Error Handling in Python | StackSkills

Autoplay
Autocomplete

Previous Lesson Complete and Continue

Python in Practice - 15 Projects to Master Python

Programming with Python: Basics and Environment Setup

What Is Programming? (16:58)
Setting Up IDE (16:47)

Data Types and Variables

Data Types in Python (15:15)
Variables (6:38)
Variable Names (4:31)

Text Data Types

Python Strings (6:49)
Extracting Values from Strings: Strings, Slicing, and Indicing (3:19)
String Built-In Functions (4:30)

Numeric Data Types

Numbers in Python (5:30)
Numeric Functions (4:04)

Boolean

Python Booleans (5:18)

Lists

Python Lists (5:04)
List Built-In Functions (6:07)

Tuples

Python Tuples (5:53)
Tuple Operations and Tuple Built-In Functions (3:58)

Sets

Pythons Sets (4:01)
Sets Built-In Functions (3:27)
Mathematical Sets Operations (3:34)

Dictionary

Python Dictionaries (4:09)
Dictionary Built-In Functions (3:51)

Decision Control in Python

Decision Control using if statements (3:26)
Creating conditions Using or and and keywords (4:45)
elif Statements (6:46)
else Statements (4:15)
Decision Control with Strings and Lists (6:51)

Loops in Python

Creating Loops Using While Statements (13:49)

Iterating over Elements

Iterating over Datatypes Using For Loops (12:17)

Functions

Functions in Python and Defining Our Own (3:15)
Getting Arguments during Function Call (3:40)
Positional and Keyword Arguments (6:53)
Arguments and Parameters (2:54)
Arbitrary Arguments (*args) (2:37)
Arbitrary Keyword Arguments (**kwargs) (3:32)
Return Values from User-Defined Functions Using the Return Keyword (1:59)
Pass Keywords for Functions (0:53)
Lambda Functions (2:23)
Creating a Duplicate List Elements Remover Function (2:43)
Redefining the Built-In type( ) Function (4:02)
Creating a Function to Smartly Round Decimal Points in a Result of Addition (8:10)

Object-Oriented Programming

What Are Classes and How to Create Them (3:27)
Defining Class Methods (1:07)
Adding, Modifying, and Deleting Class Attributes (3:16)
Class Attributes and Identifier Naming Convention (6:21)
Functions Versus Class Methods (3:34)
Operator Overloading on User-Defined Classes (5:07)
Built-Ins Overloading on User-Defined Classes (3:51)
Creating User-Defined Iterable Classes (11:46)

Inheritance

Containership (5:41)
Inheritance (4:05)
Accessing Inherited Objects (3:12)
The Object Class (1:14)
Multi-Level Inheritance (2:52)
Multiple Inheritance (4:58)

Dealing with Errors

Error Handling in Python (9:55)
User-Defined Errors (7:09)
Catching Errors with Except Block (2:59)
Use of else and finally Blocks (3:41)

Modules and Packages

Modules and Packages (13:03)
random Module (11:05)
datetime Module (8:51)

All Built-In Functions

Advanced Level: Python GUI

GUI Introduction (1:21)
Creating GUI Application Tk( ) Windows and Widgets (11:01)
Creating Button Widgets (6:36)
Getting Input from the User Using Entry Field Widgets (10:33)
Using Grid System to Place Widgets (14:32)
Button States (4:21)
Customizing Colors and Fonts (2:36)
Adding Color Theme to Your Applications (5:11)
Stylizing the Appearance of the Widgets (Relief) (9:12)
Creating Checkbox Widgets (14:42)
Creating Radio Button Widgets (11:42)
Creating Slider Widgets (13:43)
Creating Dropdown Menu widgets (7:51)
Adding more windows on top of our existing main window (2:37)
Working with Images (9:39)
File Dialog Boxes for Application (14:08)

Applications with Python GUI

Dice Roller (10:07)
Age Calculator (Total Days and Seconds Lived) (24:50)
Length Converter Applications (18:36)
Image to Icon Converter (26:12)

Advanced Level: Data Science

Data Science with Python (2:44)
Anaconda (2:53)
Jupyter Notebook (6:22)
Data Processing with NumPy Package (12:29)
Pandas Series (3:38)
n-darrays to Pandas Series (3:12)
Slicing Values from Pandas Series (2:47)
Pandas DataFrames (5:35)
Slicing Columns, Rows, and Values from Pandas DataFrames (5:08)
Matplotlib Library (3:26)
Data Processing (8:18)
Data Cleaning (15:13)
Data Analysis (13:40)
Data Visualization (16:13)
Customizing Visualizations with Matplotlib (9:33)
Different Types of Plots with Matplotlib (12:03)

Data Science Project 1

Inspecting the Data (2:26)
Importing the Data (2:14)
Data Processing and Cleaning (7:18)
Data Analysis (6:40)
Data Visualization (3:17)
Generating the Final Report (5:31)

eBook Web Store

Web Development with Python and Django (2:08)
How Websites Work and How We Can Create One? (2:44)
Starting Our Website Project with Django (6:39)
Customizing the Homepage View (11:35)
HTML Basics (12:29)
Admin Application and Creating Our Own Applications (9:43)
Creating Our Store View (17:03)
Creating Models and Storing eBooks in the Database (11:59)
Adding eBooks Through the Admin Application (9:30)
Django Template and Context System for html Views (14:25)
Web Design: Stylizing Our html Tags with CSS (17:57)
Bootstrap as Base Template (17:35)
Adding Bootstrap Cards as eBooks in Our Store Webpage (11:17)
Adding Bootstrap Navigation Bar to Our Website (6:47)
Adding the Cart to Our Website (9:40)
Bootstrap Containers (5:53)
Creating Model for Cart Items (4:31)
Getting Book ID from the Add to Cart Button (9:16)
Defining add_to_cart( ) View Function (10:58)
Displaying the Cart Sub-Total (6:14)
Adding a Delete Button to Cart Items (2:44)
Defining del_cart_item( ) View Function (5:15)
What to Display When the Cart Is Empty? (3:04)
Using Bootstrap Icons for html Elements (6:52)

Machine Learning with Python

What Is Machine Learning? (2:38)
How Machines Learn (4:17)
Creating a Machine Learning Model with Dataset (5:22)
Preparing Data to Train the Machine Learning Model (9:43)
Asking the Model to Make Predictions (5:43)
Testing the Performance of the Model (14:22)
How to Make Training and Testing Sets Easily (4:15)
Working of the Regression Model (7:42)
Creating a Classification Model (6:20)
Predicting Whether It Will Rain or Not and Testing the Predictions (14:16)

Flavor Predictor

Preparing the Data (6:54)
Training the Model (4:31)
Asking the Model to Make Predictions (5:12)

Artificial Intelligence

Natural Language Processing (6:06)
What Is Artificial Intelligence? (1:28)
Feature Extraction from Text Data with CountVectorization (13:37)
Finding TF and IDF in Extracted Features from Text Data: Text Analytics (7:04)
Working with Images: Computer Vision (9:21)
Changing Color-Spaces of Images from BGR to RGB to GRAY (8:18)

Rating Bot

Reviews and Ratings Data to Create the Model (3:20)
Extracting Features and Transforming the Reviews Data (4:35)
Training the Model to Rate Reviews (4:13)
Creating the Function to Rate Reviews (In Raw Format) (4:14)

Face Recognition Model

Getting the Data to Create the Model (8:54)
Detecting Faces in Images with Our Model (8:09)
Creating a Function to Detect Faces and Show Them (10:14)

Error Handling in Python

This video explains error handling in Python.

Complete and Continue

Lesson Content Locked

Your session expired. Please sign in again to continue.

Log In