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Python - Complete Python, Django, Data Science And Ml Guide - SKIKDA - 08-23-2023 Published 8/2023 MP4 | Video: h264, 1280x720 | 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 Buy Premium Account From My Download Links & Get Fastest Speed. |