Course Overview
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!)
FAQ
FAQ area empty
Course curriculum
-
Welcome to the Python Masterclass: Meet Your Expert Instructors
122 Xem trước -
Course Enhancements: Updates, Larger Fonts, and Downloadable Slides
124 Xem trước -
Optimizing Video Playback: Achieving Crisp 1080p Resolution on Udemy
68 Xem trước -
Enhance Comprehension: Enabling and Using Hand-Edited English Subtitles
80 -
Mastering Python Support: Utilizing the Q&A for Effective Assistance
286 Xem trước -
Maximize Learning: The Importance of Hands-On Coding and Source Code Access
175
-
What is an IDE?
145 Xem trước -
Step-by-Step Python Installation for Windows 10 and 11: Download to Setup
152 -
Installing IntelliJ IDEA on Windows: A Quick and Easy Guide for Beginners
346 -
MacOS Python Installation: Downloading and Setting Up Python on Your Mac
203 -
Get Started with IntelliJ IDEA on macOS: Download and Installation Guide
281 Xem trước -
Installing Python on Linux (Ubuntu 22.04): Terminal Commands & Pip Setup
265 Xem trước -
Installing IntelliJ IDEA Community Edition on Linux: Step-by-Step Ubuntu Guide
225 -
Configure IntelliJ IDEA for Python: Essential Setup for Windows, Mac, Linux
748 -
Optimize IntelliJ IDEA: Customize Settings for Enhanced Python Development
260
-
Introduction to Python: What is Python and Why Learn It?
136 -
Creating Your First Python Program: The Classic "Hello World" Example
233 -
Mastering the Print Function in Python: Outputting Text and Calculations
435 -
Displaying a String: "My Hovercraft is Full of Eels
0 -
Python Calculations: Print the Result of 6 times 7
0 -
Working with Strings in Python: Concatenation, Quotes, and Input
443 -
Escape Characters in Python Strings: Newlines, Tabs, and Quotes (\n, \t)
456 -
Formatting Output with Tabs: Aligning Text in Python
0 -
Advanced String Manipulation: Handling Backslashes and Special Characters
229 -
Understanding Variables and Data Types in Python: Int, String, and More
445 -
Strong Typing in Python: Understanding Data Type Compatibility and Errors
290 -
Exploring Python's Numeric Data Types: Int, Float, and Complex Numbers
227 -
Performing Calculations in Python: Understanding Numeric Operators
332 -
What are Expressions in Python? Understanding Calculations and Values
317 -
Integer Division: Calculate Whole Number Results in Python
0 -
Mastering Operator Precedence and Understanding Order of Operations in Python
434 -
Comprehensive Guide to the str String Data Type: Sequence of Characters in Pytho
354 -
Unlocking Negative Indexing: Accessing String Characters from the End in Python
247 -
String Slicing: Extracting Substrings with Start, Stop, and Step Values in Pytho
596 -
Advanced String Slicing: How to Effectively Use Negative Numbers in Python Code
161 -
Mastering Step Slicing: Extracting Characters with Intervals from Python Strings
437 -
Backwards Slicing Techniques: Using Negative Steps to Reverse Python Strings
305 -
Solving the Slicing Challenge Plus Common Python Slicing Idioms Explained
314 -
Understanding String Operators: Concatenation, Multiplication, and 'in' in Pytho
508 -
Mastering String Replacement Fields: Enhancing Output with .format() in Python 3
663 -
Advanced String Formatting: Controlling Field Width, Alignment, and Precision
650 -
Exploring Python 3.6 f-strings: A Modern Approach to String Formatting
218 -
Understanding Python 2 String Interpolation: Legacy String Formatting Techniques
321 -
Recap of Python Fundamentals: Key Concepts from the Stepping into Python Section
59 -
Mastering the Basics of Python - Test Your Knowledge on Core Concepts
-
Getting Started with Code Blocks and Understanding Python Statements
613 -
Mastering if Statements: Controlling Program Flow with Conditional Logic
577 -
Enhancing Conditional Logic: Using elif for Multiple Condition Checks in Python
293 -
Leveraging the Debugger in IntelliJ or PyCharm for Efficient Python Code
620 -
Building a Simple Guessing Game: Practicing if, elif, and else in Python
299 -
Debugging the Guessing Game: Step-by-Step Execution with if, elif, and else
240 -
String Comparison: Applying 'if' with String Variables for Condition Evaluation
0 -
Basic Conditional Logic: Implementing if/elif/else for Value Comparison
0 -
Enhancing the Guessing Game: Implementing Logic for a Second Guess in Python
378 -
Conditional Operators: Comprehensive Guide to 'less than', 'equal to' in Python
511 -
Rewriting the Guessing Game: Optimizing Conditional Checks in Python Code
152 -
Mastering Complex Conditions: How to Effectively Use 'and', 'or' in Python
310 -
Understanding and Implementing Chained Comparisons
279 -
Understanding Boolean Expressions and the Concepts of True and False in Python
468 -
Exploring Truthy and Falsy Values in Python: Beyond Boolean True and False
270 -
Using 'in' and 'not in' Operators for Efficient Python String Searching
406 -
Practical Python: 'If' Conditionals Challenge for Real-World Scenarios
59 -
'If' Challenge Solution: Mastering Conditional Logic in Python Programs
202 -
Python For Loops Explained: Iterating Through Sequences and Strings
369 -
Debugging Python For Loops: Step-by-Step Execution and Variable Inspection
464 -
Extracting User Input Values with For Loops: A Practical Python Example
309 -
Find and Print Capital Letters: Python String Manipulation Exercise
0 -
Python Range Objects: Efficient Iteration with Start, Stop, and Step Values
188 -
Basic Number Printing with For Loops: A Beginner Python Exercise
0 -
Advanced Range Techniques: Mastering Start, Stop, and Step in Python Loops
265 -
Divisibility Check: Python For Loop and Step Value Practice Exercise
0 -
Nested For Loops in Python: Constructing Complex Iterative Structures
390 -
Controlling Loop Flow: The 'continue' Statement in Python For Loops
447 -
Terminating Loops: Using the 'break' Statement in Python For Loops
411 -
Variable Initialization and None in Python: Best Practices and Explanation
271 -
Controlling Program Execution: Understanding While Loops in Python
373 -
Advanced While Loop Techniques: Practical Applications and Considerations
368 -
Python While Loops: Using 'break' to Control Loop Termination Effectively
228 -
Controlled Iteration: Using 'break' with a Divisibility Condition
0 -
Selective Iteration: Using 'continue' to Skip Specific Numbers in Python
0 -
Generating Random Numbers in Python: Exploring the 'random' Module and Import
566 -
While Loop Challenge Solution: Building an Interactive Guessing Game in Python
326 -
Binary Search Algorithm Explained: Efficient Number Guessing in Python
319 -
Implementing a High-Low Guessing Game: A Practical Python Project
520 -
Completing the Hi-Lo Game: 'pass' Statement and Python Code Structure
256 -
Thoroughly Testing the Hi-Lo Game: Ensuring Robustness and Correctness
398 -
Python Augmented Assignment: Efficient In-Place Operations Explained
462 -
Multiplication Through Repeated Addition: Augmented Assignment in Python
0 -
PEP 8: Adhering to the Python Style Guide for Readable and Maintainable Code
509 -
Refactoring Python Code: Improving Structure and Readability Safely
211 -
Python Loop Control: Mastering the ELSE Clause in FOR Loops
321 -
Mastering 'else' in Python Loops: Hi-Lo Game Enhancement
306 -
Debugging in PyCharm & IntelliJ: Conditional Breakpoints
283 -
Practical Python: Using 'else' with Loops in Game Development
108 -
Python Flow Control Mastery: Section Review and Coding Task
199 -
Solving the Python Menu Challenge: Step-by-Step Code Solution
230 -
Optimizing Python Code: Menu Challenge Refactoring Solution
295 -
Advanced Python Loop Control: Replacing 'while True'
107 -
Mastering Python Flow Control: If/Else, For/While Loops Quiz
-
Sequence Types in Python: Lists, Tuples, and Ranges
175 -
Python Lists: Creating, Indexing, and Slicing Lists
264 -
Understanding Immutable Objects in Python: Int, Float, Bool
390 -
Python Mutable Objects: Lists, Dictionaries, and Sets
279 -
List Aliasing: Multiple Names for the Same Python List
204 -
Python Sequence Operations: Min, Max, Len, and Count
284 -
Python Mutable Sequence Operations: Append and More
221 -
Adding Items to a List with Append: Python By Example
461 -
Python Coding Challenge Solution: Adding Menu Options
127 -
Python List Iteration: Efficient Looping with Enumerate
252 -
Mastering Python's Enumerate Function: Indexes and Values
268 -
Python Code Refactoring: Dynamic Menu with List Comprehension
502 -
Flower and Shrub List Separator
0 -
Python List Manipulation: Removing Items with .remove()
309 -
Mastering List Sorting in Python: Sort() vs. Sorted()
268 -
Python's Built-in Functions: A Comprehensive Overview
227 -
Python List Sorting: Mastering the sorted() Function
597 -
Case-Insensitive String Sorting in Python: str.casefold()
280 -
Creating Python Lists: Literals, Concatenation, and More
556 -
Python List Slicing: Replacing Subsets of List Elements
354 -
Python List Modification: Safely Deleting Items
449 -
Removing List Values Safely: Handling Ordered Data
173 -
Python List Processing: Removing High Values Efficiently
392 -
Python Testing Best Practices: Edge Cases and Corner Cases
200 -
Thorough Python Code Testing: A Practical Demonstration
227 -
Reverse Iteration: Removing List Items from the End
354 -
Reverse Iteration in Python: Using the reversed() Function
304 -
Algorithm Performance in Python: Comparing Deletion Methods
538 -
Python Lists: Quick Recap of Key Concepts and Techniques
170 -
Nested Lists in Python: Structure, Access, and PEP 8 Style
553 -
Processing Nested Lists in Python: A Practical Example
282 -
Python Challenge Solution: Removing 'spam' from Nested Lists
216 -
Python Function Signatures: Understanding Parameters
215 -
Python's print() Function Revisited: sep and end
383 -
String Manipulation in Python: The join() Method
464 -
String Manipulation in Python: The split() Method
549 -
Converting Strings to Integers in Python: Mini-Challenge Solution
343 -
The Magical Adder
0 -
Introduction to Tuples: Python's Immutable Sequences
285 -
Understanding Immutability: Working with Python Tuples
441 -
Tuple Unpacking in Python: Assigning Multiple Variables
389 -
Practical Tuple Unpacking: Real-World Python Examples
246 -
More on Unpacking in Python: Sequences and Variables
369 -
Nested Data Structures: Combining Tuples and Lists in Python
311 -
Python Tuple Unpacking Challenge: Efficient Code Solution
190 -
Delving into Nested Structures: Practical Tuple Applications
224 -
Mastering Complex Data: A Comprehensive Guide to Nested Structures
337 -
Advanced Python List Navigation: Mastering Multi-Level Indexing
260 -
Practical Application of Nested Data Structure Indexing in Python
0 -
Jukebox Project Preview: Interactive Menu System in Python
145 -
Project Setup: Importing Data and Managing Dependencies in Python
305 -
Building the Jukebox: Dynamic Menu Creation and User Input Handling
424 -
Understanding Constants in Python: Best Practices for Code Clarity
533 -
Completing the Python Jukebox: Song Selection and Playback Logic
337 -
Enhance Jukebox: Navigating Back to Main Menu Without Song Selection
42 -
Jukebox Challenge Resolved: Enabling Seamless Menu Navigation
243 -
Lists, Tuples, and Jukebox: Key Takeaways from the Section
167
-
Getting Started with Functions: A Practical Overview
158 -
Constructing Custom Functions: Syntax, Structure, and Return Values
335 -
Analyzing Program Execution: Function Calls and Debugging Techniques
265 -
Function Parameters and Arguments: Passing Data and Understanding Scope
280 -
Debugging Parameterized Functions: Step-by-Step Execution Analysis
479 -
Creating a Palindrome Checker: Function Design and String Manipulation
433 -
Palindrome Challenge: Enhancing Case-Insensitive String Comparison
179 -
Sentence Palindrome Challenge: Handling Punctuation and Spaces
328 -
Advanced Function Design: Calling Functions Within Functions
125 -
Return Values in Python: Explicit and Implicit Function Outputs
484 -
Get_integer Input Validation: Error Handling and User Messaging
255 -
Even or Odd Numbers within a Specified Range
0 -
Understanding None: Python's Default Return Value for Functions
178 -
Designing Action-Oriented Functions: Banner Printing Example
478 -
Exception Handling: Managing Invalid Arguments with ValueError
442 -
Function Parameter Customization: Setting Width for Enhanced Flexibility
126 -
Enhancing Function Usability: Implementing Default Parameter Values
154 -
Improving Function Calls with Keyword Arguments for Clarity
381 -
Documenting Functions: Creating Clear and Informative Docstrings
363 -
Generating Function Documentation: Writing and Using Docstrings
470 -
Docstring Best Practices and Tools: Achieving Professional Code Quality
373 -
Docstring Challenge: Solutions and Best Practices for Documentation
-
Introduction to Fibonacci Numbers: Mathematical Concepts and Sequences
232 -
Implementing a Fibonacci Sequence Generator: A Practical Function Example
487 -
Type Hints and Annotations: Enhancing Code Readability and Clarity
436 -
Combining Annotations and Default Values in Python Function Parameters
212 -
Documenting the banner_text Function: A Comprehensive Docstring Example
-
Historical Context: Teletypewriters, ANSI Escape Codes, and Terminals
334 -
Enhancing Terminal Output: Implementing Text Coloring and Effects
470 -
Testing Python Programs: Simulating User Execution Environments
355 -
Installing the Colorama Package
489 -
Step-by-Step Guide to Activating a Virtual Environment in Python
361 -
Creating Automated Tests for the HiLo Game Using Python Functions
599 -
Analyzing Binary Search Efficiency: Counting Correct Guesses in HiLo
287 -
Implement the Fizz Buzz Game Logic Using a Python Function
0 -
Building an Interactive Fizz Buzz Game: Player vs Computer in Python
242 -
Developing a Complete Fizz Buzz Game: Solution and Implementation Details
386 -
Creating a Python Function to Calculate Factorials with Docstrings
0 -
Mastering Variable Arguments in Python: A Deep Dive into *args Unpacking
458 -
Enhancing the colour_print Function with Multiple ANSI Escape Sequences
329 -
Understanding Python Function Parameters: Ordering and Usage Rules
138 -
Practical Application of Python Parameter Types: A Hands-On Example
406 -
Summation Function: Utilizing Variable Arguments (*args) in Python
0 -
Comprehensive Summary of Python Functions: Key Concepts and Best
215
-
Introduction to Python Dictionaries and Sets: Core Data Structures
94 -
Python Dictionary Fundamentals: Understanding Key-Value Data Storage
499 -
Iterating Over Dictionaries in Python: Keys, Values, and Items Method
398 -
Adding Items to a Dictionary in Python: Modifying Dictionary Contents
246 -
Modifying Dictionary Values in Python: Updating and Replacing Entries
218 -
Deleting Dictionary Items in Python: Using del and pop Methods
428 -
Efficiently Using in with Python Dictionaries: Checking for Key Existence
478 -
Solution: Building a Menu System with Python Dictionaries (Challenge)
512 -
Integrating Lists and Dictionaries in Python: A Practical Example
-
Enhancing the Computer Builder: Adding Dictionary Item Functionality
299 -
Creating a Smart Fridge Application: Leveraging Multiple Dictionaries
263 -
Meal Planner in Python: Displaying and Selecting Recipes from a Dictionary
559 -
Combining Python Dictionaries: Accessing Nested Data Structures
345 -
Pantry Check: Validating Recipe Ingredients Against Available Stock
263 -
Recipe Data Structures: Dictionaries vs. Tuples for Quantity Tracking
319 -
Implementing Quantity Checks in Python Dictionaries for Inventory Management
384 -
Enhancing the Meal Planner: Building a Dynamic Shopping List (Challenge)
411 -
Refactoring Code: Adapting to Data Structure Changes in Python Programs
342 -
Optimizing Dictionary Updates: Introducing the setdefault Method in Python
604 -
Counting Character Occurrences in a String: Building a Frequency Dictionary
0 -
Integrating External APIs: A Practical Mobile Phone Data Synchronization Demo
487 -
Exploring the Python dict API: A Comprehensive Documentation Overview
518 -
Remaining Dictionary Methods: fromkeys, keys, and values in Python
277 -
Dictionary Manipulation: Utilizing the update Method for Efficient Merging
388 -
Working with Dictionary Views: Accessing Dynamic Values using values Method
486 -
Understanding References and Mutable Objects in Python Dictionaries
339 -
Step-by-Step Demonstration of Shallow Copying in Python Dictionaries
346 -
Illustrating Shallow Copy: A Detailed Walkthrough of Dictionary References
227 -
Contrasting Deep and Shallow Copies: Implications for Mutable Dictionary Values
311 -
Implementing a Custom Deep Copy Function for Python Dictionaries (Challenge)
518 -
Understanding Hash Functions and Hash Values in Python
476 -
Implementing a Basic Hashing Function: A Practical Example
525 -
Practical Implementation of Hash Tables in Python Explained
417 -
Creating a Simple Dictionary: Hash Table Implementation
307 -
Securing Data: Exploring Hash Functions in Cybersecurity
229 -
Python's hashlib Module: Secure Hashes and Message Digests
731 -
Introduction to Sets: Unordered Collections of Unique Items
372 -
Working with Python Sets: Basic Operations and Examples
288 -
Unordered Nature of Sets: Implications and Considerations
296 -
Efficient Membership Testing: Leveraging Python Sets
489 -
Optimizing Code with Sets: Fast Membership Testing
435 -
Modifying Sets in Python: Adding Items with the add() Method
342 -
Removing Duplicates from Data: Leveraging the Power of Python Sets
381 -
Removing Elements: Comprehensive Guide to Python's Set Methods
497 -
Safely Removing Items from Sets: Mastering Python's discard Method
324 -
Efficient Set Modification: Mastering the remove Method
627 -
Arbitrary Element Removal: Understanding pop in Python Sets
281 -
Combining Sets: Comprehensive Guide to Set Union in Python
332 -
Real-World Applications: Implementing Set Union in Python
259 -
Modifying Sets Efficiently: Using the Union Update Method
177 -
Methods Versus Operators: Advantages of Methods with Iterables
303 -
Finding Common Elements: Mastering Set Intersection in Python
335 -
Identifying Overlapping Data: Practical Use of Set Intersection
356 -
Preposition Intersection
0 -
Exclusive Elements: Understanding Set Difference in Python
139 -
Practical Set Operations: Applying Set Difference in Real Scenarios
178 -
Finding Unique Items Using Set Difference
0 -
Unique Elements Combined: Exploring Set Symmetric Difference
366 -
Exploring Relationships: Subsets and Supersets in Python Sets
184 -
Checking Set Relationships: Implementing Subset and Superset
407 -
Python Sets: Select Job Candidates with Superset and Proper Superset
485 -
Python Dictionary & Set Mastery: Comprehensive Review and Recap
-
Python Input and Output (I/O) Fundamentals: An Introductory Overview
103 -
Understanding Computer File Systems: Files, Directories, and Paths
638 -
Command Line Navigation: Mastering the Terminal or Command Prompt
366 -
Demystifying File Paths: Absolute vs. Relative and Cross-Platform
703 -
Defining and Working with Text Files: Formats, Uses and Examples
147 -
Reading Data from Text Files: A Comprehensive Python Approach
638 -
Python's with Statement: Simplifying File Handling for Beginners
191 -
Python's with Statement: Simplifying File Handling for Beginners
503 -
Mastering Python's String strip Methods: strip, lstrip, rstrip
418 -
String Manipulation: Using removeprefix and removesuffix (Python 3.9+)
312 -
Parsing Text File Data: A Step-by-Step Guide for Python Developers
353 -
Efficient Text Data Handling: Organizing and Structuring Information
389 -
Challenge Solution: Retrieving and Displaying a Country's Capital City
358 -
Efficient Data Retrieval: Implementing Multiple Keys for Dictionary Values
203 -
Writing to Text Files: A Comprehensive Guide to Printing Output Data
275 -
File Handling in Python: Writing Text Data Using the write Method
544 -
Understanding Python File Modes: r, w, x, a, r+, and w+
298 -
A Deep Dive into Character Encodings: ASCII, EBCDIC and Unicode
393 -
Working with Unicode Strings and Encodings in Python (UTF-8)
246 -
Identifying and Handling File Encodings in Python: A Practical Guide
621 -
Data Serialization with JSON: Encoding and Decoding in Python
457 -
Understanding JSON Data Types and Limitations in Python Serialization
368 -
Parsing Real-World JSON Data from a File: A Temperature Anomaly Example
464 -
Downloading and Parsing JSON Data from the Internet Using Python
483 -
Introduction to the CSV File Format: Structure, Uses, and Standards
407 -
Efficient CSV Data Handling: Reading and Parsing with Python's CSV Module
472 -
Mastering CSV Quoting: Handling Special Characters and Data Types in Python
338 -
Understanding and Utilizing CSV Dialects and Sniffer in Python
401 -
Exploring the CSV Dialect Object and Its Attributes in Python
345 -
Writing Data to CSV Files with Python's CSV Module: A Practical Guide
250 -
Parsing CSV Data into Dictionaries Using Python's csv.DictReader
200 -
Challenge Solution: Building a Country Data Dictionary with DictReader
370 -
Controlling CSV Parsing with Custom Fieldnames and Dialects in Python
481 -
Reading and Writing to Multiple Files Simultaneously in Python
274 -
Creating CSV Files with Python's csv.DictWriter: A Step-by-Step Guide
458 -
Transforming Data with Python: Leveraging the zip Function
461 -
Simultaneous Read/Write Operations on Text Files: Techniques & Cautions
497 -
Challenge Solution: Implementing Invoice Number Parsing and Generation
441 -
Implementing the record_invoice Function: Reading, Writing, File Pointers
475 -
Enhancing File Handling: Utilizing seek and tell for Efficient Access
555 -
Mastering seek and tell for File Pointer Manipulation in Python
504 -
Optimizing File Operations: Improving the record_invoice Function
275 -
Working with Text Files: Python's TextIO and Key Concepts Summarized
-
Introduction to Binary Files in Python: Understanding bytes and bytearray
665 -
Hands-On Binary File Handling: Reading and Inverting a Bitmap Image
703 -
Understanding Big Endian and Little Endian Byte Order in Computer Systems
201 -
Decoding Binary Data: Extracting and Interpreting Bitmap File Information
606 -
Extract, Read, and Modify Metadata: Comprehensive MP3 ID3 Tag Management
484 -
Deep Dive into MP3 Metadata: Navigating and Using the ID3v2 Specification
438 -
Hands-On Python: Decoding and Extracting Data from Binary MP3 ID3 Frames
700 -
Complete Python Code Implementation for Reading and Writing MP3 ID3 Tags
612 -
Mastering Image Extraction: A Step-by-Step Guide to Decoding MP3 APIC Frames
857 -
Validate Your Code: Step-by-Step Testing of the read_id3 Program in Python
348 -
Secure Your Downloads: Verify File Integrity with SHA-256 Hash Checksums
363 -
Binary File Handling in Python: The Ultimate, Comprehensive, Practical Guide
-
Introduction to Python Modules, Functions, and Section Overview
205 -
Exploring Turtle Graphics: Drawing Shapes and Patterns with Turtle Module
607 -
Targeted Imports: Importing Specific Functions and Objects from Modules
240 -
Understanding Python Namespaces: Global Scope and Variable Visibility
381 -
Mastering Local Scope: Understanding Variables within Functions
340 -
Exploring the Builtins Namespace: Accessing Python's Built-in Functions
465 -
Deep Dive into Nested Functions: Understanding Function Definitions
220 -
Understanding Enclosing Scope in Python: Accessing Outer Function Variables
204 -
Free Variables and Namespace Optimization in Python: Behind the Scenes
192 -
Modifying Free Variables: Understanding Variable Binding in Inner Scopes
444 -
Namespace Dictionaries and Free Variable Behavior: An In-Depth Look
384 -
Using the nonlocal Keyword: Modifying Variables in Enclosing Scopes
262 -
Mastering the global Keyword: Modifying Global Variables from Inner Scopes
598 -
Import Mechanisms and Global Namespace: Memory Usage and Optimization
704 -
Iterating Over the Globals Dictionary: Copying for Safe Modification
150 -
Understanding the Risks and Uses of 'import *' in Python Modules
263 -
Controlling Module Execution Using 'if __name__ == '__main__':'
371 -
Optimizing Python Code: Local Namespace Lookup for Functions
428 -
Launching Web Pages: Utilizing the Python 'webbrowser' Module
349
-
Introduction to Handling Dates and Times in Python Programming
205 -
Mastering the datetime Module's Date Class: Formatting and Usage
673 -
Using Timedelta Objects for Date and Time Calculations in Python
486 -
Understanding the Time Class in Python's Datetime Module
932 -
Deep Dive into Python's Datetime.Date, with Import Clarifications
393 -
Navigating Aware and Naive Datetime Objects in Python Development
354 -
Installing and Using the Zoneinfo Backport for Timezone Management
300 -
Creating and Utilizing Timezone Objects in Python Applications
646 -
Step-by-Step Solution for the Timezone Challenge in Python Coding
820 -
Addressing Unexpected Daylight Saving Time Behavior in Python
554 -
Best Practices for Datetime Arithmetic: Prioritizing UTC Operations
603 -
Course Remaster Update: Access the Latest Python Programming Content Now
81
-
Course Enhancements: An Overview of the Section Remastering
-
An Introduction to the Tkinter Module for GUI Development
749 -
Introduction to the TkInter Pack Geometry Manager for Widget Layout
821 -
Introduction to Using the TkInter Grid Geometry Manager in Python
778 -
Building an Advanced GUI: A Step-by-Step Example - Part 1
1033 -
Building an Advanced GUI: A Step-by-Step Example - Part 2
883 -
Completing the Advanced GUI: A Step-by-Step Guide - Part 3
1088 -
Developing a Simple Calculator GUI Layout: A Tkinter Challenge
897 -
Introduction to Writing and Using Functions in Python Programming
914 -
Exploring Python Functions Further: Variable Arguments, Default Values
727 -
Python Functions Continued: Enhancements and File Output
603 -
Creating a Parabola Drawing Function: Expanding Function Knowledge
865 -
Variable Scope in Python Functions: Best Practices and Common Pitfalls
782 -
Refining Drawing Function and Introducing Circles
771 -
Improving Circle Drawing and a New Coding Challenge for Practice
619 -
Setting Up the Basic Structure of the Blackjack Game in Tkinter
822 -
Implementing Card Loading Functionality for the Blackjack Game
825 -
Implementing the Card Dealing Mechanism in the Blackjack Game
530 -
Understanding and Correctly Using Global Variables in Python
788 -
Mastering the Global Keyword for Variable Scope in Python Functions
1018 -
Completing the Game Logic: Testing the Blackjack Card Game
775 -
Adding a New Game Feature: Tkinter Coding Challenge
1184 -
Underscores in Python, import, and Name Space
1246 -
Understanding Scope in Python Functions, LEGB, and Nonlocal Keyword
1045 -
Exploring Function Nesting, Recursion and LEGB Rules
967 -
Using Recursion with the OS and non local Module
817 -
Non local keyword, and Understanding LEGB in Python
1027
-
Introduction to Python OOP: Classes, Objects, and Programming Paradigms
901 -
Python Class Instances: Constructors, Self Parameter, and Object Attributes
903 -
Python Class Attributes: Shared Variables and Namespace Exploration
628 -
Python Methods Part 1: Encapsulation and Bank Account Class Example
877 -
Python Methods Part 2: Transaction Logs, Static Methods, and Class Design
859 -
Python Non-Public Attributes, Name Mangling, and Underscore Conventions
713 -
Python Docstrings: Usage, Raw Literals, and Documentation Best Practices
911 -
Python Album Class: Combining Classes and Docstring Implementation
822 -
Python Artist Class: Importing Albums and Handling Class Relationships
956 -
Implementing the Revised Load_Data Algorithm in Python: A Step-by-Step Guide
882 -
Mastering File Comparison Techniques and Algorithm Flowcharts in Python
706 -
Implementing Revised Load_Data Algorithm: A Deep Dive into Python Functions
842 -
Exploring Object-Oriented Programming: A Practical Python Example
749 -
Mastering Python Properties: Getters, Setters, and Attribute Management
582 -
Mastering Python Properties: Getters, Setters, and Attribute Management
362 -
Python Object-Oriented Programming: Understanding and Using Getters and Setters
959 -
Python OOP Deep Dive: Instance Variables, Class Attributes, and Properties
871 -
Python Properties: Alternative Syntax and Decorators for Getters and Setters
306 -
Mastering Inheritance in Object-Oriented Python: Creating and Extending Classes
900 -
Python Subclassing: Extending Classes, Overriding, and Calling Super Methods
850 -
Python Inheritance: Calling Superclass Methods to Extend Subclass Functionality
676 -
Overriding Methods in Python: Changing Superclass Behavior in Subclasses
571 -
Python OOP: Overriding Methods to Customize Subclass Functionality in Detail
977 -
Practical Inheritance Challenge: Building a Vampire King Subclass in Python
698 -
Polymorphism in Python: Understanding Dynamic Typing and Object Behavior
695 -
Python's Duck Typing: Polymorphism Without Strict Inheritance Explained
426 -
Mastering Composition in Python: Building Complex Objects from Simpler Classes
1137 -
HTML Document Creation with Composition: Building Complex Structures in Python
679 -
Python OOP: Implementing and Testing the HTML Document and Final Challenge
637 -
Aggregation in Python OOP: A Weaker Form of Composition Explained and Applied
771
-
Introduction to Databases
266 -
Database Terminology
573 -
A simple SQLite database browser
539 -
Introduction to SQL – Creating tables
442 -
Inserting data and displaying it
463 -
UPDATE and DELETE
359 -
The WHERE clause
296 -
Querying and linked tables
376 -
Primary keys
302 -
Sorting the results
371 -
Inner Joins
610 -
Joining multiple tables
303 -
Aliases
291 -
Wildcards in the WHERE clause
335 -
Views
427 -
Modifying a View definition
537 -
Introduction to SQL Functions
822 -
Backing up a SQLite database
383 -
Challenge Solutions
674 -
Integrating Databases with Python: Leveraging the SQLite3 Module for Data
794 -
Python Database Programming: Understanding Connections, Cursors, Transactions
1099 -
Python Database Security: Understanding and Preventing SQL Injection Attacks
747 -
Enhancing Database Interactions with Placeholders and Parameter Substitution
543 -
Python Exception Handling: Mastering Try, Except, Else, and Finally Blocks
1065 -
Python Exception Handling Challenge: Interactive Integer Division Program
831 -
Advanced Exception Handling in Python: Best Practices and Considerations
889 -
Preventing SQL Injection Attacks: Python Database Security Best Practices
760 -
Understanding Python Stack Trace for Effective Debugging and Error Analysis
567 -
Creating Custom Exceptions in Python: Enhancing Code Robustness & Clarity
954 -
Implementing Transaction Rollback for Data Integrity in Python Database Apps
756 -
Integrating Database Operations into Python Classes: A Practical Example
880 -
GUI Database Editors: An Overview of Tools for Enhanced Database Management
93 -
Mastering the IntelliJ IDEA Ultimate Edition Database Tool for Python Devs
875 -
Troubleshooting 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
822 -
Mastering Timezones: Displaying Local and UTC Times from SQLite Databases
654 -
Mastering SQLite Date and Time: strftime() for UTC Conversion in Queries
797 -
Challenge: Store and Retrieve Original Timezone Data in SQLite with Python
809 -
SQLite Timezone Challenges: Understanding and Avoiding Common Pitfalls
266 -
Database Transactions: Implementing Rollback for Data Integrity in Python
998 -
Building a Simple SQLite Database Browser with Python and Tkinter
1187 -
Enhancing Your Database Browser: Adding Scrollbars to Tkinter Listboxes
588 -
Understanding Python's Star Args (args) for Flexible Function Parameters
876 -
Keyword Arguments Deep Dive: Mastering Python's kwargs for Flexibility
552 -
Refining Keyword Argument Handling in Python: Addressing Potential Conflicts
1017 -
Creating a Reusable Scrollable Listbox Class in Tkinter with Python
769 -
Python and SQLite: Populating a Tkinter Listbox from a Database Query
604 -
Linking DataListBoxes for Dynamic Updates in a Python Database Application
370 -
Creating the DataListbox Class: A Reusable, Self-Populating Tkinter Widget
995 -
Dynamically Linking Tkinter Listboxes for Enhanced Database-Driven Applications
694 -
Finalising DataListbox: Linking DataListboxes for Dynamic Data Display
904 -
Fixing Data Retrieval Bugs in Python Database ListBox Applications
1048
-
Advanced Python Features: Generators, Comprehensions, Lambdas Overview
43 -
Python Generators, Yield Keyword, and Memory Optimization Techniques
905 -
Mastering Python Generators: next() Function and Iteration Explained
392 -
Practical Generator Examples: Fibonacci Sequence, Pi Calculation in Python
1110 -
Exploring File Systems with Python: Using the os.walk Generator
974 -
Mastering File System Traversal: Advanced os.walk and fnmatch in Python
974 -
Extracting Metadata: Reading MP3 ID3 Tags with Python Generators
1164 -
Demystifying Python List Comprehensions: Syntax, Usage, and Examples
1092 -
List Comprehensions vs. For Loops: Side Effects and Python Versions
495 -
List Comprehension Challenge: Rewriting For Loops (Solution Included)
593 -
Python Conditional Comprehensions: Filtering and If/Else Logic
714 -
Advanced Conditional Expressions: FizzBuzz and Complex Filtering
708 -
Python Comprehension Challenges: FizzBuzz, Locations, and Conversions
183 -
Fizzbuzz List Comprehension: Step-by-Step Solution and Explanation
269 -
Locations Challenge: List Comprehension to For Loop Conversion Guide
709 -
Python Nested Comprehensions: Combining Lists and Iterations
710 -
Python Nested Comprehensions Challenge: Times Tables Solution
898 -
Measuring Python Code Performance with the timeit Module
710 -
Advanced timeit Techniques: Setup Argument and Function Timing
742 -
Timeit Challenge: Measuring Factorial Function Performance
833 -
Timeit Module Challenge Solution and Explanation
650 -
Introduction to the Python Map Function: Alternatives to Comprehensions
539 -
Python Map Function Challenge and Solution: Hands-On Practice
429 -
The Python Filter Function: Filtering Data with Functions and Comprehensions
497 -
Understanding Python's reduce() Function: Examples and Alternatives
460 -
Mastering any and all in Python: Combining with Comprehensions
642 -
Understanding Python Named Tuples: Creation and Usage Guide
652 -
Using any and all with Comprehensions - Code Examples
678 -
Introduction to Lambda Expressions and Sorting with Key Functions
450 -
Replacing Functions with Lambdas-Code Refactoring Examples
256 -
Deep Dive into Lambda Expressions: Understanding Anonymous Functions in Python
395 -
Mastering Python's Conditional Expressions: if/else in a Single Line of Code
566 -
Practical Application: Writing Conditional Expressions - Challenge Exercise
155 -
Combining Lambda Functions and Conditional Expressions for Efficient Sorting
279 -
Building a Basic Calculator GUI in Tkinter: A Practical Use Case for Lambdas
358 -
Addressing Lambda Limitations in Loops: Tkinter Calculator Button Commands
611 -
Implementing Callbacks as Class Methods: State-Carrying Objects in Tkinter
468 -
Subclassing Tkinter Frame for Custom Widgets: Creating a Reusable Component
438 -
Security Risks of Using eval in Python: Demonstration and Explanation
231 -
Mitigating Security Risks: How to Safely Use the eval Function in Python
235 -
Improving Calculator Security: Preventing Arbitrary Code Execution in Tkinter
359 -
Functions as First-Class Objects in Python: Practical Use in Dictionaries
402
-
Demystifying Big O Notation: Understanding Algorithm Complexity in Detail
518 -
Visualizing Algorithm Efficiency: Big O Notation Tables and Growth Charts
431 -
Implementing Bubble Sort: A Practical Introduction to Sorting Algorithms
853 -
Optimizing Bubble Sort: Reducing Comparisons for Improved Performance
323 -
Understanding the Big O of Optimized Bubble Sort: A Deep Dive
287 -
Further Optimizing Bubble Sort: Handling Nearly Sorted Data Efficiently
336 -
Algorithm Performance: Analyzing Best, Worst, and Average Case Scenarios
180 -
Big O Notation and Algorithm Optimization: A Comprehensive Summary
162
Requirment
-
You’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.
Outcomes
-
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.
0 Student
2 Courses
0 review