Python – Complete Python, Django, Data Science And Ml Guide

Free Download Python – Complete Python, Django, Data Science And Ml Guide
Published 8/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 27.45 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 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
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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