Getting Started
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Introduction (5:37)
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How to Use This Course (10:36)
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Installing Python (3:18)
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Installing Powershell (4:18)
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Python Virtual Environments (6:32)
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Visual Studio Code (5:43)
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Hello World (4:11)
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The Shebang or Hashbang (4:08)
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Where to Find the Source Code (2:11)
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VS Code Tips (5:42)
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Variables (5:36)
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An Interactive Program (5:52)
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Builtin Functions (5:17)
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Numeric Variables (7:17)
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Numeric Expressions (5:16)
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Python Types (5:44)
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Peforming Calculations (9:06)
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Converting Temperatures (8:43)
Loops and Conditions
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A Program Inspired By WarGames (1:33)
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Boolean Variables (6:13)
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The If Statement (8:25)
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If Else (2:12)
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Constants (6:51)
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If Else If (7:20)
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Comparison Operators (8:13)
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Fridge Exercise (4:28)
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Fridge Solution (9:03)
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Fridge Improvements (8:37)
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For Loops (5:23)
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Ranges (4:46)
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Indentation (4:23)
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Break (5:42)
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Continue (2:07)
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Password Exercise (2:01)
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Password Solution (6:04)
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Boolean Operators (6:37)
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Boolean Operators Exercise (2:11)
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Boolean Operators First Solution (12:29)
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Boolean Operators Second Solution (4:31)
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While Loops (3:56)
Functions
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Your First Function (7:20)
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Multiple Functions (6:24)
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Function Arguments (5:23)
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The Identity Function (6:19)
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Changing Parameters (4:48)
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Return Values (6:52)
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Multiple Arguments (5:46)
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Factorial Exercise (4:50)
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Factorial Solution (5:49)
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Default Arguments (3:53)
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Keyword Arguments (3:39)
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Variable Length Arguments (4:59)
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Variable Length Keyword Arguments (7:41)
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Arguments and Parameters Summary (4:45)
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Arguments Exercise Solution (3:46)
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Multiple Return Values (4:25)
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BMI Exercise Solution (3:10)
Containers
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Tuples (5:26)
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Packing and Unpacking Tuples (7:21)
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Tuple Slicing (5:32)
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Tuple Functions and Operators (7:54)
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Lists (4:18)
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Joining Lists (9:14)
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Modifying Lists (9:18)
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Extended Slicing (8:25)
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Inserting and Extending Lists (2:41)
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Removing List Items (4:36)
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List Comprehensions (7:51)
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List Comprehension Conditions (4:53)
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List Comprehension If Else (3:23)
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List Database Exercise (4:12)
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Database Exercise Tips (5:06)
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Database Exercise Functions (7:20)
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Completing the Database (7:20)
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About Data Validation (3:05)
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Sets (7:00)
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Adding To and Updating Sets (3:41)
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Removing Items from Sets (5:07)
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Set Union and Intersection (4:59)
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Difference Update (4:22)
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Set Exercise (1:16)
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Set Exercise Solution (5:02)
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Dictionaries (4:21)
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Adding Items to Dictionaries (3:46)
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Iterating Over Dictionaries (4:48)
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Dictionary Views (4:50)
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Deleting Dictionary Items (2:39)
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The Dictionary Get Method (2:39)
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Default Dictionaries (4:08)
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Dictionary Comprehensions (4:43)
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Dictionary Exercise (1:22)
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Dictionary Exercise Solution (7:17)
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Casefold and None (6:23)
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Enumerate and Zip (3:38)
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Improving the Dictionary Exercise Solution (3:58)
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Hashing Algorithms (8:00)
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Container Summary (5:23)
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Time Complexity (7:43)
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Lists of Lists (3:30)
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Iterating Over Lists of Lists (5:50)
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Dictionaries of Lists (4:12)
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Dictionaries of Sets Exercise (6:59)
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Dictionaries of Sets Solution Part 1 (4:33)
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Dictionaries of Sets Solution Part 2 (7:39)
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Global Variables (4:33)
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Random Items (1:55)
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Modular Arithmetic (5:07)
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Containers Exercise (2:45)
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Containers Solution Part 1 (5:29)
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Container Solution Part 2 (8:35)
String Formatting
Regular Expressions
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A Simple Regular Expression (3:43)
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Matching Multiple Characters (2:45)
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The Ternary Operator (3:35)
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Greedy Matching (5:56)
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Matching Numbers and Words (7:29)
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Capture Groups (3:07)
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Ranges in Regexes (4:33)
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Character Classes (4:25)
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Email Exercise Solution (3:29)
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Character Class Not (6:24)
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A Note On Escaping (2:50)
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Regular Expression Comments (5:51)
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Referring to Capture Groups (3:07)
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Capture and Non-Capture Groups (5:44)
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Matching Newlines (4:05)
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Matching Ends of Lines (4:56)
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Search (3:42)
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Findall (4:46)
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Matching Starts of Lines (5:39)
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Splitting (2:36)
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Substitution (1:37)
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Alternatives (4:36)
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Budget Exercise (2:45)
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Budget Solution Part 1 (6:02)
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Budget Solution Part 2 (7:48)
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Ignoring Case (2:16)
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Compiling Regular Expressions (6:32)
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Lookahead Assertions (8:05)
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Not Space or Digits or Text (4:15)
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Regular Expressions Summary (5:59)
Handling Errors
Object-Oriented Programming
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Classes (6:59)
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Constructors (5:00)
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Self (7:18)
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Properties (7:14)
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Converting to Strings (4:19)
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Encapsulation (6:16)
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An OO Word Game (8:03)
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Choosing Words (4:17)
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Guessing Letters (6:17)
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Displaying Letters (5:53)
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Completing the Word Game (7:08)
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Getters and Setters (8:08)
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Inheritance (5:54)
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Overriding Methods (3:33)
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Polymorphism (5:41)
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Super Constructors (5:24)
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Class Properties (7:03)
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Assigning IDs (4:24)
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Class Methods (6:53)
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Objects and Classes (6:04)
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OOP Exercise (4:39)
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OOP Solution Part 1 (5:28)
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OOP Solution Part 2 (6:25)
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OOP Solution Part 3 (6:48)
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Class Hierarchies (5:44)
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Multiple Inheritance (3:29)
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The Diamond Problem (6:01)
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Mixins (7:00)
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The Property Class (9:23)
Conway's Game of Life
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Conway Game of Life (2:23)
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A Basic GUI App (5:29)
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Frames (5:04)
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Refactoring Into Classes (5:06)
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Grids (7:57)
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A Canvas Class (4:09)
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Getting Widget Sizes (9:18)
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Drawing Cells (6:19)
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A Cell Class (6:45)
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Toggling Cell State (7:02)
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Handling Button Clicks (5:51)
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Selecting Neighbours (3:48)
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Wrapping (8:12)
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Game of Life Rules (3:38)
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Implementing the Rules (8:30)
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Clearing the Grid (2:11)
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Randomising (6:46)
Modules
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Modules Demo (5:04)
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Conditionally Running Main (6:00)
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Importing Parts of Modules (2:50)
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Packages (2:58)
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Games Package Solution (4:13)
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Functions in Dictionaries (7:15)
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Games Menu Solution (5:56)
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Package Initialisation (6:49)
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How Python Locates Modules (6:30)
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Inspecting Modules (5:03)
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Subpackages (3:59)
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Package Attributes (4:25)
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Referencing Parallel Packages (5:11)
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Installing Modules (7:59)
Operators
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Clock Exercise (3:16)
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Clock Solution (3:38)
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Implementing Add (2:45)
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Implementing Unary Operators (5:10)
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Flags (3:47)
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Bitwise Or (5:49)
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Bitwise Flags (5:51)
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Bitwise And (1:42)
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Flags Exercise (3:34)
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Flags Solution (7:13)
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Bitwise XOR and NOT (4:56)
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Bit Shift Operators (7:07)
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Hexadecimal Numbers (9:08)
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Hexadecimal Colors Solutions (6:07)
Functional Programming
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Recursion (5:38)
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Introducing Functional Programming (3:33)
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Passing Functions to Functions (3:43)
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Iterators (6:19)
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Powers of Two Iterator (4:05)
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Mapping (5:17)
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Lambda Functions (1:48)
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Defining Functions in Loops (6:49)
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1209_Lambda_Exercise_Solution (3:55)
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Sorting (4:46)
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Next and Iter (7:59)
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Generating Characters (3:23)
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Generators (4:45)
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Generators Exercise (2:29)
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Generators Solution (1:56)
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General Generator Syntax (3:05)
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Generators As Loops Solution (5:21)
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Game of Life Solution (5:45)
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Itertools (5:01)
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Function Generators (3:56)
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Powers of Two Generator Solution (2:04)
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Filtering (2:33)
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Reduce (4:07)
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A Functional Word Exercise (3:35)
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Functional Word Solution (4:01)
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Functional Parsing Exercise (1:11)
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Functional Parsing Solution (3:18)
Files
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Reading Files (2:25)
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Mall Customers Database (4:20)
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Ensuring Files Get Closed (2:35)
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Examining With (6:05)
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Iterating Over Files (2:53)
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Writing Files (3:12)
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Files Exercise Solution (7:03)
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Appending to Files (1:27)
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Handling Binary Text (8:31)
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Binary Files (3:13)
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Serialization (3:05)
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Serializing Integers (5:32)
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Deserializing Integers (3:36)
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Saving and Loading Ints (4:24)
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Numbers Versus Bytes (11:28)
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Python Arrays (7:49)
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Saving Arrays (5:51)
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Pickling (3:54)
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JSON (5:05)
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File Dialogs (8:21)
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Game of Life Menus (4:55)
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Game of Life Load and Save (9:30)
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Testing Game of Life (5:03)
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The OS Module (6:08)
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Word Count Exercise (3:26)
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Splitting into Words (7:20)
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Counting Words (6:50)
Numpy
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Numpy Arrays (6:37)
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Creating Numpy Arrays (11:23)
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Numpy Arithmetic (4:42)
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Numpy Slicing (5:20)
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2D Indexing (5:12)
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Views (4:20)
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Advanced Indexing (6:12)
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Numpy Matrices (7:17)
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Matrix Multiplication (6:17)
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Numpy Functions (4:24)
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Numpy Exercise (2:50)
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Numpy Solution Part 1 (6:38)
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Numpy Solution Part 2 (5:10)
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Tiling (4:42)
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Masks (2:18)
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Combining Boolean Arrays (3:42)
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Filtering Numpy Arrays (3:41)
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Variance and Standard Deviation (5:42)
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Variance Exercise (6:11)
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Bessel's Correction (8:02)
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Scaling and Variance (7:50)
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Loading CSV in Numpy (1:52)
Graphs and Plotting
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Pyplot Basics (3:09)
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Styles (5:00)
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Configuration (3:31)
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More Configuration (6:22)
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Word Lengths Exercise (1:35)
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Word Length Plot Solution Part 1 (9:24)
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Word Length Solution Part 2 (6:54)
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Bar Charts (5:49)
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Pie Charts (6:22)
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Pie Chart Solution (5:51)
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Scatter Plots (10:08)
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Histograms (6:22)
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Multiple Graphs on One Chart (4:51)
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Subplots (6:50)
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Subplots Solution (6:26)
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3D Plots (6:02)
Pandas
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Introduction (6:08)
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Referencing Cells (3:58)
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Loc and iloc (7:34)
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Changing Values (5:44)
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Pandas Functions (7:34)
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Series (4:36)
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Pandas Charts (3:09)
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Sorting (6:11)
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Correlations (6:02)
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Grouping (6:52)
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Grouped Types (5:09)
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Group Aggregate Functions (4:18)
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Filtering (4:25)
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Multiple Groups (3:39)
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Plotting Groups (8:15)
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Binning (8:13)
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Groupby Exercise (0:40)
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Groupby Exercise Solution Part 1 (5:43)
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Groupby Exercise Solution Part 2 (7:15)
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Zipfs Law Exercise (8:38)
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Zipfs Law Solution (5:11)
Regression
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Linear Regression Data (5:20)
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Introduction (4:35)
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Configuring Labels (6:19)
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Equation of a Line (7:01)
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Linear Regression (7:36)
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Why Add Constant (5:45)
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R Squared (5:19)
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Calculating R Squared (7:53)
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1709_Train_Test (7:39)
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Predictions With Linear Regression (8:31)
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Linear Regression Exercise (2:52)
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Plotting Grapes Solution (3:25)
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Predicting Grape Weights (6:43)
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Removing Outliers (6:56)
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Multiple Linear Regression (5:05)
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A Multiple Linear Regression Model (7:03)
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About Polynomial Regression (6:20)
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Polynomial Features (7:32)
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A Polynomial Regression Model (9:02)
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1720_A_Surprising_Result (6:55)
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Binomial Logistic Regression and Causation (7:27)
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Categorical Dummies (5:39)
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The Logistic Equation (7:03)
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Logistic Regression Model (6:32)
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Multiple Logistic Regression (6:21)
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Getting Predictions with Logistic Regression (3:23)
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Confusion Matrices (6:40)
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Scaling and Normalisation (8:38)
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Normalising Split Data (7:15)
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Using Standard Scaler (8:47)
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Confusion Matrix Exercise (4:04)
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Confusion Matrix Solution Part 1 (7:27)
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Confusion Matrix Solution Part 2 (7:10)
Clustering
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Clustering (5:34)
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K-Means Clustering (8:17)
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Centroids and Inertia (4:31)
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The Elbow Method (7:35)
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K-Means Exercise Solution (5:48)
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Exercise Analysis (4:46)
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The Iris Flower Data Set (4:09)
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Loading the Iris Data (4:33)
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Seaborn Plots (5:14)
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K-Means Iris Exercise (2:15)
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K-Means Iris Solution (12:07)
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Permutations Exercise (4:52)
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Permutations Solution (7:07)
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Normalized Mutual Information (4:26)
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Dendrograms (7:37)
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The Linkage Table (9:23)
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Clustering Iris Data (8:22)
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Scikit-Learn Agglomerative Clustering (7:25)
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Linkage and Affinity (7:08)
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Fit Predict Transform (6:49)
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Nearest Neighbours (5:26)
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Spherically Symmetric Data (9:40)
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DBSCAN (5:47)
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Determining Epsilon (9:19)
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Using DBSCAN (6:41)
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DBSCAN Moons Exercise (6:44)
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DBSCAN Moons Solution (7:54)
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Silhouette Scores (4:43)
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Nearest Neighbors Classification (2:08)
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Using K-Neighbors Classifier (9:24)
Naive Bayes
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Bayes' Theorem (13:15)
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Naive Bayes (9:37)
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Applying Naive Bayes to Classification (7:29)
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An Email Dataset (1:20)
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Loading Emails (7:29)
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Counting Words (3:29)
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Listing Common Words (7:02)
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The Predictor Matrix (4:01)
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Naive Bayes Classifiers (9:03)
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Naive Bayes Exercise (4:17)
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Naive Bayes Solution (6:39)
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Classifying Irises (6:21)
Decision Trees
Principal Component Analysis
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Introduction (4:57)
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Data for PCA (7:18)
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How PCA Works (9:34)
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Transforming Data With PCA (8:37)
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Explained Variance Ratios (9:04)
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Iris Data PCA Analysis (8:09)
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PCA Components (5:03)
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Classifying Irises With PCA (9:05)
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PCA Tips (6:59)
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PCA Exercise (3:36)
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PCA Solution (13:42)
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The MNIST Dataset (4:23)
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Fetching from Openml (6:26)
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Loading MNIST With Keras (6:33)
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Character Recognition (9:47)
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Configuring Logistic Regression (8:37)
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Displaying Images (7:04)
Artificial Neural Networks (ANNs)
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An Artificial Neuron (5:42)
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Activation Functions (5:31)
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Minimizing Loss (8:22)
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Preparing Iris Data (8:30)
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A Basic ANN (10:27)
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Dropout and Tweaking the Network (5:23)
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MNIST Exercise (4:21)
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MNIST Preparing the Data (4:38)
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MNIST ANN (9:34)
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Improving the MNIST ANN (4:57)
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Comparing Subarrays (5:43)
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Displaying Misclassified Images (6:18)
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Saving and Loading (3:29)
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Pipelines (6:23)
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Standalone Classifier (4:09)
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California Housing Dataset (4:08)
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Regression Neural Net (8:54)
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Improving Regression (3:30)
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Analysing Results (7:33)
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Detecting Overfitting (8:51)
Conclusion
