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Python - Complete Python, Django, Data Science And Ml Guide - Panter - 15.01.2024

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Python - Complete Python, Django, Data Science And Ml Guide
Last updated 8/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 22.74 GB | Duration: 50h 27m

Learn the most popular Python programming language including Django, Pygame, Jupyter, Data Science and Machine Learning

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: Understand error handling mechanisms in Python 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. As 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: Course and Project Files

Lecture 7 Download Project Files

Section 4: Basic Concepts in Python

Lecture 8 Key Concept in Python

Lecture 9 Main Data Types in Python

Lecture 10 Practice - Working with Main Data Types

Section 5: Introduction to Functions and Built-in Functions in Python

Lecture 11 Built-in Functions

Lecture 12 Practice - Defining and Using Functions

Lecture 13 Practice - Using the Return Statement in Functions

Lecture 14 Practice - Exploring Built-in Functions

Lecture 15 Practice - Using the built-in dir() Function

Lecture 16 Practice - Gathering User Input with the built-in input() Function

Section 6: Code Formatting and PEP8

Lecture 17 Code Indentations

Lecture 18 Practice - Working with Indentations

Lecture 19 Following PEP 8 Guidelines

Lecture 20 Enabling Auto-Formatting in PyCharm

Section 7: Comments

Lecture 21 Comments

Lecture 22 Practice - Adding Comments to Your Code

Section 8: Expressions and Instructions

Lecture 23 Understanding Expressions

Lecture 24 Understanding Statements

Lecture 25 Practice - Using Expressions

Lecture 26 Practice - Using Statements

Section 9: Variables

Lecture 27 Variables

Lecture 28 Practice - Defining and Using Variables

Section 10: Data Types and Structures

Lecture 29 Understanding Dynamic Typing

Lecture 30 Types and Data Structures Overview

Lecture 31 Variables and Objects

Lecture 32 Practice - Using the built-in id() Function

Lecture 33 Practice - Exploring Core Data Classes (str, int, bool, list, dict)

Lecture 34 Practice - Using the built-in isinstance() Function

Section 11: Strings

Lecture 35 Strings

Lecture 36 Practice - String Manipulation

Lecture 37 Practice - String Methods

Section 12: String Concatenation

Lecture 38 String Concatenation

Lecture 39 Practice - Concatenating Strings using the + Operator

Lecture 40 Practice - Using f-strings for String Formatting

Lecture 41 Practice - Alternative String Formatting Methods

Section 13: Numeric Types

Lecture 42 Integers

Lecture 43 Practice - Integers Manipulation

Lecture 44 Float Numbers

Lecture 45 Practice - Floating-Point Numbers Manipulation

Lecture 46 Working with Complex Numbers

Section 14: Boolean Type

Lecture 47 Boolean Values

Lecture 48 Practice - Working with Boolean Values

Lecture 49 Type Conversion

Section 15: Magic Methods

Lecture 50 Magic Methods

Lecture 51 Practice - Utilizing Magic Attributes and Methods

Section 16: Lists

Lecture 52 Lists

Lecture 53 List Methods

Lecture 54 Practice - Working with Lists

Lecture 55 Copying Lists

Lecture 56 Practice - Copying Lists

Lecture 57 TASK - Working with Lists

Section 17: Dictionaries

Lecture 58 Dictionaries

Lecture 59 Practice - Manipulating Dictionaries

Lecture 60 Practice - Dictionary Methods

Lecture 61 Other Operations with Dictionaries

Lecture 62 Practice - Using the get() Method for Dictionaries

Lecture 63 Practice - Converting Other Types to a Dictionary

Lecture 64 TASK - Working with Dictionaries

Section 18: Tuples

Lecture 65 Tuples

Lecture 66 Practice - Tuples Manipulation

Section 19: Sets

Lecture 67 Sets

Lecture 68 Practice - Working with Sets

Lecture 69 Understanding Set Theory

Lecture 70 Set Methods

Lecture 71 Practice - Usage of the Set Methods

Lecture 72 Practice - Calculating Symmetric Difference of Sets

Lecture 73 TASK - Working with Sets

Section 20: Ranges

Lecture 74 Ranges

Lecture 75 Practice - Range Manipulation

Lecture 76 Practice - Range Methods and Attributes

Section 21: Working with Sequences

Lecture 77 Built-in Functions for Sequences

Lecture 78 Built-in zip() Function

Lecture 79 Practice - Working with zip Objects

Lecture 80 Practice - Converting a zip Object to a Dictionary

Lecture 81 Comparison of Different Sequences

Section 22: Modifying Objects in Python

Lecture 82 Understanding Immutable Objects in Python

Lecture 83 Understanding Mutable Objects in Python

Lecture 84 Strategies to Prevent Object Mutation

Lecture 85 Practice - Creating Deep Copies of Objects

Section 23: Functions

Lecture 86 Functions

Lecture 87 Calling Functions: Arguments vs Parameters

Lecture 88 Shortest Function in Python

Section 24: Function Arguments

Lecture 89 Mutable and Immutable Arguments in Function Calls

Lecture 90 Practice - Using Mutable and Immutable Objects as Function Arguments

Lecture 91 Practice - Mandatory and Optional Positional Arguments

Lecture 92 TASK - Functions Manipulation

Lecture 93 Function Arguments

Section 25: Args and kwargs in Functions

Lecture 94 Practice - Using *args to Gather Positional Arguments into a Tuple

Lecture 95 Keyword Arguments

Lecture 96 Practice - Working with Keyword Arguments

Lecture 97 Practice - Using **kwargs to Merge Keyword Arguments in a Dictionary

Lecture 98 TASK - Manipulating Function Arguments

Lecture 99 Args and kwargs

Lecture 100 Practice - Gathering Positional Arguments into the *args Tuple

Lecture 101 Practice - Gathering All Keyword Arguments into the **kwargs Dictionary

Section 26: Default Function Parameters

Lecture 102 Default Function Parameters

Lecture 103 Practice - Using Default Function Parameters

Section 27: Docstrings

Lecture 104 Docstrings

Lecture 105 Practice - Writing and Using Docstrings

Lecture 106 Practice - Exploring Docstrings

Lecture 107 Practice - Adding Docstrings to Functions

Section 28: Callback Functions

Lecture 108 Callback Functions

Lecture 109 Rules for Working with Functions

Section 29: Global and Local Variables

Lecture 110 Scopes

Lecture 111 The Global Keyword

Lecture 112 Practice - Global and Local Variables

Lecture 113 Practice - Using the Global Keyword

Section 30: Operators

Lecture 114 Operators

Lecture 115 Unary and Binary Operators

Lecture 116 Practice - Working with Prefix Unary Operators

Lecture 117 TASK - Operators

Section 31: Falsy and Truthy Values

Lecture 118 Falsy and Truthy Values

Lecture 119 Practice - Falsy and Truthy Values

Section 32: Logical and Comparison Operators

Lecture 120 Logical Operators

Lecture 121 Practice - Short-Circuit OR Operator

Lecture 122 Practice - Short-Circuit AND Operator

Lecture 123 Practice - Combining OR and AND Operators

Lecture 124 Practice - Examples with Logical Operators

Lecture 125 Practice - Comparison Operators

Lecture 126 The del Statement

Section 33: Lambda Functions

Lecture 127 Lambda Functions

Lecture 128 Practice - Returning Lambda Functions from Functions

Lecture 129 Practice - Sorting a List using Lambda Functions

Lecture 130 Practice - Filtering a List using Lambda Functions

Section 34: Error Handling

Lecture 131 Error Handling

Lecture 132 Practice - Using Different Error Classes in the Try and Except

Lecture 133 Practice - Using Multiple Error Classes in one Except Block and Parent Exception

Lecture 134 Practice - Using Else and Finally Blocks

Lecture 135 Example - Handling File Not Found Errors

Lecture 136 Example - Handling Undefined Variable Errors

Lecture 137 Practice - Raising Custom Errors

Lecture 138 Practice - Handling Raised Errors using Try and Except

Lecture 139 Practice - Specifying Types for Function Parameters

Lecture 140 TASK - Proper Error Handling

Section 35: Sequence Unpacking

Lecture 141 Sequence Unpacking

Lecture 142 Practice - Unpacking Tuples

Lecture 143 Practice - Unpacking a List of Tuples

Lecture 144 Practice - Unpacking Remaining Elements

Lecture 145 Practice - Unpacking Selected Elements

Lecture 146 Practice - Unpacking a List into Positional Arguments

Lecture 147 Practice - Unpacking a Dictionary into Keyword Arguments

Lecture 148 Practice - Flexibility in Function Calls

Section 36: Unpacking Dictionaries

Lecture 149 Dictionary Unpacking Operator **

Lecture 150 Practice - Using the Dictionary Unpacking Operator

Lecture 151 Practice - Merging Two Dictionaries

Section 37: Conditional Statements

Lecture 152 Conditional Statements

Lecture 153 Practice - Working with Multiple if Statements

Lecture 154 The if-else Statement

Lecture 155 The if-elif Statement

Lecture 156 Practice - Combining if, elif, and else Statements

Lecture 157 Practice - Considering the Order of Conditions in if Statements

Lecture 158 Practice - Incorporating if Statements into Functions

Lecture 159 Practice - Using if and return Statements within Functions

Lecture 160 Example - Calculating School Grades using if and return in the Function

Lecture 161 TASK - Conditional Statements

Section 38: Ternary Operator

Lecture 162 Ternary Operator

Lecture 163 Practice - Utilizing the Ternary Operator

Lecture 164 Example - Calculating Discounts with the Ternary Operator

Lecture 165 Example - Data Manipulation using the Ternary Operator

Lecture 166 Example - Calculating School Grades using the Ternary Operator

Section 39: For-In Loop

Lecture 167 Loops

Lecture 168 For-In Loop

Lecture 169 Practice - Iterating through Lists and Tuples using For-In Loops

Lecture 170 Practice - Iterating through Dictionaries using For-In Loops

Lecture 171 Practice - Iterating through Ranges, Strings, and Sets with For-In Loops

Lecture 172 TASKS - Working with For-In Loops

Section 40: While Loop

Lecture 173 While Loop

Lecture 174 Practice - Utilizing the While Loop

Lecture 175 Example - Making Selections with the While Loop

Lecture 176 Practice - Using break Statements in While and For-In Loops

Lecture 177 Practice - Using continue and break Statements in While Loops

Lecture 178 TASK - While Loop

Section 41: For-In Expression (Comprehensions)

Lecture 179 For-In Expression

Lecture 180 List, Set, and Dictionary Comprehensions

Lecture 181 Practice - Using List Comprehension

Lecture 182 Practice - Using Dictionary Comprehension

Lecture 183 Practice - Utilizing Tuple Comprehension

Lecture 184 Practice - Converting Tuples to Lists

Lecture 185 Example - Constructing Dictionaries from Sequences

Lecture 186 Practice - Short For-In Loops with Conditional Statements

Lecture 187 Example - Converting Dictionary to Another Dictionary

Lecture 188 TASKS - Short For-In Loops

Lecture 189 Example - Chaining For-In Expressions

Section 42: Generators

Lecture 190 Generators in For-In Expressions

Lecture 191 Practice - Generators and Iteration over the Generator

Section 43: Decorator Functions

Lecture 192 Introduction to Decorator Functions

Lecture 193 Example - Verifying User Permissions with Decorator Functions

Lecture 194 Example - Logging using Decorator Functions

Lecture 195 Example - Validating Arguments with Decorator Functions

Section 44: Objects and Classes

Lecture 196 Classes and Objects

Lecture 197 Practice - Understanding Classes and Class Instances

Lecture 198 Practice - Adding Instance Attributes through Dot Notation

Lecture 199 Adding Instance Attributes using the __init__ Method

Lecture 200 Practice - Incorporating Own Instance Attributes with the __init__ Method

Section 45: Instance and Class Methods

Lecture 201 Instance vs Class Methods

Lecture 202 Practice - Inheriting Methods by the Instances

Lecture 203 Static Class Methods

Lecture 204 Practice - Utilizing Static Methods in Classes

Lecture 205 Class Attributes

Lecture 206 Practice - Working with Class Attributes

Section 46: Magic Methods in Classes

Lecture 207 Magic Methods in Classes

Lecture 208 Practice - Utilizing Magic Methods in Classes

Section 47: Classes Extension

Lecture 209 Inheritance from Other Classes

Lecture 210 Practice - Extending Classes

Section 48: Classes on Practice

Lecture 211 Example - Creating Forum, User, and Post Classes

Lecture 212 Example - Creating Instances of the Forum, User, and Post Classes

Lecture 213 Example - Methods for Finding Users by Username and Email

Lecture 214 Example - Method for Finding All Posts by a Specific User

Lecture 215 Example - Retrieving User Posts by Email

Lecture 216 Example - Adding Parameter Types

Lecture 217 Example - Wrapping up the Forum, Users, and Posts Example

Section 49: Key Principles in Object-Oriented Programming

Lecture 218 Encapsulation in Object-Oriented Programming (OOP)

Lecture 219 Inheritance in Object-Oriented Programming (OOP)

Lecture 220 Polymorphism in Object-Oriented Programming (OOP)

Lecture 221 Abstraction in Object-Oriented Programming (OOP)

Section 50: Modules

Lecture 222 Modules

Lecture 223 Practice - Importing Entire Custom Modules

Lecture 224 Practice - Selective Imports from Other Modules

Lecture 225 Practice - Importing between Different Modules

Lecture 226 Practice - Modules in Subfolders

Section 51: Built-in Modules

Lecture 227 Built-in Modules

Lecture 228 Practice - Importing from Built-in Modules

Section 52: What is __name__ and __main__

Lecture 229 Practice - __name__ and __main__

Lecture 230 Example - Executing Functions only when Module is run Directly

Lecture 231 Practice - Packages in Python

Section 53: JavaScript Object Notation (JSON)

Lecture 232 JavaScript Object Notation (JSON)

Lecture 233 Practice - Converting Python Objects to JSON

Lecture 234 Practice - Converting from JSON to Python Objects

Lecture 235 Practice - Formatting Dictionaries using JSON

Lecture 236 TASKS - JSON

Section 54: Working with Files

Lecture 237 Working with Files

Lecture 238 Working with Files and Directories using the os Module

Lecture 239 Removing Files and Directories using the os Module

Lecture 240 Summary of Directory and File Operations using the os Module

Lecture 241 Working with Files and Directories using the Path Class

Lecture 242 Iterating over Directories and Removing Files using the Path Class

Lecture 243 Reading and Writing Files

Lecture 244 Writing and Reading Files using the built-in open Function

Lecture 245 Using the with Statement

Lecture 246 Removing Files using unlink

Lecture 247 TASK - Files

Section 55: Working with Zip Archives

Lecture 248 Built-in zipfile Module and Creating Zip Archives

Lecture 249 Reading from the Zip Archive

Section 56: Working with CSV Files

Lecture 250 Working with CSV Files

Lecture 251 Iterating over Each Row in the CSV File

Section 57: Working with Dates and Times

Lecture 252 Built-in datetime Module

Lecture 253 Examples - Using the datetime Class

Lecture 254 Examples - Converting Strings to Datetime Objects

Lecture 255 Example - Working with the timedelta Class

Lecture 256 Built-in time Module

Section 58: Generating Random Sequences and Passwords

Lecture 257 Built-in random Module

Lecture 258 Examples - Utilizing choices and shuffle Methods from the random Module

Lecture 259 Built-in secrets Module

Lecture 260 Examples - Generating CSRF Tokens, URL-Safe Tokens, and OTP Passwords

Lecture 261 Example - Generating Strong Passwords

Section 59: Math Module and Recursive Functions

Lecture 262 Built-in math Module

Lecture 263 Recursive Functions

Section 60: Regular Expressions

Lecture 264 Built-in re Module for Regular Expressions

Lecture 265 Example - Creating Patterns for Matching

Lecture 266 Example - Email Validation using Regular Expressions

Lecture 267 Example - Substring Replacement using Regular Expressions

Lecture 268 Example - Removing Excessive Spaces using Regular Expressions

Lecture 269 TASK - Password Verification

Section 61: Sending Emails

Lecture 270 Running smtp4dev SMTP server in a Docker Container

Lecture 271 Sending an Email using SMTP

Lecture 272 Formatting an Email using an HTML Template

Lecture 273 SMTP Wrap-Up and Removing the Docker smtp4dev Container

Section 62: Working with SQLite Database

Lecture 274 Creating an SQLite3 Database and Table

Lecture 275 Writing Data into the SQLite Table

Lecture 276 Reading Data from the SQLite Table

Lecture 277 SQLite Summary

Section 63: Other Built-in Modules

Lecture 278 Built-in array Module

Lecture 279 Saving Arrays to Files and Reading Arrays from Files

Lecture 280 Accessing Program Arguments using the built-in sys Module

Lecture 281 Built-in webbrowser Module

Section 64: Virtual Environments

Lecture 282 Introduction to PIP - Package Manager for Python

Lecture 283 Using a Globally Installed requests Package

Lecture 284 Uninstalling Globally Installed Packages using PIP

Lecture 285 Creating a Python Virtual Environment

Lecture 286 Activation and Deactivation of the Virtual Environment in the Shell

Lecture 287 Installing Packages within the Virtual Environment

Lecture 288 Saving a List of Installed Packages in a Requirements Text File

Lecture 289 Challenges of Package Management using Requirements Files

Section 65: Pipenv for Virtual Environments Management

Lecture 290 Installing pipenv for Virtual Environments Management

Lecture 291 Creating a Virtual Environment using pipenv

Lecture 292 Installing Packages using pipenv

Lecture 293 Updating Packages using pipenv

Lecture 294 Recreating Virtual Environment in the Project Folder using pipenv

Lecture 295 Using venv for Virtual Environments in PyCharm

Lecture 296 Using pipenv for Virtual Environments in PyCharm

Section 66: Introduction to the Django Web Framework

Lecture 297 Introduction to the Django Web Framework and Project Overview

Lecture 298 Model View Controller (MVC) Programming Pattern

Lecture 299 Understanding How MVC Pattern is Implemented in Django

Lecture 300 Creating a New PyCharm Project and Installing Django

Section 67: Creating a Django Project

Lecture 301 Creating a New Django Project

Lecture 302 Overview of the manage.py File in Django

Lecture 303 Starting and Verifying the Django Server

Lecture 304 Overview of Settings in the Django Project

Lecture 305 Overview of Default Routing Configuration in Django

Section 68: Creating a Django Application

Lecture 306 Creating the Shop Application in Django

Lecture 307 Explaining the Naming of the Django Project as "base"

Lecture 308 Exploring the Contents of the Shop Application

Lecture 309 Creating a View Function

Lecture 310 Attaching the View Function to a URL

Lecture 311 Adding Shop Application Routes to the Global Project Routing Configuration

Section 69: Database and Migrations in Django

Lecture 312 Applying Default Migrations in the Django Project

Lecture 313 Creating an Admin User in the Django Project

Lecture 314 Creating Course and Category Models

Lecture 315 Enabling the Shop Application in the Django Project

Lecture 316 Creating and Applying Migrations for the Shop Application

Lecture 317 Modifying Database Models

Lecture 318 Creating a Category using the Category Model in the Shell

Lecture 319 Creating Courses using the Course Model in the Shell

Lecture 320 Creating Categories and Courses in the Admin Interface

Lecture 321 Modifying How Courses and Categories are Displayed in the Admin Panel

Lecture 322 Sending Course Titles to the Client in the Response

Section 70: Creating Templates in Django

Lecture 323 Creating an HTML Template

Lecture 324 Using an HTML Template in the View Function

Lecture 325 Populating the HTML Template with Data from the Database

Lecture 326 How we Connected Templates, Views, and Models

Lecture 327 Adding the Bootstrap CSS Library to the HTML Template

Section 71: Extending Other Templates in Django

Lecture 328 Creating a Base HTML Template for Reuse in Other Templates

Lecture 329 Adding a Navigation Bar in the Base Template

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

Lecture 331 SOLUTION - Making the Title of the Web Page Dynamic

Section 72: Creating Multiple Routes and View Functions

Lecture 332 Creating a Route for the Single Course Web Page

Lecture 333 Creating a View Function for the Single Course

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

Lecture 335 SOLUTION - Creating an HTML Template for the Single Course

Lecture 336 Responding with a 404 When Course is Not Found in the Database

Section 73: Routing Between Pages in Django

Lecture 337 Setting Up Routing Between Pages Using Relative or Absolute Paths

Lecture 338 Setting Up Routing Based on the Names of the URL Patterns

Lecture 339 Considering Application Names in the Routing Setup

Lecture 340 Adding a Link to the All Courses Page

Lecture 341 Moving the Templates Folder Out of the Shop Application Folder

Lecture 342 Modifying the Model for the Courses

Lecture 343 Summary of the Django Shop Application

Lecture 344 Installing django-tastypie for the API Django Application

Section 74: Creating an API Django Application

Lecture 345 Creating an API Django Application

Lecture 346 Creating Models for the API Application

Lecture 347 Configuring Routing for the API Application

Lecture 348 Verifying the API Service

Lecture 349 Adding Version for the API

Lecture 350 Installing Postman and Sending GET and DELETE Requests

Section 75: Managing Authentication for API Requests

Lecture 351 Creating an API Key for the User

Lecture 352 Enabling Authentication and Authorization for the Model and Using DELETE Method

Lecture 353 Disabling Authentication Only for GET Requests

Lecture 354 Creating a New Resource Using POST Method

Lecture 355 Properly Connecting the Course to the Category in POST Requests Using Hydrate Me

Lecture 356 Adding Dehydrate Method to Modify Data Before Sending to Client

Lecture 357 Summary for Setting Up GET, POST, and DELETE Requests

Section 76: Django Project Refactoring and Admin Settings

Lecture 358 Refactoring Routing for the API Application

Lecture 359 Setting Up Index Route and Adding Navigation to Navbar

Lecture 360 Modifying Administrative Panel

Lecture 361 Summary of Django Courses Project

Section 77: Creating Games with Pygame

Lecture 362 Introduction to Pygame and Creating the Game Window

Lecture 363 Modifying Background Color of the Game Surface

Lecture 364 Displaying a Rectangle in the Game

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

Lecture 366 SOLUTION - Placing Rectangle in the Middle of the Game Window

Lecture 367 Moving Rectangle Using Keyboard Arrows

Lecture 368 Stopping Rectangle from Moving Outside of the Surface

Section 78: Creating a Shooter Game with Pygame

Lecture 369 Final Shooter Game Overview

Lecture 370 Loading Images for the Game and Fighter

Lecture 371 Displaying Fighter on the Surface

Lecture 372 Moving Fighter Left or Right

Lecture 373 Making Fighter Movement Continuous

Lecture 374 Adding the Ball to the Game

Lecture 375 Showing Ball Based on Fighter Position

Lecture 376 Moving the Ball After Firing

Lecture 377 Adding the Alien to the Game

Lecture 378 Moving the Alien Down the Surface

Section 79: Interaction of the Elements in the Pygame

Lecture 379 Detecting Collision Between Alien and Fighter, Ending the Game

Lecture 380 Hitting the Alien with the Ball

Lecture 381 Increasing Alien Speed After Each Hit

Lecture 382 Adding Hit Counter

Lecture 383 Shooter Game Summary

Section 80: Game Refactoring using Classes and OOP

Lecture 384 Start of Shooter Refactoring and Creating the Fighter Class

Lecture 385 Adding Methods in the Fighter Class

Lecture 386 Creating an Alien Class

Lecture 387 Adding Methods in the Alien Class

Lecture 388 Creating a Ball Class

Lecture 389 Adding Methods in the Ball Class

Lecture 390 Creating a Game Class

Lecture 391 Adding Methods in the Game Class

Lecture 392 Adding Methods for Drawing Elements and Finalizing Refactoring

Lecture 393 Game Refactoring Summary

Lecture 394 Running the Game After Refactoring

Section 81: Jupyter Notebook

Lecture 395 Installing Jupyter Notebook

Lecture 396 Editing in Jupyter Notebook

Lecture 397 Order of Execution of Cells in Jupyter Notebook

Lecture 398 Adding Markdown, Saving, and Loading Jupyter Notebooks

Section 82: Jupyter Lab

Lecture 399 Installing Jupyter Lab and Editing Notebooks

Lecture 400 Exploring Features of Jupyter Lab

Lecture 401 Installing External Packages in Jupyter Notebook

Section 83: NumPy - Creating Arrays

Lecture 402 Introduction to NumPy and Creating One-Dimensional Arrays

Lecture 403 Two-Dimensional Arrays in NumPy

Lecture 404 Understanding Axes in NumPy

Lecture 405 Arithmetic Operations with NumPy Arrays

Lecture 406 Concatenating NumPy Arrays

Lecture 407 Summary of Basic Operations with NumPy Arrays

Section 84: NumPy - Random Values

Lecture 408 Filling a NumPy Array with Zeroes, Ones, or Random Floats

Lecture 409 Generating Random Elements Using randint and uniform

Lecture 410 Understanding Seed Number

Lecture 411 NumPy arange, reshape, and flatten Methods

Section 85: NumPy - Examples

Lecture 412 NumPy Examples 1 and 2 (One-Dimensional Array)

Lecture 413 NumPy Examples 3 and 4 (One-Dimensional Array)

Lecture 414 NumPy Example 5 (Two-Dimensional Array)

Lecture 415 NumPy Example 6 (Two-Dimensional Array)

Lecture 416 NumPy Example 7 (Three-Dimensional Array)

Lecture 417 NumPy Summary

Section 86: Pandas - Working with DataFrames and Series

Lecture 418 Introduction to Pandas and Installation

Lecture 419 Creating a DataFrame from a Dictionary

Lecture 420 Basic Operations with DataFrame

Lecture 421 Describing the DataFrame

Lecture 422 Finding Null Values in the DataFrame

Lecture 423 Finding Columns with Specific Data Type

Lecture 424 Series Data Structure in Pandas

Lecture 425 Selecting Part of the DataFrame Using loc and iloc Properties

Lecture 426 Filtering Data in the DataFrame

Lecture 427 Datetime Type in Pandas

Lecture 428 Sorting Data in the DataFrame

Lecture 429 Adding and Removing Columns and Concatenating DataFrames

Lecture 430 Summary of Pandas DataFrames and Series

Section 87: Pandas - Random Data and Working with CSV

Lecture 431 Generating Random Data for DataFrames

Lecture 432 Creating a DataFrame Using Random Data

Lecture 433 Saving DataFrames to CSV Files

Lecture 434 Creating DataFrames from CSV Files

Lecture 435 Writing DataFrames to Excel and JSON Files

Section 88: Pandas - Analysing CSV-Loaded DataFrames

Lecture 436 Analyzing CSV-Loaded DataFrames

Lecture 437 Grouping Data in DataFrames

Lecture 438 Displaying Series Data on Plots Using Matplotlib

Lecture 439 Summary of Example with Random CSV Data

Section 89: Matplotlib - Creating Charts

Lecture 440 Examples of Plot and Scatter Diagrams Using Matplotlib

Lecture 441 Examples of Matplotlib Subplots

Lecture 442 Using DataFrames for Creating Diagrams

Lecture 443 Boxplots, Area Plots, and Pie Charts

Lecture 444 Example of a Heatmap in Matplotlib

Lecture 445 Displaying Real-World Data on Various Charts

Section 90: Scikit-learn - Machine Learning

Lecture 446 Introduction to Scikit-Learn and Installation

Lecture 447 Loading and Analyzing Sample Data for Model Creation

Lecture 448 Handling Null Values in DataFrame

Lecture 449 Attempting to Create a Model for Predicting Target Values

Lecture 450 Encoding Non-Numeric Values in Input Data

Lecture 451 Building and Predicting with Cleaned and Encoded Data

Lecture 452 Summary of Model for Predicting Favorite Transport

Lecture 453 Visualizing DecisionTreeClassifier Model

Lecture 454 Creating Charts for Data from the Built Model

Lecture 455 Evaluating Model Accuracy

Section 91: Machine Learning Model for Real Data

Lecture 456 Loading CSV File with Airline Passenger Satisfaction Data

Lecture 457 Analyzing DataFrame with Passenger Satisfaction Data

Lecture 458 Filling Null Values with Mean Value

Lecture 459 Creating Diagrams for Passenger Data Analysis

Lecture 460 Manually Encoding Non-Numeric Values in DataFrame

Lecture 461 Encoding Non-Numeric Values Using LabelEncoder

Lecture 462 Creating Additional Diagrams After Data Cleaning and Encoding

Lecture 463 Filtering DataFrame with Passenger Data

Lecture 464 Using DecisionTreeClassifier for Model Creation

Lecture 465 Measuring Model Accuracy with DecisionTreeClassifier

Lecture 466 Using Other Classifiers for Model Creation

Lecture 467 Summary of Airline Passenger Satisfaction Project

Section 92: Making Machine Learning Model More Real

Lecture 468 Removing Passenger Votes from DataFrame

Lecture 469 Saving Trained Model for Future Use

Lecture 470 Summary of Realistic Model for Passenger Satisfaction Prediction

Beginning Python programmers who want to learn how to program,Those who are planning to work in the direction of Data Science and Machine Learning,Web developers who want to build web applications with Python,Those who want to perform tasks related to machine learning, data processing,Game developers who want to create games with Python Pygame

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