, elif, and else
240String Comparison: Applying 'if' with String Variables for Condition Evaluation
0Basic Conditional Logic: Implementing if/elif/else for Value Comparison
0Enhancing the Guessing Game: Implementing Logic for a Second Guess in Python
378Conditional Operators: Comprehensive Guide to 'less than', 'equal to' in Python
511Rewriting the Guessing Game: Optimizing Conditional Checks in Python Code
152Mastering Complex Conditions: How to Effectively Use 'and', 'or' in Python
310Understanding and Implementing Chained Comparisons
279Understanding Boolean Expressions and the Concepts of True and False in Python
468Exploring Truthy and Falsy Values in Python: Beyond Boolean True and False
270Using 'in' and 'not in' Operators for Efficient Python String Searching
406Practical Python: 'If' Conditionals Challenge for Real-World Scenarios
59'If' Challenge Solution: Mastering Conditional Logic in Python Programs
202Python For Loops Explained: Iterating Through Sequences and Strings
369Debugging Python For Loops: Step-by-Step Execution and Variable Inspection
464Extracting User Input Values with For Loops: A Practical Python Example
309Find and Print Capital Letters: Python String Manipulation Exercise
0Python Range Objects: Efficient Iteration with Start, Stop, and Step Values
188Basic Number Printing with For Loops: A Beginner Python Exercise
0Advanced Range Techniques: Mastering Start, Stop, and Step in Python Loops
265Divisibility Check: Python For Loop and Step Value Practice Exercise
0Nested For Loops in Python: Constructing Complex Iterative Structures
390Controlling Loop Flow: The 'continue' Statement in Python For Loops
447Terminating Loops: Using the 'break' Statement in Python For Loops
411Variable Initialization and None in Python: Best Practices and Explanation
271Controlling Program Execution: Understanding While Loops in Python
373Advanced While Loop Techniques: Practical Applications and Considerations
368Python While Loops: Using 'break' to Control Loop Termination Effectively
228Controlled Iteration: Using 'break' with a Divisibility Condition
0Selective Iteration: Using 'continue' to Skip Specific Numbers in Python
0Generating Random Numbers in Python: Exploring the 'random' Module and Import
566While Loop Challenge Solution: Building an Interactive Guessing Game in Python
326Binary Search Algorithm Explained: Efficient Number Guessing in Python
319Implementing a High-Low Guessing Game: A Practical Python Project
520Completing the Hi-Lo Game: 'pass' Statement and Python Code Structure
256Thoroughly Testing the Hi-Lo Game: Ensuring Robustness and Correctness
398Python Augmented Assignment: Efficient In-Place Operations Explained
462Multiplication Through Repeated Addition: Augmented Assignment in Python
0PEP 8: Adhering to the Python Style Guide for Readable and Maintainable Code
509Refactoring Python Code: Improving Structure and Readability Safely
211Python Loop Control: Mastering the ELSE Clause in FOR Loops
321Mastering 'else' in Python Loops: Hi-Lo Game Enhancement
306Debugging in PyCharm & IntelliJ: Conditional Breakpoints
283Practical Python: Using 'else' with Loops in Game Development
108Python Flow Control Mastery: Section Review and Coding Task
199Solving the Python Menu Challenge: Step-by-Step Code Solution
230Optimizing Python Code: Menu Challenge Refactoring Solution
295Advanced Python Loop Control: Replacing 'while True'
107Mastering Python Flow Control: If/Else, For/While Loops Quiz
Sequence Types in Python: Lists, Tuples, and Ranges
175Python Lists: Creating, Indexing, and Slicing Lists
264Understanding Immutable Objects in Python: Int, Float, Bool
390Python Mutable Objects: Lists, Dictionaries, and Sets
279List Aliasing: Multiple Names for the Same Python List
204Python Sequence Operations: Min, Max, Len, and Count
284Python Mutable Sequence Operations: Append and More
221Adding Items to a List with Append: Python By Example
461Python Coding Challenge Solution: Adding Menu Options
127Python List Iteration: Efficient Looping with Enumerate
252Mastering Python's Enumerate Function: Indexes and Values
268Python Code Refactoring: Dynamic Menu with List Comprehension
502Flower and Shrub List Separator
0Python List Manipulation: Removing Items with .remove()
309Mastering List Sorting in Python: Sort() vs. Sorted()
268Python's Built-in Functions: A Comprehensive Overview
227Python List Sorting: Mastering the sorted() Function
597Case-Insensitive String Sorting in Python: str.casefold()
280Creating Python Lists: Literals, Concatenation, and More
556Python List Slicing: Replacing Subsets of List Elements
354Python List Modification: Safely Deleting Items
449Removing List Values Safely: Handling Ordered Data
173Python List Processing: Removing High Values Efficiently
392Python Testing Best Practices: Edge Cases and Corner Cases
200Thorough Python Code Testing: A Practical Demonstration
227Reverse Iteration: Removing List Items from the End
354Reverse Iteration in Python: Using the reversed() Function
304Algorithm Performance in Python: Comparing Deletion Methods
538Python Lists: Quick Recap of Key Concepts and Techniques
170Nested Lists in Python: Structure, Access, and PEP 8 Style
553Processing Nested Lists in Python: A Practical Example
282Python Challenge Solution: Removing 'spam' from Nested Lists
216Python Function Signatures: Understanding Parameters
215Python's print() Function Revisited: sep and end
383String Manipulation in Python: The join() Method
464String Manipulation in Python: The split() Method
549Converting Strings to Integers in Python: Mini-Challenge Solution
343The Magical Adder
0Introduction to Tuples: Python's Immutable Sequences
285Understanding Immutability: Working with Python Tuples
441Tuple Unpacking in Python: Assigning Multiple Variables
389Practical Tuple Unpacking: Real-World Python Examples
246More on Unpacking in Python: Sequences and Variables
369Nested Data Structures: Combining Tuples and Lists in Python
311Python Tuple Unpacking Challenge: Efficient Code Solution
190Delving into Nested Structures: Practical Tuple Applications
224Mastering Complex Data: A Comprehensive Guide to Nested Structures
337Advanced Python List Navigation: Mastering Multi-Level Indexing
260Practical Application of Nested Data Structure Indexing in Python
0Jukebox Project Preview: Interactive Menu System in Python
145Project Setup: Importing Data and Managing Dependencies in Python
305Building the Jukebox: Dynamic Menu Creation and User Input Handling
424Understanding Constants in Python: Best Practices for Code Clarity
533Completing the Python Jukebox: Song Selection and Playback Logic
337Enhance Jukebox: Navigating Back to Main Menu Without Song Selection
42Jukebox Challenge Resolved: Enabling Seamless Menu Navigation
243Lists, Tuples, and Jukebox: Key Takeaways from the Section
167Getting Started with Functions: A Practical Overview
158Constructing Custom Functions: Syntax, Structure, and Return Values
335Analyzing Program Execution: Function Calls and Debugging Techniques
265Function Parameters and Arguments: Passing Data and Understanding Scope
280Debugging Parameterized Functions: Step-by-Step Execution Analysis
479Creating a Palindrome Checker: Function Design and String Manipulation
433Palindrome Challenge: Enhancing Case-Insensitive String Comparison
179Sentence Palindrome Challenge: Handling Punctuation and Spaces
328Advanced Function Design: Calling Functions Within Functions
125Return Values in Python: Explicit and Implicit Function Outputs
484Get_integer Input Validation: Error Handling and User Messaging
255Even or Odd Numbers within a Specified Range
0Understanding None: Python's Default Return Value for Functions
178Designing Action-Oriented Functions: Banner Printing Example
478Exception Handling: Managing Invalid Arguments with ValueError
442Function Parameter Customization: Setting Width for Enhanced Flexibility
126Enhancing Function Usability: Implementing Default Parameter Values
154Improving Function Calls with Keyword Arguments for Clarity
381Documenting Functions: Creating Clear and Informative Docstrings
363Generating Function Documentation: Writing and Using Docstrings
470Docstring Best Practices and Tools: Achieving Professional Code Quality
373Docstring Challenge: Solutions and Best Practices for Documentation
Introduction to Fibonacci Numbers: Mathematical Concepts and Sequences
232Implementing a Fibonacci Sequence Generator: A Practical Function Example
487Type Hints and Annotations: Enhancing Code Readability and Clarity
436Combining Annotations and Default Values in Python Function Parameters
212Documenting the banner_text Function: A Comprehensive Docstring Example
Historical Context: Teletypewriters, ANSI Escape Codes, and Terminals
334Enhancing Terminal Output: Implementing Text Coloring and Effects
470Testing Python Programs: Simulating User Execution Environments
355Installing the Colorama Package
489Step-by-Step Guide to Activating a Virtual Environment in Python
361Creating Automated Tests for the HiLo Game Using Python Functions
599Analyzing Binary Search Efficiency: Counting Correct Guesses in HiLo
287Implement the Fizz Buzz Game Logic Using a Python Function
0Building an Interactive Fizz Buzz Game: Player vs Computer in Python
242Developing a Complete Fizz Buzz Game: Solution and Implementation Details
386Creating a Python Function to Calculate Factorials with Docstrings
0Mastering Variable Arguments in Python: A Deep Dive into *args Unpacking
458Enhancing the colour_print Function with Multiple ANSI Escape Sequences
329Understanding Python Function Parameters: Ordering and Usage Rules
138Practical Application of Python Parameter Types: A Hands-On Example
406Summation Function: Utilizing Variable Arguments (*args) in Python
0Comprehensive Summary of Python Functions: Key Concepts and Best
215Introduction to Python Dictionaries and Sets: Core Data Structures
94Python Dictionary Fundamentals: Understanding Key-Value Data Storage
499Iterating Over Dictionaries in Python: Keys, Values, and Items Method
398Adding Items to a Dictionary in Python: Modifying Dictionary Contents
246Modifying Dictionary Values in Python: Updating and Replacing Entries
218Deleting Dictionary Items in Python: Using del and pop Methods
428Efficiently Using in with Python Dictionaries: Checking for Key Existence
478Solution: Building a Menu System with Python Dictionaries (Challenge)
512Integrating Lists and Dictionaries in Python: A Practical Example
Enhancing the Computer Builder: Adding Dictionary Item Functionality
299Creating a Smart Fridge Application: Leveraging Multiple Dictionaries
263Meal Planner in Python: Displaying and Selecting Recipes from a Dictionary
559Combining Python Dictionaries: Accessing Nested Data Structures
345Pantry Check: Validating Recipe Ingredients Against Available Stock
263Recipe Data Structures: Dictionaries vs. Tuples for Quantity Tracking
319Implementing Quantity Checks in Python Dictionaries for Inventory Management
384Enhancing the Meal Planner: Building a Dynamic Shopping List (Challenge)
411Refactoring Code: Adapting to Data Structure Changes in Python Programs
342Optimizing Dictionary Updates: Introducing the setdefault Method in Python
604Counting Character Occurrences in a String: Building a Frequency Dictionary
0Integrating External APIs: A Practical Mobile Phone Data Synchronization Demo
487Exploring the Python dict API: A Comprehensive Documentation Overview
518Remaining Dictionary Methods: fromkeys, keys, and values in Python
277Dictionary Manipulation: Utilizing the update Method for Efficient Merging
388Working with Dictionary Views: Accessing Dynamic Values using values Method
486Understanding References and Mutable Objects in Python Dictionaries
339Step-by-Step Demonstration of Shallow Copying in Python Dictionaries
346Illustrating Shallow Copy: A Detailed Walkthrough of Dictionary References
227Contrasting Deep and Shallow Copies: Implications for Mutable Dictionary Values
311Implementing a Custom Deep Copy Function for Python Dictionaries (Challenge)
518Understanding Hash Functions and Hash Values in Python
476Implementing a Basic Hashing Function: A Practical Example
525Practical Implementation of Hash Tables in Python Explained
417Creating a Simple Dictionary: Hash Table Implementation
307Securing Data: Exploring Hash Functions in Cybersecurity
229Python's hashlib Module: Secure Hashes and Message Digests
731Introduction to Sets: Unordered Collections of Unique Items
372Working with Python Sets: Basic Operations and Examples
288Unordered Nature of Sets: Implications and Considerations
296Efficient Membership Testing: Leveraging Python Sets
489Optimizing Code with Sets: Fast Membership Testing
435Modifying Sets in Python: Adding Items with the add() Method
342Removing Duplicates from Data: Leveraging the Power of Python Sets
381Removing Elements: Comprehensive Guide to Python's Set Methods
497Safely Removing Items from Sets: Mastering Python's discard Method
324Efficient Set Modification: Mastering the remove Method
627Arbitrary Element Removal: Understanding pop in Python Sets
281Combining Sets: Comprehensive Guide to Set Union in Python
332Real-World Applications: Implementing Set Union in Python
259Modifying Sets Efficiently: Using the Union Update Method
177Methods Versus Operators: Advantages of Methods with Iterables
303Finding Common Elements: Mastering Set Intersection in Python
335Identifying Overlapping Data: Practical Use of Set Intersection
356Preposition Intersection
0Exclusive Elements: Understanding Set Difference in Python
139Practical Set Operations: Applying Set Difference in Real Scenarios
178Finding Unique Items Using Set Difference
0Unique Elements Combined: Exploring Set Symmetric Difference
366Exploring Relationships: Subsets and Supersets in Python Sets
184Checking Set Relationships: Implementing Subset and Superset
407Python Sets: Select Job Candidates with Superset and Proper Superset
485Python Dictionary & Set Mastery: Comprehensive Review and Recap
Python Input and Output (I/O) Fundamentals: An Introductory Overview
103Understanding Computer File Systems: Files, Directories, and Paths
638Command Line Navigation: Mastering the Terminal or Command Prompt
366Demystifying File Paths: Absolute vs. Relative and Cross-Platform
703Defining and Working with Text Files: Formats, Uses and Examples
147Reading Data from Text Files: A Comprehensive Python Approach
638Python's with Statement: Simplifying File Handling for Beginners
191Python's with Statement: Simplifying File Handling for Beginners
503Mastering Python's String strip Methods: strip, lstrip, rstrip
418String Manipulation: Using removeprefix and removesuffix (Python 3.9+)
312Parsing Text File Data: A Step-by-Step Guide for Python Developers
353Efficient Text Data Handling: Organizing and Structuring Information
389Challenge Solution: Retrieving and Displaying a Country's Capital City
358Efficient Data Retrieval: Implementing Multiple Keys for Dictionary Values
203Writing to Text Files: A Comprehensive Guide to Printing Output Data
275File Handling in Python: Writing Text Data Using the write Method
544Understanding Python File Modes: r, w, x, a, r+, and w+
298A Deep Dive into Character Encodings: ASCII, EBCDIC and Unicode
393Working with Unicode Strings and Encodings in Python (UTF-8)
246Identifying and Handling File Encodings in Python: A Practical Guide
621Data Serialization with JSON: Encoding and Decoding in Python
457Understanding JSON Data Types and Limitations in Python Serialization
368Parsing Real-World JSON Data from a File: A Temperature Anomaly Example
464Downloading and Parsing JSON Data from the Internet Using Python
483Introduction to the CSV File Format: Structure, Uses, and Standards
407Efficient CSV Data Handling: Reading and Parsing with Python's CSV Module
472Mastering CSV Quoting: Handling Special Characters and Data Types in Python
338Understanding and Utilizing CSV Dialects and Sniffer in Python
401Exploring the CSV Dialect Object and Its Attributes in Python
345Writing Data to CSV Files with Python's CSV Module: A Practical Guide
250Parsing CSV Data into Dictionaries Using Python's csv.DictReader
200Challenge Solution: Building a Country Data Dictionary with DictReader
370Controlling CSV Parsing with Custom Fieldnames and Dialects in Python
481Reading and Writing to Multiple Files Simultaneously in Python
274Creating CSV Files with Python's csv.DictWriter: A Step-by-Step Guide
458Transforming Data with Python: Leveraging the zip Function
461Simultaneous Read/Write Operations on Text Files: Techniques & Cautions
497Challenge Solution: Implementing Invoice Number Parsing and Generation
441Implementing the record_invoice Function: Reading, Writing, File Pointers
475Enhancing File Handling: Utilizing seek and tell for Efficient Access
555Mastering seek and tell for File Pointer Manipulation in Python
504Optimizing File Operations: Improving the record_invoice Function
275Working with Text Files: Python's TextIO and Key Concepts Summarized
Introduction to Binary Files in Python: Understanding bytes and bytearray
665Hands-On Binary File Handling: Reading and Inverting a Bitmap Image
703Understanding Big Endian and Little Endian Byte Order in Computer Systems
201Decoding Binary Data: Extracting and Interpreting Bitmap File Information
606Extract, Read, and Modify Metadata: Comprehensive MP3 ID3 Tag Management
484Deep Dive into MP3 Metadata: Navigating and Using the ID3v2 Specification
438Hands-On Python: Decoding and Extracting Data from Binary MP3 ID3 Frames
700Complete Python Code Implementation for Reading and Writing MP3 ID3 Tags
612Mastering Image Extraction: A Step-by-Step Guide to Decoding MP3 APIC Frames
857Validate Your Code: Step-by-Step Testing of the read_id3 Program in Python
348Secure Your Downloads: Verify File Integrity with SHA-256 Hash Checksums
363Binary File Handling in Python: The Ultimate, Comprehensive, Practical Guide
Introduction to Python Modules, Functions, and Section Overview
205Exploring Turtle Graphics: Drawing Shapes and Patterns with Turtle Module
607Targeted Imports: Importing Specific Functions and Objects from Modules
240Understanding Python Namespaces: Global Scope and Variable Visibility
381Mastering Local Scope: Understanding Variables within Functions
340Exploring the Builtins Namespace: Accessing Python's Built-in Functions
465Deep Dive into Nested Functions: Understanding Function Definitions
220Understanding Enclosing Scope in Python: Accessing Outer Function Variables
204Free Variables and Namespace Optimization in Python: Behind the Scenes
192Modifying Free Variables: Understanding Variable Binding in Inner Scopes
444Namespace Dictionaries and Free Variable Behavior: An In-Depth Look
384Using the nonlocal Keyword: Modifying Variables in Enclosing Scopes
262Mastering the global Keyword: Modifying Global Variables from Inner Scopes
598Import Mechanisms and Global Namespace: Memory Usage and Optimization
704Iterating Over the Globals Dictionary: Copying for Safe Modification
150Understanding the Risks and Uses of 'import *' in Python Modules
263Controlling Module Execution Using 'if __name__ == '__main__':'
371Optimizing Python Code: Local Namespace Lookup for Functions
428Launching Web Pages: Utilizing the Python 'webbrowser' Module
349Introduction to Handling Dates and Times in Python Programming
205Mastering the datetime Module's Date Class: Formatting and Usage
673Using Timedelta Objects for Date and Time Calculations in Python
486Understanding the Time Class in Python's Datetime Module
932Deep Dive into Python's Datetime.Date, with Import Clarifications
393Navigating Aware and Naive Datetime Objects in Python Development
354Installing and Using the Zoneinfo Backport for Timezone Management
300Creating and Utilizing Timezone Objects in Python Applications
646Step-by-Step Solution for the Timezone Challenge in Python Coding
820Addressing Unexpected Daylight Saving Time Behavior in Python
554Best Practices for Datetime Arithmetic: Prioritizing UTC Operations
603Course Remaster Update: Access the Latest Python Programming Content Now
81Course Enhancements: An Overview of the Section Remastering
An Introduction to the Tkinter Module for GUI Development
749Introduction to the TkInter Pack Geometry Manager for Widget Layout
821Introduction to Using the TkInter Grid Geometry Manager in Python
778Building an Advanced GUI: A Step-by-Step Example - Part 1
1033Building an Advanced GUI: A Step-by-Step Example - Part 2
883Completing the Advanced GUI: A Step-by-Step Guide - Part 3
1088Developing a Simple Calculator GUI Layout: A Tkinter Challenge
897Introduction to Writing and Using Functions in Python Programming
914Exploring Python Functions Further: Variable Arguments, Default Values
727Python Functions Continued: Enhancements and File Output
603Creating a Parabola Drawing Function: Expanding Function Knowledge
865Variable Scope in Python Functions: Best Practices and Common Pitfalls
782Refining Drawing Function and Introducing Circles
771Improving Circle Drawing and a New Coding Challenge for Practice
619Setting Up the Basic Structure of the Blackjack Game in Tkinter
822Implementing Card Loading Functionality for the Blackjack Game
825Implementing the Card Dealing Mechanism in the Blackjack Game
530Understanding and Correctly Using Global Variables in Python
788Mastering the Global Keyword for Variable Scope in Python Functions
1018Completing the Game Logic: Testing the Blackjack Card Game
775Adding a New Game Feature: Tkinter Coding Challenge
1184Underscores in Python, import, and Name Space
1246Understanding Scope in Python Functions, LEGB, and Nonlocal Keyword
1045Exploring Function Nesting, Recursion and LEGB Rules
967Using Recursion with the OS and non local Module
817Non local keyword, and Understanding LEGB in Python
1027Introduction to Python OOP: Classes, Objects, and Programming Paradigms
901Python Class Instances: Constructors, Self Parameter, and Object Attributes
903Python Class Attributes: Shared Variables and Namespace Exploration
628Python Methods Part 1: Encapsulation and Bank Account Class Example
877Python Methods Part 2: Transaction Logs, Static Methods, and Class Design
859Python Non-Public Attributes, Name Mangling, and Underscore Conventions
713Python Docstrings: Usage, Raw Literals, and Documentation Best Practices
911Python Album Class: Combining Classes and Docstring Implementation
822Python Artist Class: Importing Albums and Handling Class Relationships
956Implementing the Revised Load_Data Algorithm in Python: A Step-by-Step Guide
882Mastering File Comparison Techniques and Algorithm Flowcharts in Python
706Implementing Revised Load_Data Algorithm: A Deep Dive into Python Functions
842Exploring Object-Oriented Programming: A Practical Python Example
749Mastering Python Properties: Getters, Setters, and Attribute Management
582Mastering Python Properties: Getters, Setters, and Attribute Management
362Python Object-Oriented Programming: Understanding and Using Getters and Setters
959Python OOP Deep Dive: Instance Variables, Class Attributes, and Properties
871Python Properties: Alternative Syntax and Decorators for Getters and Setters
306Mastering Inheritance in Object-Oriented Python: Creating and Extending Classes
900Python Subclassing: Extending Classes, Overriding, and Calling Super Methods
850Python Inheritance: Calling Superclass Methods to Extend Subclass Functionality
676Overriding Methods in Python: Changing Superclass Behavior in Subclasses
571Python OOP: Overriding Methods to Customize Subclass Functionality in Detail
977Practical Inheritance Challenge: Building a Vampire King Subclass in Python
698Polymorphism in Python: Understanding Dynamic Typing and Object Behavior
695Python's Duck Typing: Polymorphism Without Strict Inheritance Explained
426Mastering Composition in Python: Building Complex Objects from Simpler Classes
1137HTML Document Creation with Composition: Building Complex Structures in Python
679Python OOP: Implementing and Testing the HTML Document and Final Challenge
637Aggregation in Python OOP: A Weaker Form of Composition Explained and Applied
771Introduction to Databases
266Database Terminology
573A simple SQLite database browser
539Introduction to SQL – Creating tables
442Inserting data and displaying it
463UPDATE and DELETE
359The WHERE clause
296Querying and linked tables
376Primary keys
302Sorting the results
371Inner Joins
610Joining multiple tables
303Aliases
291Wildcards in the WHERE clause
335Views
427Modifying a View definition
537Introduction to SQL Functions
822Backing up a SQLite database
383Challenge Solutions
674Integrating Databases with Python: Leveraging the SQLite3 Module for Data
794Python Database Programming: Understanding Connections, Cursors, Transactions
1099Python Database Security: Understanding and Preventing SQL Injection Attacks
747Enhancing Database Interactions with Placeholders and Parameter Substitution
543Python Exception Handling: Mastering Try, Except, Else, and Finally Blocks
1065Python Exception Handling Challenge: Interactive Integer Division Program
831Advanced Exception Handling in Python: Best Practices and Considerations
889Preventing SQL Injection Attacks: Python Database Security Best Practices
760Understanding Python Stack Trace for Effective Debugging and Error Analysis
567Creating Custom Exceptions in Python: Enhancing Code Robustness & Clarity
954Implementing Transaction Rollback for Data Integrity in Python Database Apps
756Integrating Database Operations into Python Classes: A Practical Example
880GUI Database Editors: An Overview of Tools for Enhanced Database Management
93Mastering the IntelliJ IDEA Ultimate Edition Database Tool for Python Devs
875Troubleshooting Common Issues with the Community Edition Database Plugin
Reminder Use Python datetime.timezone Instead of pytz for Concrete Timezones
Enhancing the Account Class: Integrating Database Updates for Deposits/Withdrawa
822Mastering Timezones: Displaying Local and UTC Times from SQLite Databases
654Mastering SQLite Date and Time: strftime() for UTC Conversion in Queries
797Challenge: Store and Retrieve Original Timezone Data in SQLite with Python
809SQLite Timezone Challenges: Understanding and Avoiding Common Pitfalls
266Database Transactions: Implementing Rollback for Data Integrity in Python
998Building a Simple SQLite Database Browser with Python and Tkinter
1187Enhancing Your Database Browser: Adding Scrollbars to Tkinter Listboxes
588Understanding Python's Star Args (args) for Flexible Function Parameters
876Keyword Arguments Deep Dive: Mastering Python's kwargs for Flexibility
552Refining Keyword Argument Handling in Python: Addressing Potential Conflicts
1017Creating a Reusable Scrollable Listbox Class in Tkinter with Python
769Python and SQLite: Populating a Tkinter Listbox from a Database Query
604Linking DataListBoxes for Dynamic Updates in a Python Database Application
370Creating the DataListbox Class: A Reusable, Self-Populating Tkinter Widget
995Dynamically Linking Tkinter Listboxes for Enhanced Database-Driven Applications
694Finalising DataListbox: Linking DataListboxes for Dynamic Data Display
904Fixing Data Retrieval Bugs in Python Database ListBox Applications
1048Advanced Python Features: Generators, Comprehensions, Lambdas Overview
43Python Generators, Yield Keyword, and Memory Optimization Techniques
905Mastering Python Generators: next() Function and Iteration Explained
392Practical Generator Examples: Fibonacci Sequence, Pi Calculation in Python
1110Exploring File Systems with Python: Using the os.walk Generator
974Mastering File System Traversal: Advanced os.walk and fnmatch in Python
974Extracting Metadata: Reading MP3 ID3 Tags with Python Generators
1164Demystifying Python List Comprehensions: Syntax, Usage, and Examples
1092List Comprehensions vs. For Loops: Side Effects and Python Versions
495List Comprehension Challenge: Rewriting For Loops (Solution Included)
593Python Conditional Comprehensions: Filtering and If/Else Logic
714Advanced Conditional Expressions: FizzBuzz and Complex Filtering
708Python Comprehension Challenges: FizzBuzz, Locations, and Conversions
183Fizzbuzz List Comprehension: Step-by-Step Solution and Explanation
269Locations Challenge: List Comprehension to For Loop Conversion Guide
709Python Nested Comprehensions: Combining Lists and Iterations
710Python Nested Comprehensions Challenge: Times Tables Solution
898Measuring Python Code Performance with the timeit Module
710Advanced timeit Techniques: Setup Argument and Function Timing
742Timeit Challenge: Measuring Factorial Function Performance
833Timeit Module Challenge Solution and Explanation
650Introduction to the Python Map Function: Alternatives to Comprehensions
539Python Map Function Challenge and Solution: Hands-On Practice
429The Python Filter Function: Filtering Data with Functions and Comprehensions
497Understanding Python's reduce() Function: Examples and Alternatives
460Mastering any and all in Python: Combining with Comprehensions
642Understanding Python Named Tuples: Creation and Usage Guide
652Using any and all with Comprehensions - Code Examples
678Introduction to Lambda Expressions and Sorting with Key Functions
450Replacing Functions with Lambdas-Code Refactoring Examples
256Deep Dive into Lambda Expressions: Understanding Anonymous Functions in Python
395Mastering Python's Conditional Expressions: if/else in a Single Line of Code
566Practical Application: Writing Conditional Expressions - Challenge Exercise
155Combining Lambda Functions and Conditional Expressions for Efficient Sorting
279Building a Basic Calculator GUI in Tkinter: A Practical Use Case for Lambdas
358Addressing Lambda Limitations in Loops: Tkinter Calculator Button Commands
611Implementing Callbacks as Class Methods: State-Carrying Objects in Tkinter
468Subclassing Tkinter Frame for Custom Widgets: Creating a Reusable Component
438Security Risks of Using eval in Python: Demonstration and Explanation
231Mitigating Security Risks: How to Safely Use the eval Function in Python
235Improving Calculator Security: Preventing Arbitrary Code Execution in Tkinter
359Functions as First-Class Objects in Python: Practical Use in Dictionaries
402Demystifying Big O Notation: Understanding Algorithm Complexity in Detail
518Visualizing Algorithm Efficiency: Big O Notation Tables and Growth Charts
431Implementing Bubble Sort: A Practical Introduction to Sorting Algorithms
853Optimizing Bubble Sort: Reducing Comparisons for Improved Performance
323Understanding the Big O of Optimized Bubble Sort: A Deep Dive
287Further Optimizing Bubble Sort: Handling Nearly Sorted Data Efficiently
336Algorithm Performance: Analyzing Best, Worst, and Average Case Scenarios
180Big O Notation and Algorithm Optimization: A Comprehensive Summary
162You’ve either already got it or it’s FREE. Here’s the checklist:
A computer - Windows, Mac, and Linux are all supported. Setup and installation instructions are included for each platform.
Your enthusiasm to learn this go-to programming language. It’s a valuable lifetime skill which you can’t un-learn!
Everything else needed to start programming in Python is already included in the course.
Have a fundamental understanding of the Python programming language.
Have the skills and understanding of Python to confidently apply for Python programming jobs.
Acquire the pre-requisite Python skills to move into specific branches - Machine Learning, Data Science, etc..
Add the Python Object-Oriented Programming (OOP) skills to your résumé.
Understand how to create your own Python programs.
Learn Python from experienced professional software developers.
Understand both Python 2 and Python 3.
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