What you'll learn
You will learn the basic principles of Python and learn all the main functions that are used most often in real projects and are in demand the most
You will practice all the examples that I will show throughout the course using the Python interpreter, Visual Studio Code with Code Runner
You will master all the necessary packages for Data Science and Machine Learning such as NumPy, Pandas, Matplotlib and Scikit-learn using Jupyter Notebook
You will learn the basic functionality of Python, ranging from variables, lists, dictionaries, to classes, loops, modules, and creating virtual environments
In addition, you will learn how to use functional and object-oriented approaches in Python programming.

Requirements
There are no prerequisites, all you need is a desire to learn and practice
It is advisable to study on a laptop with an external monitor, you can also use a tablet

Description
Python is the easiest programming language in the world. But at the same time, Python is a powerful tool with which you can solve a huge range of different tasks, from file processing to machine learning , data processing , game creation and web application development .Thus, having learned Python, you can choose a profession from a wide range of vacancies, or you can use Python to create your own applications and solve your own problems.This course includes many practical tasks, as well as tasks for self-fulfillment .Python is an object oriented programming language.Python is also a language with a huge amount of features, but in order to be able to code in Python, you need to UNDERSTAND the key concepts of Python. And that's what I'm going to focus on with you in this course.Before writing code and running examples, you will receive from me explanations and answers to questions WHY and WHY , and only after that HOW to write code.I will not waste your time and therefore I have created the most effective course structure. All the examples that I will explain and run are written by me before the course, but you will write and run the code yourself.All video lectures in this course are over 50 hours long , but expect to spend around 500 hours to master all the topics of the course, including self-completion of all practical tasks.In this course you will learn following key topics:Foundational Python Programming: Learn the fundamental concepts of Python programming, from data types, functions, and variables to control structures like loops and conditional statements.Object-Oriented Programming (OOP): Dive into the principles of OOP, understanding classes, objects, inheritance, encapsulation, and polymorphism, and discover how to leverage them for efficient code organization.File Handling and Modules: Explore file manipulation techniques, from working with directories and files using the os module to using external modules, enabling code reuse, and managing packages with PIP.Web Development with Django: Get an introduction to web development using Django, covering MVC architecture, URL routing, model creation, and interacting with databases to build dynamic web applications.API Development: Learn to create RESTful APIs using Django and handle API requests and responses, including authentication, authorization, and versioning.Game Development with Pygame: Enter the world of game development with Pygame, creating interactive games by working with graphics, animations, and user input.Data Manipulation with NumPy and Pandas: Discover data analysis and manipulation using NumPy and Pandas, covering array operations, dataframes, and handling real-world data sets.Error Handling and Debugging: Understand error handling mechanisms in Python, from handling exceptions to proper debugging techniques, ensuring robust and reliable code.Package Management and Virtual Environments: Master package management using PIP, create virtual environments to isolate projects, and manage dependencies effectively.Visualization and Machine Learning: Explore data visualization with Matplotlib, and dip your toes into machine learning concepts with Scikit-Learn, covering model creation, evaluation, and prediction.Why it's important: This course provides a comprehensive foundation in Python programming, from basic syntax to advanced topics like OOP, web and game development, data manipulation, and more. Understanding these concepts is crucial for building versatile applications, performing data analysis, and even stepping into machine learning, ensuring you're equipped for a wide range of programming tasks and projects.After completing this course, you can safely say that you KNOW Python and CAN use the most popular Python functions. AAs any of my courses this course comes with 30-days money back guarantee. No questions asked!

Overview
Section 1: Introduction to Python

Lecture 1 Introduction to the Complete Python Guide

Lecture 2 Where to Write and Run Python Code

Lecture 3 Practice - Installing Python

Lecture 4 Practice - Using the Python Interactive Interpreter

Section 2: Installing and Using PyCharm IDE

Lecture 5 Installing PyCharm

Lecture 6 Getting Familiar with the PyCharm Interface

Section 3: Basic Concepts in Python

Lecture 7 Key Concept in Python

Lecture 8 Main Data Types in Python

Lecture 9 Practice - Working with Main Data Types

Section 4: Introduction to Functions and Built-in Functions in Python

Lecture 10 Built-in Functions

Lecture 11 Practice - Defining and Using Functions

Lecture 12 Practice - Using the Return Statement in Functions

Lecture 13 Practice - Exploring Built-in Functions

Lecture 14 Practice - Using the built-in dir() Function

Lecture 15 Practice - Gathering User Input with the built-in input() Function

Section 5: Code Formatting and PEP8

Lecture 16 Code Indentations

Lecture 17 Practice - Working with Indentations

Lecture 18 Following PEP 8 Guidelines

Lecture 19 Enabling Auto-Formatting in PyCharm

Section 6: Comments

Lecture 20 Comments

Lecture 21 Practice - Adding Comments to Your Code

Section 7: Expressions and Instructions

Lecture 22 Understanding Expressions

Lecture 23 Understanding Statements

Lecture 24 Practice - Using Expressions

Lecture 25 Practice - Using Statements

Section 8: Variables

Lecture 26 Variables

Lecture 27 Practice - Defining and Using Variables

Section 9: Data Types and Structures

Lecture 28 Understanding Dynamic Typing

Lecture 29 Types and Data Structures Overview

Lecture 30 Variables and Objects

Lecture 31 Practice - Using the built-in id() Function

Lecture 32 Practice - Exploring Core Data Classes (str, int, bool, list, dict)

Lecture 33 Practice - Using the built-in isinstance() Function

Section 10: Strings

Lecture 34 Strings

Lecture 35 Practice - String Manipulation

Lecture 36 Practice - String Methods

Section 11: String Concatenation

Lecture 37 String Concatenation

Lecture 38 Practice - Concatenating Strings using the + Operator

Lecture 39 Practice - Using f-strings for String Formatting

Lecture 40 Practice - Alternative String Formatting Methods

Section 12: Numeric Types

Lecture 41 Integers

Lecture 42 Practice - Integers Manipulation

Lecture 43 Float Numbers

Lecture 44 Practice - Floating-Point Numbers Manipulation

Lecture 45 Working with Complex Numbers

Section 13: Boolean Type

Lecture 46 Boolean Values

Lecture 47 Practice - Working with Boolean Values

Lecture 48 Type Conversion

Section 14: Magic Methods

Lecture 49 Magic Methods

Lecture 50 Practice - Utilizing Magic Attributes and Methods

Section 15: Lists

Lecture 51 Lists

Lecture 52 List Methods

Lecture 53 Practice - Working with Lists

Lecture 54 Copying Lists

Lecture 55 Practice - Copying Lists

Lecture 56 TASK - Working with Lists

Section 16: Dictionaries

Lecture 57 Dictionaries

Lecture 58 Practice - Manipulating Dictionaries

Lecture 59 Practice - Dictionary Methods

Lecture 60 Other Operations with Dictionaries

Lecture 61 Practice - Using the get() Method for Dictionaries

Lecture 62 Practice - Converting Other Types to a Dictionary

Lecture 63 TASK - Working with Dictionaries

Section 17: Tuples

Lecture 64 Tuples

Lecture 65 Practice - Tuples Manipulation

Section 18: Sets

Lecture 66 Sets

Lecture 67 Practice - Working with Sets

Lecture 68 Understanding Set Theory

Lecture 69 Set Methods

Lecture 70 Practice - Usage of the Set Methods

Lecture 71 Practice - Calculating Symmetric Difference of Sets

Lecture 72 TASK - Working with Sets

Section 19: Ranges

Lecture 73 Ranges

Lecture 74 Practice - Range Manipulation

Lecture 75 Practice - Range Methods and Attributes

Section 20: Working with Sequences

Lecture 76 Built-in Functions for Sequences

Lecture 77 Built-in zip() Function

Lecture 78 Practice - Working with zip Objects

Lecture 79 Practice - Converting a zip Object to a Dictionary

Lecture 80 Comparison of Different Sequences

Section 21: Modifying Objects in Python

Lecture 81 Understanding Immutable Objects in Python

Lecture 82 Understanding Mutable Objects in Python

Lecture 83 Strategies to Prevent Object Mutation

Lecture 84 Practice - Creating Deep Copies of Objects

Section 22: Functions

Lecture 85 Functions

Lecture 86 Calling Functions: Arguments vs Parameters

Lecture 87 Shortest Function in Python

Section 23: Function Arguments

Lecture 88 Mutable and Immutable Arguments in Function Calls

Lecture 89 Practice - Using Mutable and Immutable Objects as Function Arguments

Lecture 90 Practice - Mandatory and Optional Positional Arguments

Lecture 91 TASK - Functions Manipulation

Lecture 92 Function Arguments

Section 24: Args and kwargs in Functions

Lecture 93 Practice - Using *args to Gather Positional Arguments into a Tuple

Lecture 94 Keyword Arguments

Lecture 95 Practice - Working with Keyword Arguments

Lecture 96 Practice - Using **kwargs to Merge Keyword Arguments in a Dictionary

Lecture 97 TASK - Manipulating Function Arguments

Lecture 98 Args and kwargs

Lecture 99 Practice - Gathering Positional Arguments into the *args Tuple

Lecture 100 Practice - Gathering All Keyword Arguments into the **kwargs Dictionary

Section 25: Default Function Parameters

Lecture 101 Default Function Parameters

Lecture 102 Practice - Using Default Function Parameters

Section 26: Docstrings

Lecture 103 Docstrings

Lecture 104 Practice - Writing and Using Docstrings

Lecture 105 Practice - Exploring Docstrings

Lecture 106 Practice - Adding Docstrings to Functions

Section 27: Callback Functions

Lecture 107 Callback Functions

Lecture 108 Rules for Working with Functions

Section 28: Global and Local Variables

Lecture 109 Scopes

Lecture 110 The Global Keyword

Lecture 111 Practice - Global and Local Variables

Lecture 112 Practice - Using the Global Keyword

Section 29: Operators

Lecture 113 Operators

Lecture 114 Unary and Binary Operators

Lecture 115 Practice - Working with Prefix Unary Operators

Lecture 116 TASK - Operators

Section 30: Falsy and Truthy Values

Lecture 117 Falsy and Truthy Values

Lecture 118 Practice - Falsy and Truthy Values

Section 31: Logical and Comparison Operators

Lecture 119 Logical Operators

Lecture 120 Practice - Short-Circuit OR Operator

Lecture 121 Practice - Short-Circuit AND Operator

Lecture 122 Practice - Combining OR and AND Operators

Lecture 123 Practice - Examples with Logical Operators

Lecture 124 Practice - Comparison Operators

Lecture 125 The del Statement

Section 32: Lambda Functions

Lecture 126 Lambda Functions

Lecture 127 Practice - Returning Lambda Functions from Functions

Lecture 128 Practice - Sorting a List using Lambda Functions

Lecture 129 Practice - Filtering a List using Lambda Functions

Section 33: Error Handling

Lecture 130 Error Handling

Lecture 131 Practice - Using Different Error Classes in the Try and Except

Lecture 132 Practice - Using Multiple Error Classes in one Except Block and Parent Exception

Lecture 133 Practice - Using Else and Finally Blocks

Lecture 134 Example - Handling File Not Found Errors

Lecture 135 Example - Handling Undefined Variable Errors

Lecture 136 Practice - Raising Custom Errors

Lecture 137 Practice - Handling Raised Errors using Try and Except

Lecture 138 Practice - Specifying Types for Function Parameters

Lecture 139 TASK - Proper Error Handling

Section 34: Sequence Unpacking

Lecture 140 Sequence Unpacking

Lecture 141 Practice - Unpacking Tuples

Lecture 142 Practice - Unpacking a List of Tuples

Lecture 143 Practice - Unpacking Remaining Elements

Lecture 144 Practice - Unpacking Selected Elements

Lecture 145 Practice - Unpacking a List into Positional Arguments

Lecture 146 Practice - Unpacking a Dictionary into Keyword Arguments

Lecture 147 Practice - Flexibility in Function Calls

Section 35: Unpacking Dictionaries

Lecture 148 Dictionary Unpacking Operator **

Lecture 149 Practice - Using the Dictionary Unpacking Operator

Lecture 150 Practice - Merging Two Dictionaries

Section 36: Conditional Statements

Lecture 151 Conditional Statements

Lecture 152 Practice - Working with Multiple if Statements

Lecture 153 The if-else Statement

Lecture 154 The if-elif Statement

Lecture 155 Practice - Combining if, elif, and else Statements

Lecture 156 Practice - Considering the Order of Conditions in if Statements

Lecture 157 Practice - Incorporating if Statements into Functions

Lecture 158 Practice - Using if and return Statements within Functions

Lecture 159 Example - Calculating School Grades using if and return in the Function

Lecture 160 TASK - Conditional Statements

Section 37: Ternary Operator

Lecture 161 Ternary Operator

Lecture 162 Practice - Utilizing the Ternary Operator

Lecture 163 Example - Calculating Discounts with the Ternary Operator

Lecture 164 Example - Data Manipulation using the Ternary Operator

Lecture 165 Example - Calculating School Grades using the Ternary Operator

Section 38: For-In Loop

Lecture 166 Loops

Lecture 167 For-In Loop

Lecture 168 Practice - Iterating through Lists and Tuples using For-In Loops

Lecture 169 Practice - Iterating through Dictionaries using For-In Loops

Lecture 170 Practice - Iterating through Ranges, Strings, and Sets with For-In Loops

Lecture 171 TASKS - Working with For-In Loops

Section 39: While Loop

Lecture 172 While Loop

Lecture 173 Practice - Utilizing the While Loop

Lecture 174 Example - Making Selections with the While Loop

Lecture 175 Practice - Using break Statements in While and For-In Loops

Lecture 176 Practice - Using continue and break Statements in While Loops

Lecture 177 TASK - While Loop

Section 40: For-In Expression (Comprehensions)

Lecture 178 For-In Expression

Lecture 179 List, Set, and Dictionary Comprehensions

Lecture 180 Practice - Using List Comprehension

Lecture 181 Practice - Using Dictionary Comprehension

Lecture 182 Practice - Utilizing Tuple Comprehension

Lecture 183 Practice - Converting Tuples to Lists

Lecture 184 Example - Constructing Dictionaries from Sequences

Lecture 185 Practice - Short For-In Loops with Conditional Statements

Lecture 186 Example - Converting Dictionary to Another Dictionary

Lecture 187 TASKS - Short For-In Loops

Lecture 188 Example - Chaining For-In Expressions

Section 41: Generators

Lecture 189 Generators in For-In Expressions

Lecture 190 Practice - Generators and Iteration over the Generator

Section 42: Decorator Functions

Lecture 191 Introduction to Decorator Functions

Lecture 192 Example - Verifying User Permissions with Decorator Functions

Lecture 193 Example - Logging using Decorator Functions

Lecture 194 Example - Validating Arguments with Decorator Functions

Section 43: Objects and Classes

Lecture 195 Classes and Objects

Lecture 196 Practice - Understanding Classes and Class Instances

Lecture 197 Practice - Adding Instance Attributes through Dot Notation

Lecture 198 Adding Instance Attributes using the __init__ Method

Lecture 199 Practice - Incorporating Own Instance Attributes with the __init__ Method

Section 44: Instance and Class Methods

Lecture 200 Instance vs Class Methods

Lecture 201 Practice - Inheriting Methods by the Instances

Lecture 202 Static Class Methods

Lecture 203 Practice - Utilizing Static Methods in Classes

Lecture 204 Class Attributes

Lecture 205 Practice - Working with Class Attributes

Section 45: Magic Methods in Classes

Lecture 206 Magic Methods in Classes

Lecture 207 Practice - Utilizing Magic Methods in Classes

Section 46: Classes Extension

Lecture 208 Inheritance from Other Classes

Lecture 209 Practice - Extending Classes

Section 47: Classes on Practice

Lecture 210 Example - Creating Forum, User, and Post Classes

Lecture 211 Example - Creating Instances of the Forum, User, and Post Classes

Lecture 212 Example - Methods for Finding Users by Username and Email

Lecture 213 Example - Method for Finding All Posts by a Specific User

Lecture 214 Example - Retrieving User Posts by Email

Lecture 215 Example - Adding Parameter Types

Lecture 216 Example - Wrapping up the Forum, Users, and Posts Example

Section 48: Key Principles in Object-Oriented Programming

Lecture 217 Encapsulation in Object-Oriented Programming (OOP)

Lecture 218 Inheritance in Object-Oriented Programming (OOP)

Lecture 219 Polymorphism in Object-Oriented Programming (OOP)

Lecture 220 Abstraction in Object-Oriented Programming (OOP)

Section 49: Modules

Lecture 221 Modules

Lecture 222 Practice - Importing Entire Custom Modules

Lecture 223 Practice - Selective Imports from Other Modules

Lecture 224 Practice - Importing between Different Modules

Lecture 225 Practice - Modules in Subfolders

Section 50: Built-in Modules

Lecture 226 Built-in Modules

Lecture 227 Practice - Importing from Built-in Modules

Section 51: What is __name__ and __main__

Lecture 228 Practice - __name__ and __main__

Lecture 229 Example - Executing Functions only when Module is run Directly

Lecture 230 Practice - Packages in Python

Section 52: javascript Object Notation (JSON)

Lecture 231 javascript Object Notation (JSON)

Lecture 232 Practice - Converting Python Objects to JSON

Lecture 233 Practice - Converting from JSON to Python Objects

Lecture 234 Practice - Formatting Dictionaries using JSON

Lecture 235 TASKS - JSON

Section 53: Working with Files

Lecture 236 Working with Files

Lecture 237 Working with Files and Directories using the os Module

Lecture 238 Removing Files and Directories using the os Module

Lecture 239 Summary of Directory and File Operations using the os Module

Lecture 240 Working with Files and Directories using the Path Class

Lecture 241 Iterating over Directories and Removing Files using the Path Class

Lecture 242 Reading and Writing Files

Lecture 243 Writing and Reading Files using the built-in open Function

Lecture 244 Using the with Statement

Lecture 245 Removing Files using unlink

Lecture 246 TASK - Files

Section 54: Working with Zip Archives

Lecture 247 Built-in zipfile Module and Creating Zip Archives

Lecture 248 Reading from the Zip Archive

Section 55: Working with CSV Files

Lecture 249 Working with CSV Files

Lecture 250 Iterating over Each Row in the CSV File

Section 56: Working with Dates and Times

Lecture 251 Built-in datetime Module

Lecture 252 Examples - Using the datetime Class

Lecture 253 Examples - Converting Strings to Datetime Objects

Lecture 254 Example - Working with the timedelta Class

Lecture 255 Built-in time Module

Section 57: Generating Random Sequences and Passwords

Lecture 256 Built-in random Module

Lecture 257 Examples - Utilizing choices and shuffle Methods from the random Module

Lecture 258 Built-in secrets Module

Lecture 259 Examples - Generating CSRF Tokens, URL-Safe Tokens, and OTP Passwords

Lecture 260 Example - Generating Strong Passwords

Section 58: Math Module and Recursive Functions

Lecture 261 Built-in math Module

Lecture 262 Recursive Functions

Section 59: Regular Expressions

Lecture 263 Built-in re Module for Regular Expressions

Lecture 264 Example - Creating Patterns for Matching

Lecture 265 Example - Email Validation using Regular Expressions

Lecture 266 Example - Substring Replacement using Regular Expressions

Lecture 267 Example - Removing Excessive Spaces using Regular Expressions

Lecture 268 TASK - Password Verification

Section 60: Sending Emails

Lecture 269 Running smtp4dev SMTP server in a Docker Container

Lecture 270 Sending an Email using SMTP

Lecture 271 Formatting an Email using an HTML Template

Lecture 272 SMTP Wrap-Up and Removing the Docker smtp4dev Container

Section 61: Working with SQLite Database

Lecture 273 Creating an SQLite3 Database and Table

Lecture 274 Writing Data into the SQLite Table

Lecture 275 Reading Data from the SQLite Table

Lecture 276 SQLite Summary

Section 62: Other Built-in Modules

Lecture 277 Built-in array Module

Lecture 278 Saving Arrays to Files and Reading Arrays from Files

Lecture 279 Accessing Program Arguments using the built-in sys Module

Lecture 280 Built-in webbrowser Module

Section 63: Virtual Environments

Lecture 281 Introduction to PIP - Package Manager for Python

Lecture 282 Using a Globally Installed requests Package

Lecture 283 Uninstalling Globally Installed Packages using PIP

Lecture 284 Creating a Python Virtual Environment

Lecture 285 Activation and Deactivation of the Virtual Environment in the Shell

Lecture 286 Installing Packages within the Virtual Environment

Lecture 287 Saving a List of Installed Packages in a Requirements Text File

Lecture 288 Challenges of Package Management using Requirements Files

Section 64: Pipenv for Virtual Environments Management

Lecture 289 Installing pipenv for Virtual Environments Management

Lecture 290 Creating a Virtual Environment using pipenv

Lecture 291 Installing Packages using pipenv

Lecture 292 Updating Packages using pipenv

Lecture 293 Recreating Virtual Environment in the Project Folder using pipenv

Lecture 294 Using venv for Virtual Environments in PyCharm

Lecture 295 Using pipenv for Virtual Environments in PyCharm

Section 65: Introduction to the Django Web Framework

Lecture 296 Introduction to the Django Web Framework and Project Overview

Lecture 297 Model View Controller (MVC) Programming Pattern

Lecture 298 Understanding How MVC Pattern is Implemented in Django

Lecture 299 Creating a New PyCharm Project and Installing Django

Section 66: Creating a Django Project

Lecture 300 Creating a New Django Project

Lecture 301 Overview of the manage.py File in Django

Lecture 302 Starting and Verifying the Django Server

Lecture 303 Overview of Settings in the Django Project

Lecture 304 Overview of Default Routing Configuration in Django

Section 67: Creating a Django Application

Lecture 305 Creating the Shop Application in Django

Lecture 306 Explaining the Naming of the Django Project as "base"

Lecture 307 Exploring the Contents of the Shop Application

Lecture 308 Creating a View Function

Lecture 309 Attaching the View Function to a URL

Lecture 310 Adding Shop Application Routes to the Global Project Routing Configuration

Section 68: Database and Migrations in Django

Lecture 311 Applying Default Migrations in the Django Project

Lecture 312 Creating an Admin User in the Django Project

Lecture 313 Creating Course and Category Models

Lecture 314 Enabling the Shop Application in the Django Project

Lecture 315 Creating and Applying Migrations for the Shop Application

Lecture 316 Modifying Database Models

Lecture 317 Creating a Category using the Category Model in the Shell

Lecture 318 Creating Courses using the Course Model in the Shell

Lecture 319 Creating Categories and Courses in the Admin Interface

Lecture 320 Modifying How Courses and Categories are Displayed in the Admin Panel

Lecture 321 Sending Course Titles to the Client in the Response

Section 69: Creating Templates in Django

Lecture 322 Creating an HTML Template

Lecture 323 Using an HTML Template in the View Function

Lecture 324 Populating the HTML Template with Data from the Database

Lecture 325 How we Connected Templates, Views, and Models

Lecture 326 Adding the Bootstrap CSS Library to the HTML Template

Section 70: Extending Other Templates in Django

Lecture 327 Creating a Base HTML Template for Reuse in Other Templates

Lecture 328 Adding a Navigation Bar in the Base Template

Lecture 329 TASK - Making the Title of the Web Page Dynamic

Lecture 330 SOLUTION - Making the Title of the Web Page Dynamic

Section 71: Creating Multiple Routes and View Functions

Lecture 331 Creating a Route for the Single Course Web Page

Lecture 332 Creating a View Function for the Single Course

Lecture 333 TASK - Creating an HTML Template for the Single Course

Lecture 334 SOLUTION - Creating an HTML Template for the Single Course

Lecture 335 Responding with a 404 When Course is Not Found in the Database

Section 72: Routing Between Pages in Django

Lecture 336 Setting Up Routing Between Pages Using Relative or Absolute Paths

Lecture 337 Setting Up Routing Based on the Names of the URL Patterns

Lecture 338 Considering Application Names in the Routing Setup

Lecture 339 Adding a Link to the All Courses Page

Lecture 340 Moving the Templates Folder Out of the Shop Application Folder

Lecture 341 Modifying the Model for the Courses

Lecture 342 Summary of the Django Shop Application

Lecture 343 Installing django-tastypie for the API Django Application

Section 73: Creating an API Django Application

Lecture 344 Creating an API Django Application

Lecture 345 Creating Models for the API Application

Lecture 346 Configuring Routing for the API Application

Lecture 347 Verifying the API Service

Lecture 348 Adding Version for the API

Lecture 349 Installing Postman and Sending GET and DELETE Requests

Section 74: Managing Authentication for API Requests

Lecture 350 Creating an API Key for the User

Lecture 351 Enabling Authentication and Authorization for the Model and Using DELETE Method

Lecture 352 Disabling Authentication Only for GET Requests

Lecture 353 Creating a New Resource Using POST Method

Lecture 354 Properly Connecting the Course to the Category in POST Requests Using Hydrate Me

Lecture 355 Adding Dehydrate Method to Modify Data Before Sending to Client

Lecture 356 Summary for Setting Up GET, POST, and DELETE Requests

Section 75: Django Project Refactoring and Admin Settings

Lecture 357 Refactoring Routing for the API Application

Lecture 358 Setting Up Index Route and Adding Navigation to Navbar

Lecture 359 Modifying Administrative Panel

Lecture 360 Summary of Django Courses Project

Section 76: Creating Games with Pygame

Lecture 361 Introduction to Pygame and Creating the Game Window

Lecture 362 Modifying Background Color of the Game Surface

Lecture 363 Displaying a Rectangle in the Game

Lecture 364 TASK - Placing Rectangle in the Middle of the Game Window

Lecture 365 SOLUTION - Placing Rectangle in the Middle of the Game Window

Lecture 366 Moving Rectangle Using Keyboard Arrows

Lecture 367 Stopping Rectangle from Moving Outside of the Surface

Section 77: Creating a Shooter Game with Pygame

Lecture 368 Final Shooter Game Overview

Lecture 369 Loading Images for the Game and Fighter

Lecture 370 Displaying Fighter on the Surface

Lecture 371 Moving Fighter Left or Right

Lecture 372 Making Fighter Movement Continuous

Lecture 373 Adding the Ball to the Game

Lecture 374 Showing Ball Based on Fighter Position

Lecture 375 Moving the Ball After Firing

Lecture 376 Adding the Alien to the Game

Lecture 377 Moving the Alien Down the Surface

Section 78: Interaction of the Elements in the Pygame

Lecture 378 Detecting Collision Between Alien and Fighter, Ending the Game

Lecture 379 Hitting the Alien with the Ball

Lecture 380 Increasing Alien Speed After Each Hit

Lecture 381 Adding Hit Counter

Lecture 382 Shooter Game Summary

Section 79: Game Refactoring using Classes and OOP

Lecture 383 Start of Shooter Refactoring and Creating the Fighter Class

Lecture 384 Adding Methods in the Fighter Class

Lecture 385 Creating an Alien Class

Lecture 386 Adding Methods in the Alien Class

Lecture 387 Creating a Ball Class

Lecture 388 Adding Methods in the Ball Class

Lecture 389 Creating a Game Class

Lecture 390 Adding Methods in the Game Class

Lecture 391 Adding Methods for Drawing Elements and Finalizing Refactoring

Lecture 392 Game Refactoring Summary

Lecture 393 Running the Game After Refactoring

Section 80: Jupyter Notebook

Lecture 394 Installing Jupyter Notebook

Lecture 395 Editing in Jupyter Notebook

Lecture 396 Order of Execution of Cells in Jupyter Notebook

Lecture 397 Adding Markdown, Saving, and Loading Jupyter Notebooks

Section 81: Jupyter Lab

Lecture 398 Installing Jupyter Lab and Editing Notebooks

Lecture 399 Exploring Features of Jupyter Lab

Lecture 400 Installing External Packages in Jupyter Notebook

Section 82: NumPy - Creating Arrays

Lecture 401 Introduction to NumPy and Creating One-Dimensional Arrays

Lecture 402 Two-Dimensional Arrays in NumPy

Lecture 403 Understanding Axes in NumPy

Lecture 404 Arithmetic Operations with NumPy Arrays

Lecture 405 Concatenating NumPy Arrays

Lecture 406 Summary of Basic Operations with NumPy Arrays

Section 83: NumPy - Random Values

Lecture 407 Filling a NumPy Array with Zeroes, Ones, or Random Floats

Lecture 408 Generating Random Elements Using randint and uniform

Lecture 409 Understanding Seed Number

Lecture 410 NumPy arange, reshape, and flatten Methods

Section 84: NumPy - Examples

Lecture 411 NumPy Examples 1 and 2 (One-Dimensional Array)

Lecture 412 NumPy Examples 3 and 4 (One-Dimensional Array)

Lecture 413 NumPy Example 5 (Two-Dimensional Array)

Lecture 414 NumPy Example 6 (Two-Dimensional Array)

Lecture 415 NumPy Example 7 (Three-Dimensional Array)

Lecture 416 NumPy Summary

Section 85: Pandas - Working with DataFrames and Series

Lecture 417 Introduction to Pandas and Installation

Lecture 418 Creating a DataFrame from a Dictionary

Lecture 419 Basic Operations with DataFrame

Lecture 420 Describing the DataFrame

Lecture 421 Finding Null Values in the DataFrame

Lecture 422 Finding Columns with Specific Data Type

Lecture 423 Series Data Structure in Pandas

Lecture 424 Selecting Part of the DataFrame Using loc and iloc Properties

Lecture 425 Filtering Data in the DataFrame

Lecture 426 Datetime Type in Pandas

Lecture 427 Sorting Data in the DataFrame

Lecture 428 Adding and Removing Columns and Concatenating DataFrames

Lecture 429 Summary of Pandas DataFrames and Series

Section 86: Pandas - Random Data and Working with CSV

Lecture 430 Generating Random Data for DataFrames

Lecture 431 Creating a DataFrame Using Random Data

Lecture 432 Saving DataFrames to CSV Files

Lecture 433 Creating DataFrames from CSV Files

Lecture 434 Writing DataFrames to Excel and JSON Files

Section 87: Pandas - Analysing CSV-Loaded DataFrames

Lecture 435 Analyzing CSV-Loaded DataFrames

Lecture 436 Grouping Data in DataFrames

Lecture 437 Displaying Series Data on Plots Using Matplotlib

Lecture 438 Summary of Example with Random CSV Data

Section 88: Matplotlib - Creating Charts

Lecture 439 Examples of Plot and Scatter Diagrams Using Matplotlib

Lecture 440 Examples of Matplotlib Subplots

Lecture 441 Using DataFrames for Creating Diagrams

Lecture 442 Boxplots, Area Plots, and Pie Charts

Lecture 443 Example of a Heatmap in Matplotlib

Lecture 444 Displaying Real-World Data on Various Charts

Section 89: Scikit-learn - Machine Learning

Lecture 445 Introduction to Scikit-Learn and Installation

Lecture 446 Loading and Analyzing Sample Data for Model Creation

Lecture 447 Handling Null Values in DataFrame

Lecture 448 Attempting to Create a Model for Predicting Target Values

Lecture 449 Encoding Non-Numeric Values in Input Data

Lecture 450 Building and Predicting with Cleaned and Encoded Data

Lecture 451 Summary of Model for Predicting Favorite Transport

Lecture 452 Visualizing DecisionTreeClassifier Model

Lecture 453 Creating Charts for Data from the Built Model

Lecture 454 Evaluating Model Accuracy

Section 90: Machine Learning Model for Real Data

Lecture 455 Loading CSV File with Airline Passenger Satisfaction Data

Lecture 456 Analyzing DataFrame with Passenger Satisfaction Data

Lecture 457 Filling Null Values with Mean Value

Lecture 458 Creating Diagrams for Passenger Data Analysis

Lecture 459 Manually Encoding Non-Numeric Values in DataFrame

Lecture 460 Encoding Non-Numeric Values Using LabelEncoder

Lecture 461 Creating Additional Diagrams After Data Cleaning and Encoding

Lecture 462 Filtering DataFrame with Passenger Data

Lecture 463 Using DecisionTreeClassifier for Model Creation

Lecture 464 Measuring Model Accuracy with DecisionTreeClassifier

Lecture 465 Using Other Classifiers for Model Creation

Lecture 466 Summary of Airline Passenger Satisfaction Project

Section 91: Making Machine Learning Model More Real

Lecture 467 Removing Passenger Votes from DataFrame

Lecture 468 Saving Trained Model for Future Use

Lecture 469 Summary of Realistic Model for Passenger Satisfaction Prediction

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