1. Programming with Python: Basics and Environment Setup

• What Is Programming?
• Setting Up IDE

2. Data Types and Variables FREE CHAPTER

• Data Types in Python
• Variables
• Variable Names

3. Text Data Types

• Python Strings
• Extracting Values from Strings: Strings, Slicing, and Indicing
• String Built-In Functions

4. Numeric Data Types

• Numbers in Python
• Numeric Functions

5. Boolean

• Python Booleans

6. Lists

• Python Lists
• List Built-In Functions

7. Tuples

• Python Tuples
• Tuple Operations and Tuple Built-In Functions

8. Sets

• Pythons Sets
• Sets Built-In Functions
• Mathematical Sets Operations

9. Dictionary

• Python Dictionaries
• Dictionary Built-In Functions

10. Decision Control in Python

• Decision Control using if statements
• Creating conditions Using or and and keywords
• elif Statements
• else Statements
• Decision Control with Strings and Lists

11. Loops in Python

• Creating Loops Using While Statements

12. Iterating over Elements

• Iterating over Datatypes Using For Loops

13. Functions

• Functions in Python and Defining Our Own
• Getting Arguments during Function Call
• Positional and Keyword Arguments
• Arguments and Parameters
• Arbitrary Arguments (*args)
• Arbitrary Keyword Arguments (**kwargs)
• Return Values from User-Defined Functions Using the Return Keyword
• Pass Keywords for Functions
• Lambda Functions
• Creating a Duplicate List Elements Remover Function
• Redefining the Built-In type( ) Function
• Creating a Function to Smartly Round Decimal Points in a Result of Addition

14. Object-Oriented Programming

• What Are Classes and How to Create Them
• Defining Class Methods
• Adding, Modifying, and Deleting Class Attributes
• Class Attributes and Identifier Naming Convention
• Functions Versus Class Methods
• Operator Overloading on User-Defined Classes
• Built-Ins Overloading on User-Defined Classes
• Creating User-Defined Iterable Classes

15. Inheritance

• Containership
• Inheritance
• Accessing Inherited Objects
• The Object Class
• Multi-Level Inheritance
• Multiple Inheritance

16. Dealing with Errors

• Error Handling in Python
• User-Defined Errors
• Catching Errors with Except Block
• Use of else and finally Blocks

17. Modules and Packages

• Modules and Packages
• random Module
• datetime Module

18. All Built-In Functions

• abs( )
• all( )
• any( )
• ascii( )
• bin( )
• callable( )
• compile( ), exec( ), and eval( )
• delattr( )
• dir( )
• enumerate( )
• filter( )
• format( )
• getattr( )
• globals( )
• hasattr( )
• hash( )
• help( )
• hex( )
• id( )
• input( )
• isinstance( )
• issubclass( )
• iter( ) and next( )
• locals( )
• map( )
• oct( )
• open( )
• print( )
• range( )
• repr( )
• reversed( )
• setattr( )
• vars( )
• zip( )

19. PyCharm IDE

• Creating Files in PyCharm
• Editing the Themes and Color Schemes
• Keymapping Shortcuts
• Executing Python Programs

20. Advanced Level: Python GUI

• GUI Introduction
• Creating GUI Application Tk( ) Windows and Widgets
• Creating Button Widgets
• Getting Input from the User Using Entry Field Widgets
• Using Grid System to Place Widgets
• Button States
• Customizing Colors and Fonts
• Adding Color Theme to Your Applications
• Stylizing the Appearance of the Widgets (Relief)
• Creating Checkbox Widgets
• Creating Radio Button Widgets
• Creating Slider Widgets
• Creating Dropdown Menu widgets
• Adding more windows on top of our existing main window
• Working with Images
• File Dialog Boxes for Application

21. Applications with Python GUI

• Dice Roller
• Age Calculator (Total Days and Seconds Lived)
• Length Converter Applications
• Image to Icon Converter

22. Advanced Level: Data Science

• Data Science with Python
• Anaconda
• Jupyter Notebook
• Data Processing with NumPy Package
• Pandas Series
• n-darrays to Pandas Series
• Slicing Values from Pandas Series
• Pandas DataFrames
• Slicing Columns, Rows, and Values from Pandas DataFrames
• Matplotlib Library
• Data Processing
• Data Cleaning
• Data Analysis
• Data Visualization
• Customizing Visualizations with Matplotlib
• Different Types of Plots with Matplotlib

23. Data Science Project 1

• Inspecting the Data
• Importing the Data
• Data Processing and Cleaning
• Data Analysis
• Data Visualization
• Generating the Final Report

24. eBook Web Store

• Web Development with Python and Django
• How Websites Work and How We Can Create One?
• Starting Our Website Project with Django
• Customizing the Homepage View
• HTML Basics
• Admin Application and Creating Our Own Applications
• Creating Our Store View
• Creating Models and Storing eBooks in the Database
• Adding eBooks Through the Admin Application
• Django Template and Context System for html Views
• Web Design: Stylizing Our html Tags with CSS
• Bootstrap as Base Template
• Adding Bootstrap Cards as eBooks in Our Store Webpage
• Adding Bootstrap Navigation Bar to Our Website
• Adding the Cart to Our Website
• Bootstrap Containers
• Creating Model for Cart Items
• Getting Book ID from the Add to Cart Button
• Defining add_to_cart( ) View Function
• Displaying the Cart Sub-Total
• Adding a Delete Button to Cart Items
• Defining del_cart_item( ) View Function
• What to Display When the Cart Is Empty?
• Using Bootstrap Icons for html Elements

25. Machine Learning with Python

• What Is Machine Learning?
• How Machines Learn
• Creating a Machine Learning Model with Dataset
• Preparing Data to Train the Machine Learning Model
• Asking the Model to Make Predictions
• Testing the Performance of the Model
• How to Make Training and Testing Sets Easily
• Working of the Regression Model
• Creating a Classification Model
• Predicting Whether It Will Rain or Not and Testing the Predictions

26. Flavor Predictor

• Preparing the Data
• Training the Model
• Asking the Model to Make Predictions

27. Artificial Intelligence

• What Is Artificial Intelligence?
• Natural Language Processing
• Feature Extraction from Text Data with CountVectorization
• Finding TF and IDF in Extracted Features from Text Data: Text Analytics
• Working with Images: Computer Vision
• Changing Color-Spaces of Images from BGR to RGB to GRAY

28. Rating Bot

• Reviews and Ratings Data to Create the Model
• Extracting Features and Transforming the Reviews Data
• Training the Model to Rate Reviews
• Creating the Function to Rate Reviews (In Raw Format)

29. Face Recognition Model

• Getting the Data to Create the Model
• Detecting Faces in Images with Our Model
• Creating a Function to Detect Faces and Show Them