Name: AWS Certified Solutions Architect Associate (SAA-C03)
Price: 261.99 GBP
Availability: InStock

Python

<strong>A code-oriented interactive course that will help you build a solid foundation that is essential to excel in all areas of computer science, specifically data science and machine learning. We will apply all concepts through code and focus on the concepts that are more useful for data science, machine learning, and other areas of computer science.</strong>
        <p>The objective of this course is to give you a solid foundation needed to excel in all areas of computer science-specifically data science and machine learning. The issue is that most of the probability and statistics courses are too theory-oriented. They get tangled in the math without discussing the importance of applications. Applications are always given secondary importance.

In this course, we take a code-oriented approach. We apply all concepts through code. In fact, we skip over all the useless theory that isn't relevant to computer science. Instead, we focus on the concepts that are more useful for data science, machine learning, and other areas of computer science. For instance, many probability courses skip over Bayesian inference. We will get to this immensely important concept rather quickly and give it due attention as it is widely thought of as the future of analysis!

This way, you get to learn the most important concepts in this subject in the shortest amount of time possible without having to deal with the details of the less relevant topics. Once you have developed an intuition of the important stuff, you can then learn the latest and greatest models even on your own!

All the resources for this course are available at: https://github.com/PacktPublishing/Probability-Statistics---The-Foundations-of-Machine-Learning</p>
        <h2>What You Will Learn</h2><p>Learn all necessary concepts in stats and probability<br>Learn important concepts for data science and/or machine learning<br>Understand distributions and their importance<br>Learn about Entropy, which is the foundation of all machine learning<br>Introduction to Bayesian Inference<br>Learn to apply concepts through code</p>
        <h2>Audience</h2><p>This course is designed for beginner ML and data science developers who need a solid foundation, for developers curious about data science and machine learning, for people looking to find out why probability is the foundation of all modern machine learning, or for developers who want to know how to harness the power of big data.</p>
        <h2>Approach</h2><p>In this course, we take a code-oriented approach. We will apply all concepts through code that are more useful for data science, machine learning, and other areas of computer science.</p>
        <h2>Key Features</h2><p>A practical approach towards understanding the core concepts of probability and statistics * Focuses on the applications of these important mathematical concepts in data science, machine learning, and other areas * Understand why probability is the foundation of all modern machine learning</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Probability-Statistics---The-Foundations-of-Machine-Learning</p>
        <h2>About the Author</h2><h3>Dr. Mohammad Nauman</h3><p>Dr. Mohammad Nauman has a PhD in computer science and a PostDoc from the Max Planck Institute for software systems. He has been programming since early 2000 and has worked with many different languages, tools, and platforms. He holds extensive research experience with many state-of-the-art models. His research in Android security has led to some major shifts in the Android permission model.
He loves teaching and the most important reason he teaches online is to make sure that maximum people can learn through his content. Hope you have fun learning with him!</p>
        <h2>Course Outline</h2><h4>1. Diving in with Code</h4><p></p><br><h4>2. Measures of Spread</h4><p></p><br><h4>3. Applications and Rules for Probability</h4><p></p><br><h4>4. Counting</h4><p></p><br><h4>5. Random Variables - Rationale and Applications</h4><p></p><br><h4>6. Visualization in Intuition Building</h4><p></p><br><h4>7. Applications to the Real World</h4><p></p>

A code-oriented interactive course that will help you build a solid foundation that is essential to excel in all areas of computer science, specifically data science and machine learning. We will apply all concepts through code and focus on the concepts that are more useful for data science, machine learning, and other areas of computer science.
The objective of this course is to give you a solid foundation needed to excel in all areas of computer science-specifically data science and machine learning. The issue is that most of the probability and statistics courses are too theory-oriented. They get tangled in the math without discussing the importance of applications. Applications are always given secondary importance. In this course, we take a code-oriented approach. We apply all concepts through code. In fact, we skip over all the useless theory that isn't relevant to computer science. Instead, we focus on the concepts that are more useful for data science, machine learning, and other areas of computer science. For instance, many probability courses skip over Bayesian inference. We will get to this immensely important concept rather quickly and give it due attention as it is widely thought of as the future of analysis! This way, you get to learn the most important concepts in this subject in the shortest amount of time possible without having to deal with the details of the less relevant topics. Once you have developed an intuition of the important stuff, you can then learn the latest and greatest models even on your own! All the resources for this course are available at: https://github.com/PacktPublishing/Probability-Statistics---The-Foundations-of-Machine-Learning
What You Will Learn
Learn all necessary concepts in stats and probability
Learn important concepts for data science and/or machine learning
Understand distributions and their importance
Learn about Entropy, which is the foundation of all machine learning
Introduction to Bayesian Inference
Learn to apply concepts through code
Audience
This course is designed for beginner ML and data science developers who need a solid foundation, for developers curious about data science and machine learning, for people looking to find out why probability is the foundation of all modern machine learning, or for developers who want to know how to harness the power of big data.
Approach
In this course, we take a code-oriented approach. We will apply all concepts through code that are more useful for data science, machine learning, and other areas of computer science.
Key Features
A practical approach towards understanding the core concepts of probability and statistics * Focuses on the applications of these important mathematical concepts in data science, machine learning, and other areas * Understand why probability is the foundation of all modern machine learning
Github Repo
https://github.com/PacktPublishing/Probability-Statistics---The-Foundations-of-Machine-Learning
About the Author
Dr. Mohammad Nauman
Dr. Mohammad Nauman has a PhD in computer science and a PostDoc from the Max Planck Institute for software systems. He has been programming since early 2000 and has worked with many different languages, tools, and platforms. He holds extensive research experience with many state-of-the-art models. His research in Android security has led to some major shifts in the Android permission model.
He loves teaching and the most important reason he teaches online is to make sure that maximum people can learn through his content. Hope you have fun learning with him!
Course Outline
1. Diving in with Code

2. Measures of Spread

3. Applications and Rules for Probability

4. Counting

5. Random Variables - Rationale and Applications

6. Visualization in Intuition Building

7. Applications to the Real World


Packt

Data Science

A code-oriented interactive course that will help you build a solid foundation that is essential to excel in all areas of computer science, specifically data science and machine learning. We will apply all concepts through code and focus on the concepts that are more useful for data science, machine learning, and other areas of computer science.

Probability / Statistics - The Foundations of Machine Learning

General Admission

<strong>Learn Python programming by developing robust GUIs and games</strong>
        <p>Coding for beginners and kids is now made exciting and easy. Learn to code fun?games, graphics and graphical user interfaces (GUIs) in Python, one of the most powerful programming languages known for its speed, flexibility, and ease-of-use. The Python coding language integrates well with other platforms and runs on almost all modern devices. This OSI-approved open-source language allows free use and distribution (including commercial distribution).
This course helps you delve into the graphics and UX (user experience) aspects of Python. You'll get up to speed with this computer language in a hands-on manner by drawing shapes, coding a simple game, and designing GUIs (graphical user interfaces), including a functional GUI for a temperature converter app. The course will also guide you through analyzing scientific and statistical data. As you advance, you'll get to grips with developing educational software. In addition to this, you'll gain comprehensive insights into accessing and organizing databases, along with understanding how to manage networks.
By the end of this course, you will be well-versed with using not only Python 2 but Python 3 as well for designing immersive games and developing interactive applications and websites.
All the codes and supporting files for this course are available at - https://github.com/PacktPublishing/Project-Based-Python-Programming-For-Kids-and-Beginners</p>
        <h2>What You Will Learn</h2><p>Build simple Python-based games using programming loops and functions<br>Draw graphics using the Python module Turtle<br>Develop Python graphical user interfaces with Tkinter<br>Understand how to work with Python 2 and 3<br>Use the in-built Python modules for your projects<br>Use Microsoft Visual Studio Code-a powerful IDLE for programming and development in Python and other languages</p>
        <h2>Audience</h2><p>If you are interested in developing your Python skills, working through real-life programming projects, or building exciting games and GUIs, then this course is for you.</p>
        <h2>Approach</h2><p>The course provides detailed instructions for everything from Python installation to getting started with Microsoft Visual Code. It features helpful coding instructions, along with code examples. Each video will teach you a new programming?concept?that you can apply in real time. The course also helps you reinforce your learning with fun quizzes.</p>
        <h2>Key Features</h2><p>Learn the basics of Python game programming * Develop intuitive and efficient Python GUIs * Create simple yet practical applications in Python</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/project-based-python-programming-for-kids-and-beginners</p>
        <h2>About the Author</h2><h3>Minerva Singh</h3><p>Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.</p>
        <h2>Course Outline</h2><h4>1. Introduction to Project Based Python Programming</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to the Course & Me</p><p style='margin: 0'>Introduction to Project Based Python Programming: Introduction to the Course & Me</p></td></tr><tr><td style='padding: 15px;'><p>2. Python Installation for Windows</p><p style='margin: 0'>Introduction to Project Based Python Programming: Python Installation for Windows</p></td></tr><tr><td style='padding: 15px;'><p>3. Python Installation for Other OS</p><p style='margin: 0'>Introduction to Project Based Python Programming: Python Installation for Other OS</p></td></tr><tr><td style='padding: 15px;'><p>4. Online Python IDLE</p><p style='margin: 0'>Introduction to Project Based Python Programming: Online Python IDLE</p></td></tr><tr><td style='padding: 15px;'><p>5. Hello World in Python</p><p style='margin: 0'>Introduction to Project Based Python Programming: Hello World in Python</p></td></tr><tr><td style='padding: 15px;'><p>6. Python Coding with Visual Studio</p><p style='margin: 0'>Introduction to Project Based Python Programming: Python Coding with Visual Studio</p></td></tr><tr><td style='padding: 15px;'><p>7. Some Common Python Terms</p><p style='margin: 0'>Introduction to Project Based Python Programming: Some Common Python Terms</p></td></tr><tr><td style='padding: 15px;'><p>8. Conclusion to Section 1</p><p style='margin: 0'>Introduction to Project Based Python Programming: Conclusion to Section 1</p></td></tr></tbody></table><br><h4>2. Diving into the Python Basics</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Basic Arithmetic in Python</p><p style='margin: 0'>Diving into the Python Basics: Basic Arithmetic in Python</p></td></tr><tr><td style='padding: 15px;'><p>2. Welcome to the World of Data Types</p><p style='margin: 0'>Diving into the Python Basics: Welcome to the World of Data Types</p></td></tr><tr><td style='padding: 15px;'><p>3. Random Number Generation</p><p style='margin: 0'>Diving into the Python Basics: Random Number Generation</p></td></tr><tr><td style='padding: 15px;'><p>4. Working With Strings</p><p style='margin: 0'>Diving into the Python Basics: Working With Strings</p></td></tr><tr><td style='padding: 15px;'><p>5. Get User Inputs</p><p style='margin: 0'>Diving into the Python Basics: Get User Inputs</p></td></tr><tr><td style='padding: 15px;'><p>6. Tuples</p><p style='margin: 0'>Diving into the Python Basics: Tuples</p></td></tr><tr><td style='padding: 15px;'><p>7. Lists</p><p style='margin: 0'>Diving into the Python Basics: Lists</p></td></tr><tr><td style='padding: 15px;'><p>8. Dictionaries</p><p style='margin: 0'>Diving into the Python Basics: Dictionaries</p></td></tr><tr><td style='padding: 15px;'><p>9. Defining our Own Functions in Python-Basic</p><p style='margin: 0'>Diving into the Python Basics: Defining our Own Functions in Python-Basic</p></td></tr><tr><td style='padding: 15px;'><p>10. Some More On Functions</p><p style='margin: 0'>Diving into the Python Basics: Some More On Functions</p></td></tr><tr><td style='padding: 15px;'><p>11. Conclusions to Section 2</p><p style='margin: 0'>Diving into the Python Basics: Conclusions to Section 2</p></td></tr></tbody></table><br><h4>3. Decision Making with Programming</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Rationale for this section</p><p style='margin: 0'>Decision Making with Programming: Rationale for this section</p></td></tr><tr><td style='padding: 15px;'><p>2. if-else loops</p><p style='margin: 0'>Decision Making with Programming: if-else loops</p></td></tr><tr><td style='padding: 15px;'><p>3. elif in if-else loops</p><p style='margin: 0'>Decision Making with Programming: elif in if-else loops</p></td></tr><tr><td style='padding: 15px;'><p>4. while loop</p><p style='margin: 0'>Decision Making with Programming: while loop</p></td></tr><tr><td style='padding: 15px;'><p>5. for loop</p><p style='margin: 0'>Decision Making with Programming: for loop</p></td></tr><tr><td style='padding: 15px;'><p>6. More on Loops</p><p style='margin: 0'>Decision Making with Programming: More on Loops</p></td></tr><tr><td style='padding: 15px;'><p>7. Nested For Loop</p><p style='margin: 0'>Decision Making with Programming: Nested For Loop</p></td></tr><tr><td style='padding: 15px;'><p>8. Build a Number Guessing Game!!-Basic</p><p style='margin: 0'>Decision Making with Programming: Build a Number Guessing Game!!-Basic</p></td></tr><tr><td style='padding: 15px;'><p>9. Build a Number Guessing Game!!-Advanced</p><p style='margin: 0'>Decision Making with Programming: Build a Number Guessing Game!!-Advanced</p></td></tr><tr><td style='padding: 15px;'><p>10. OPTIONAL:Build a Number Guessing Game!!-(More) Advanced</p><p style='margin: 0'>Decision Making with Programming: OPTIONAL:Build a Number Guessing Game!!-(More) Advanced</p></td></tr><tr><td style='padding: 15px;'><p>11. Conclusion to Section 3</p><p style='margin: 0'>Decision Making with Programming: Conclusion to Section 3</p></td></tr></tbody></table><br><h4>4. Graphics with Python</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Working With Graphics in Python</p><p style='margin: 0'>Graphics with Python: Working With Graphics in Python</p></td></tr><tr><td style='padding: 15px;'><p>2. Draw a Square</p><p style='margin: 0'>Graphics with Python: Draw a Square</p></td></tr><tr><td style='padding: 15px;'><p>3. The Idea Behind Angles</p><p style='margin: 0'>Graphics with Python: The Idea Behind Angles</p></td></tr><tr><td style='padding: 15px;'><p>4. Draw a Rectangle Using Loops</p><p style='margin: 0'>Graphics with Python: Draw a Rectangle Using Loops</p></td></tr><tr><td style='padding: 15px;'><p>5. Create a Rectangle Function</p><p style='margin: 0'>Graphics with Python: Create a Rectangle Function</p></td></tr><tr><td style='padding: 15px;'><p>6. Code Along1: Draw an Equilateral Triangle</p><p style='margin: 0'>Graphics with Python: Code Along1: Draw an Equilateral Triangle</p></td></tr><tr><td style='padding: 15px;'><p>7. Code Along2: Draw an Equilateral Triangle With Loops</p><p style='margin: 0'>Graphics with Python: Code Along2: Draw an Equilateral Triangle With Loops</p></td></tr><tr><td style='padding: 15px;'><p>8. Code an Irregular Shape: Start a Snowflake</p><p style='margin: 0'>Graphics with Python: Code an Irregular Shape: Start a Snowflake</p></td></tr><tr><td style='padding: 15px;'><p>9. Snowflakes!!</p><p style='margin: 0'>Unsupervised Learning in Python: Hierarchical Clustering-practical</p></td></tr><tr><td style='padding: 15px;'><p>10. Conclusions to Section 4</p><p style='margin: 0'>Graphics with Python: Conclusions to Section 4</p></td></tr></tbody></table><br><h4>5. GUI Programming with Python</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Start with GUIs in Python</p><p style='margin: 0'>GUI Programming with Python: Start with GUIs in Python</p></td></tr><tr><td style='padding: 15px;'><p>2. Create a Simple Button With tkinter</p><p style='margin: 0'>GUI Programming with Python: Create a Simple Button With tkinter</p></td></tr><tr><td style='padding: 15px;'><p>3. Add Functionality to the Button</p><p style='margin: 0'>GUI Programming with Python: Add Functionality to the Button</p></td></tr><tr><td style='padding: 15px;'><p>4. The Tkinter Grid</p><p style='margin: 0'>GUI Programming with Python: The Tkinter Grid</p></td></tr><tr><td style='padding: 15px;'><p>5. Common Tkinter GUI Widgets</p><p style='margin: 0'>GUI Programming with Python: Common Tkinter GUI Widgets</p></td></tr><tr><td style='padding: 15px;'><p>6. Canvas for Drawing-part1</p><p style='margin: 0'>GUI Programming with Python: Canvas for Drawing-part1</p></td></tr><tr><td style='padding: 15px;'><p>7. Canvas for Drawing-part2</p><p style='margin: 0'>GUI Programming with Python: Canvas for Drawing-part2</p></td></tr><tr><td style='padding: 15px;'><p>8. Simple Expression Evaluator</p><p style='margin: 0'>GUI Programming with Python: Simple Expression Evaluator</p></td></tr><tr><td style='padding: 15px;'><p>9. Start With the Temperature Conversion App</p><p style='margin: 0'>GUI Programming with Python: Start With the Temperature Conversion App</p></td></tr><tr><td style='padding: 15px;'><p>10. Complete the App-1</p><p style='margin: 0'>GUI Programming with Python: Complete the App-1</p></td></tr><tr><td style='padding: 15px;'><p>11. Complete the App-2</p><p style='margin: 0'>GUI Programming with Python: Complete the App-2</p></td></tr></tbody></table>

Learn Python programming by developing robust GUIs and games
Coding for beginners and kids is now made exciting and easy. Learn to code fun?games, graphics and graphical user interfaces (GUIs) in Python, one of the most powerful programming languages known for its speed, flexibility, and ease-of-use. The Python coding language integrates well with other platforms and runs on almost all modern devices. This OSI-approved open-source language allows free use and distribution (including commercial distribution).
This course helps you delve into the graphics and UX (user experience) aspects of Python. You'll get up to speed with this computer language in a hands-on manner by drawing shapes, coding a simple game, and designing GUIs (graphical user interfaces), including a functional GUI for a temperature converter app. The course will also guide you through analyzing scientific and statistical data. As you advance, you'll get to grips with developing educational software. In addition to this, you'll gain comprehensive insights into accessing and organizing databases, along with understanding how to manage networks.
By the end of this course, you will be well-versed with using not only Python 2 but Python 3 as well for designing immersive games and developing interactive applications and websites.
All the codes and supporting files for this course are available at - https://github.com/PacktPublishing/Project-Based-Python-Programming-For-Kids-and-Beginners
What You Will Learn
Build simple Python-based games using programming loops and functions
Draw graphics using the Python module Turtle
Develop Python graphical user interfaces with Tkinter
Understand how to work with Python 2 and 3
Use the in-built Python modules for your projects
Use Microsoft Visual Studio Code-a powerful IDLE for programming and development in Python and other languages
Audience
If you are interested in developing your Python skills, working through real-life programming projects, or building exciting games and GUIs, then this course is for you.
Approach
The course provides detailed instructions for everything from Python installation to getting started with Microsoft Visual Code. It features helpful coding instructions, along with code examples. Each video will teach you a new programming?concept?that you can apply in real time. The course also helps you reinforce your learning with fun quizzes.
Key Features
Learn the basics of Python game programming * Develop intuitive and efficient Python GUIs * Create simple yet practical applications in Python
Github Repo
https://github.com/packtpublishing/project-based-python-programming-for-kids-and-beginners
About the Author
Minerva Singh
Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.
Course Outline
1. Introduction to Project Based Python Programming

1. Introduction to the Course & Me
Introduction to Project Based Python Programming: Introduction to the Course & Me
2. Python Installation for Windows
Introduction to Project Based Python Programming: Python Installation for Windows
3. Python Installation for Other OS
Introduction to Project Based Python Programming: Python Installation for Other OS
4. Online Python IDLE
Introduction to Project Based Python Programming: Online Python IDLE
5. Hello World in Python
Introduction to Project Based Python Programming: Hello World in Python
6. Python Coding with Visual Studio
Introduction to Project Based Python Programming: Python Coding with Visual Studio
7. Some Common Python Terms
Introduction to Project Based Python Programming: Some Common Python Terms
8. Conclusion to Section 1
Introduction to Project Based Python Programming: Conclusion to Section 1
2. Diving into the Python Basics

1. Basic Arithmetic in Python
Diving into the Python Basics: Basic Arithmetic in Python
2. Welcome to the World of Data Types
Diving into the Python Basics: Welcome to the World of Data Types
3. Random Number Generation
Diving into the Python Basics: Random Number Generation
4. Working With Strings
Diving into the Python Basics: Working With Strings
5. Get User Inputs
Diving into the Python Basics: Get User Inputs
6. Tuples
Diving into the Python Basics: Tuples
7. Lists
Diving into the Python Basics: Lists
8. Dictionaries
Diving into the Python Basics: Dictionaries
9. Defining our Own Functions in Python-Basic
Diving into the Python Basics: Defining our Own Functions in Python-Basic
10. Some More On Functions
Diving into the Python Basics: Some More On Functions
11. Conclusions to Section 2
Diving into the Python Basics: Conclusions to Section 2
3. Decision Making with Programming

1. Rationale for this section
Decision Making with Programming: Rationale for this section
2. if-else loops
Decision Making with Programming: if-else loops
3. elif in if-else loops
Decision Making with Programming: elif in if-else loops
4. while loop
Decision Making with Programming: while loop
5. for loop
Decision Making with Programming: for loop
6. More on Loops
Decision Making with Programming: More on Loops
7. Nested For Loop
Decision Making with Programming: Nested For Loop
8. Build a Number Guessing Game!!-Basic
Decision Making with Programming: Build a Number Guessing Game!!-Basic
9. Build a Number Guessing Game!!-Advanced
Decision Making with Programming: Build a Number Guessing Game!!-Advanced
10. OPTIONAL:Build a Number Guessing Game!!-(More) Advanced
Decision Making with Programming: OPTIONAL:Build a Number Guessing Game!!-(More) Advanced
11. Conclusion to Section 3
Decision Making with Programming: Conclusion to Section 3
4. Graphics with Python

1. Working With Graphics in Python
Graphics with Python: Working With Graphics in Python
2. Draw a Square
Graphics with Python: Draw a Square
3. The Idea Behind Angles
Graphics with Python: The Idea Behind Angles
4. Draw a Rectangle Using Loops
Graphics with Python: Draw a Rectangle Using Loops
5. Create a Rectangle Function
Graphics with Python: Create a Rectangle Function
6. Code Along1: Draw an Equilateral Triangle
Graphics with Python: Code Along1: Draw an Equilateral Triangle
7. Code Along2: Draw an Equilateral Triangle With Loops
Graphics with Python: Code Along2: Draw an Equilateral Triangle With Loops
8. Code an Irregular Shape: Start a Snowflake
Graphics with Python: Code an Irregular Shape: Start a Snowflake
9. Snowflakes!!
Unsupervised Learning in Python: Hierarchical Clustering-practical
10. Conclusions to Section 4
Graphics with Python: Conclusions to Section 4
5. GUI Programming with Python

1. Start with GUIs in Python
GUI Programming with Python: Start with GUIs in Python
2. Create a Simple Button With tkinter
GUI Programming with Python: Create a Simple Button With tkinter
3. Add Functionality to the Button
GUI Programming with Python: Add Functionality to the Button
4. The Tkinter Grid
GUI Programming with Python: The Tkinter Grid
5. Common Tkinter GUI Widgets
GUI Programming with Python: Common Tkinter GUI Widgets
6. Canvas for Drawing-part1
GUI Programming with Python: Canvas for Drawing-part1
7. Canvas for Drawing-part2
GUI Programming with Python: Canvas for Drawing-part2
8. Simple Expression Evaluator
GUI Programming with Python: Simple Expression Evaluator
9. Start With the Temperature Conversion App
GUI Programming with Python: Start With the Temperature Conversion App
10. Complete the App-1
GUI Programming with Python: Complete the App-1
11. Complete the App-2
GUI Programming with Python: Complete the App-2

Programming

Learn Python programming by developing robust GUIs and games

Project-Based Python Programming For Kids and Beginners

<strong>This concise and comprehensive course takes you through the basic and advanced topics of Ansible, explaining all the concepts clearly and thoroughly. You will not only master the concepts but also learn how to use Ansible with cloud services and containers.</strong>
        <p>Ansible is a simple IT automation engine that automates cloud provisioning, configuration management, application deployment, intra-service orchestration, and many other IT needs. Designed for multi-tier deployments from day one, Ansible models IT infrastructure by describing how all the systems interrelate, rather than just managing one system at a time. This course will guide you through multiple topics to make you understand and master Ansible.

The course starts with the learning objectives and introduces you to Ansible. Next, you will learn how to set up the environment by installing the Ansible lab, Docker, and configuring the Secure Shell (SSH) connectivity between hosts. Moving along, you will study the architecture, modules, playbooks, and YAML Ain't Markup Language (YAML) syntaxes used in Ansible. Next, you will learn how to structure advanced Ansible playbooks and uncover techniques to use Ansible with cloud services and containers. Towards the end, you will learn how to use Ansible for validation, testing, and troubleshooting.

By the end of this course, you will have mastered the basic and advanced concepts of Ansible and will have developed the skills needed to work on real-world Ansible projects.

All the Labs and resources for this course are available at https://github.com/PacktPublishing/Dive-Into-Ansible---From-Beginner-to-Expert-in-Ansible</p>
        <h2>What You Will Learn</h2><p>Configure SSH connectivity between hosts<br>Become familiar with Ansible configuration, inventories, and modules<br>Discover how to create and execute Ansible playbooks<br>Use Ansible with cloud services and containers<br>Create a dynamic inventory with minimal scripting using Ansible<br>Use Ansible for validation, testing, and troubleshooting</p>
        <h2>Audience</h2><p>This course is designed for beginners who are looking to master the basic and advanced concepts of Ansible. There are no prerequisites for taking this course.</p>
        <h2>Approach</h2><p>With the help of hands-on exercises, examples, visual diagrams, and labs, this course will teach you the basic and advanced concepts of Ansible. You will also work on a playbook project where you will launch a website with a special Easter egg, an Ansible-themed game known as 'Playbook Stacker'.</p>
        <h2>Key Features</h2><p>Gain a solid understanding of Ansible modules and playbooks * Includes the latest Ansible version (2022 v5.x) + full lab * Learn how to use Ansible with Amazon Web Services (AWS) and Docker</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Dive-Into-Ansible---From-Beginner-to-Expert-in-Ansible</p>
        <h2>About the Author</h2><h3>James Spurin</h3><p>James Spurin is an IT professional with over 15 years of experience, working in a variety of technology fields including internet technologies, automation, software development, storage, and UNIX administration. He holds an MSc with a distinction in computer science and software engineering from Liverpool University. Professionally, he has worked for a variety of major organizations, including Dell EMC, Goldman Sachs, Nomura, and Virgin Internet. He is also an advisory board member for StorageOS, a container-based storage solution. He is an active contributor to open-source software and is the creator and maintainer of Extensible Markup Language (XML) dataset, a Python library featured on the awesome Python list for parsing XML data.</p>
        <h2>Course Outline</h2><h4>1. Course Overview and Introduction to Ansible</h4><p></p><br><h4>2. Setup of the Lab Environment and Course Resources</h4><p></p><br><h4>3. Ansible Architecture and Design</h4><p></p><br><h4>4. Ansible Playbooks, Introduction</h4><p></p><br><h4>5. Ansible Playbooks, Deep Dive</h4><p></p><br><h4>6. Structuring Ansible Playbooks</h4><p></p><br><h4>7. Using Ansible with Cloud Services and Containers</h4><p></p><br><h4>8. Creating Modules and Plugins</h4><p></p><br><h4>9. Other Ansible Resources and Areas</h4><p></p><br><h4>10. Supplementary</h4><p></p>

This concise and comprehensive course takes you through the basic and advanced topics of Ansible, explaining all the concepts clearly and thoroughly. You will not only master the concepts but also learn how to use Ansible with cloud services and containers.
Ansible is a simple IT automation engine that automates cloud provisioning, configuration management, application deployment, intra-service orchestration, and many other IT needs. Designed for multi-tier deployments from day one, Ansible models IT infrastructure by describing how all the systems interrelate, rather than just managing one system at a time. This course will guide you through multiple topics to make you understand and master Ansible. The course starts with the learning objectives and introduces you to Ansible. Next, you will learn how to set up the environment by installing the Ansible lab, Docker, and configuring the Secure Shell (SSH) connectivity between hosts. Moving along, you will study the architecture, modules, playbooks, and YAML Ain't Markup Language (YAML) syntaxes used in Ansible. Next, you will learn how to structure advanced Ansible playbooks and uncover techniques to use Ansible with cloud services and containers. Towards the end, you will learn how to use Ansible for validation, testing, and troubleshooting. By the end of this course, you will have mastered the basic and advanced concepts of Ansible and will have developed the skills needed to work on real-world Ansible projects. All the Labs and resources for this course are available at https://github.com/PacktPublishing/Dive-Into-Ansible---From-Beginner-to-Expert-in-Ansible
What You Will Learn
Configure SSH connectivity between hosts
Become familiar with Ansible configuration, inventories, and modules
Discover how to create and execute Ansible playbooks
Use Ansible with cloud services and containers
Create a dynamic inventory with minimal scripting using Ansible
Use Ansible for validation, testing, and troubleshooting
Audience
This course is designed for beginners who are looking to master the basic and advanced concepts of Ansible. There are no prerequisites for taking this course.
Approach
With the help of hands-on exercises, examples, visual diagrams, and labs, this course will teach you the basic and advanced concepts of Ansible. You will also work on a playbook project where you will launch a website with a special Easter egg, an Ansible-themed game known as 'Playbook Stacker'.
Key Features
Gain a solid understanding of Ansible modules and playbooks * Includes the latest Ansible version (2022 v5.x) + full lab * Learn how to use Ansible with Amazon Web Services (AWS) and Docker
Github Repo
https://github.com/PacktPublishing/Dive-Into-Ansible---From-Beginner-to-Expert-in-Ansible
About the Author
James Spurin
James Spurin is an IT professional with over 15 years of experience, working in a variety of technology fields including internet technologies, automation, software development, storage, and UNIX administration. He holds an MSc with a distinction in computer science and software engineering from Liverpool University. Professionally, he has worked for a variety of major organizations, including Dell EMC, Goldman Sachs, Nomura, and Virgin Internet. He is also an advisory board member for StorageOS, a container-based storage solution. He is an active contributor to open-source software and is the creator and maintainer of Extensible Markup Language (XML) dataset, a Python library featured on the awesome Python list for parsing XML data.
Course Outline
1. Course Overview and Introduction to Ansible

2. Setup of the Lab Environment and Course Resources

3. Ansible Architecture and Design

4. Ansible Playbooks, Introduction

5. Ansible Playbooks, Deep Dive

6. Structuring Ansible Playbooks

7. Using Ansible with Cloud Services and Containers

8. Creating Modules and Plugins

9. Other Ansible Resources and Areas

10. Supplementary


DevOps

Docker

Ansible

Automation

This concise and comprehensive course takes you through the basic and advanced topics of Ansible, explaining all the concepts clearly and thoroughly. You will not only master the concepts but also learn how to use Ansible with cloud services and containers.

Dive Into Ansible - From Beginner to Expert in Ansible

<strong>In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks (RNNs). You will learn about sequence data, forecasting, Elman Unit, GRU, and LSTM. You will also learn how to work with image classification and how to get stock return predictions using LSTMs. We will also cover Natural Language Processing (NLP) and learn about text preprocessing and classification.</strong>
        <p>Recurrent Neural Networks are a type of deep learning architecture designed to process sequential data, such as time series, text, speech, and video. RNNs have a memory mechanism, which allows them to preserve information from past inputs and use it to inform their predictions.

TensorFlow 2 is a popular open-source software library for machine learning and deep learning. It provides a high-level API for building and training machine learning models, including RNNs.

In this compact course, you will learn how to use TensorFlow 2 to build RNNs. We will study the Simple RNN (Elman unit), the GRU, and the LSTM, followed by investigating the capabilities of the different RNN units in terms of their ability to detect nonlinear relationships and long-term dependencies. We will apply RNNs to both time series forecasting and NLP. Next, we will apply LSTMs to stock 'price' predictions, but in a different way compared to most other resources. It will mostly be an investigation about what not to do and how not to make the same mistakes that most blogs and courses make when predicting stocks.

By the end of this course, you will be able to build your own build RNNs with TensorFlow 2.</p>
        <h2>What You Will Learn</h2><p>Learn about simple RNNs (Elman unit)<br>Covers GRU (gated recurrent unit)<br>Learn how to use LSTM (long short-term memory unit)<br>Learn how to preform time series forecasting<br>Learn how to predict stock price and stock return with LSTM<br>Learn how to apply RNNs to NLP</p>
        <h2>Audience</h2><p>This course is designed for anyone interested in deep learning and machine learning or for anyone who wants to implement recurrent neural networks in TensorFlow 2. One must have decent Python programming skills, should know how to build a feedforward ANN in TensorFlow 2, and must have experience with data science libraries such as NumPy and Matplotlib.</p>
        <h2>Approach</h2><p>In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks. The course is well-balanced with theory that explains the RNN concepts and hands-on coding exercises for practical understanding. The course includes video presentations, coding lessons, hands-on exercises, and links to further resources.</p>
        <h2>Key Features</h2><p>Build your own RNNs with TensorFlow 2 * Explains RNNs, time series, and sequence data * Preform text preprocessing and text classification with LSTMs</p>
        
        <h2>About the Author</h2><h3>Lazy Programmer</h3><p>The Lazy Programmer, a distinguished online educator, boasts dual master's degrees in computer engineering and statistics, with a decade-long specialization in machine learning, pattern recognition, and deep learning, where he authored pioneering courses. His professional journey includes enhancing online advertising and digital media, notably increasing click-through rates and revenue. As a versatile full-stack software engineer, he excels in Python, Ruby on Rails, C++, and more. His expansive knowledge covers areas like bioinformatics and algorithmic trading, showcasing his diverse skill set. Dedicated to simplifying complex topics, he stands as a pivotal figure in online education, adeptly navigating students through the nuances of data science and AI.</p>
        <h2>Course Outline</h2><h4>1. Welcome</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>In this video, we will get introduced to recurrent neural networks and understand the course learning objective.</p></td></tr><tr><td style='padding: 15px;'><p>2. Outline</p><p style='margin: 0'>In this video, we will understand the course learning approach and what is required to start with this course. Then we will also understand what is covered in this course.</p></td></tr></tbody></table><br><h4>2. Recurrent Neural Networks (RNNs), Time Series, and Sequence Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Sequence Data</p><p style='margin: 0'>In this video, you will learn about sequence data.</p></td></tr><tr><td style='padding: 15px;'><p>2. Forecasting</p><p style='margin: 0'>In this video, we will discuss about forecasting.</p></td></tr><tr><td style='padding: 15px;'><p>3. Autoregressive Linear Model for Time Series Prediction</p><p style='margin: 0'>In this video, we will dive into coding and learn about the autoregressive linear model for time series prediction.</p></td></tr><tr><td style='padding: 15px;'><p>4. Proof That the Linear Model Works</p><p style='margin: 0'>In this video, you will learn how the linear model is about to forecast for a sine wave.</p></td></tr><tr><td style='padding: 15px;'><p>5. Recurrent Neural Networks (Elman Unit Part 1)</p><p style='margin: 0'>In this video, we will get introduced to simple recurrent neural networks also called as Elman Unit.</p></td></tr><tr><td style='padding: 15px;'><p>6. Recurrent Neural Networks (Elman Unit Part 2)</p><p style='margin: 0'>In this video, you will learn how to use the simple RNN to solve many-to-one tasks and many-to-many problems.</p></td></tr><tr><td style='padding: 15px;'><p>7. RNN Code Preparation</p><p style='margin: 0'>In this video, we will understand how to write code in TensorFlow 2 for a simple RNN.</p></td></tr><tr><td style='padding: 15px;'><p>8. RNN for Time Series Prediction</p><p style='margin: 0'>In this video, we will do the same forecasting exercise that we did with an autoregressive liner model, but with a simple RNN instead.</p></td></tr><tr><td style='padding: 15px;'><p>9. Paying Attention to Shapes</p><p style='margin: 0'>In this video, we will work on shapes in RNN.</p></td></tr><tr><td style='padding: 15px;'><p>10. GRU and LSTM (Part 1)</p><p style='margin: 0'>In this video, you will learn about modern RNN units called GRU.</p></td></tr><tr><td style='padding: 15px;'><p>11. GRU and LSTM (Part 2)</p><p style='margin: 0'>In this video, you will learn about modern RNN units called LSTM.</p></td></tr><tr><td style='padding: 15px;'><p>12. A More Challenging Sequence</p><p style='margin: 0'>In this video, you will learn how to preform time series prediction with a complex signal.</p></td></tr><tr><td style='padding: 15px;'><p>13. Demo of the Long-Distance Problem</p><p style='margin: 0'>In this video, we will understand how LSTMs work for resolving a long-distance problem.</p></td></tr><tr><td style='padding: 15px;'><p>14. RNN for Image Classification (Theory)</p><p style='margin: 0'>In this video, we will understand how to apply RNN for image classification.</p></td></tr><tr><td style='padding: 15px;'><p>15. RNN for Image Classification (Code)</p><p style='margin: 0'>In this video, you will learn how to preform RNN for image classification on the MNIST dataset.</p></td></tr><tr><td style='padding: 15px;'><p>16. Stock Return Predictions Using LSTMs (Part 1)</p><p style='margin: 0'>In this video, we will understand why one-step prediction on stock price is misleading and unconventional.</p></td></tr><tr><td style='padding: 15px;'><p>17. Stock Return Predictions Using LSTMs (Part 2)</p><p style='margin: 0'>In this video, we will work on a more conventional prediction called stock return.</p></td></tr><tr><td style='padding: 15px;'><p>18. Stock Return Predictions Using LSTMs (Part 3)</p><p style='margin: 0'>In this video, we will make use of all the data and try to predict whether the price will go up or down.</p></td></tr><tr><td style='padding: 15px;'><p>19. Other Ways to Forecast</p><p style='margin: 0'>In this video, we will discuss some other ways that might generate multi-step forecast.</p></td></tr><tr><td style='padding: 15px;'><p>20. Suggestion Box</p><p style='margin: 0'>In this video, the author shares how you can get in touch with him through the suggestion box.</p></td></tr></tbody></table><br><h4>3. Natural Language Processing (NLP)</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Embeddings</p><p style='margin: 0'>In this video, we will understand what embedding is.</p></td></tr><tr><td style='padding: 15px;'><p>2. Code Preparation (NLP)</p><p style='margin: 0'>In this video, you will learn how to write the code to turn a sequence of words into an acceptable format such that they can be converted into a matrix of numbers.</p></td></tr><tr><td style='padding: 15px;'><p>3. Text Preprocessing</p><p style='margin: 0'>In this video, we will work on text preprocessing.</p></td></tr><tr><td style='padding: 15px;'><p>4. Text Classification with LSTMs</p><p style='margin: 0'>In this video, we will work on text classification with LSTMs.</p></td></tr></tbody></table>

In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks (RNNs). You will learn about sequence data, forecasting, Elman Unit, GRU, and LSTM. You will also learn how to work with image classification and how to get stock return predictions using LSTMs. We will also cover Natural Language Processing (NLP) and learn about text preprocessing and classification.
Recurrent Neural Networks are a type of deep learning architecture designed to process sequential data, such as time series, text, speech, and video. RNNs have a memory mechanism, which allows them to preserve information from past inputs and use it to inform their predictions. TensorFlow 2 is a popular open-source software library for machine learning and deep learning. It provides a high-level API for building and training machine learning models, including RNNs. In this compact course, you will learn how to use TensorFlow 2 to build RNNs. We will study the Simple RNN (Elman unit), the GRU, and the LSTM, followed by investigating the capabilities of the different RNN units in terms of their ability to detect nonlinear relationships and long-term dependencies. We will apply RNNs to both time series forecasting and NLP. Next, we will apply LSTMs to stock 'price' predictions, but in a different way compared to most other resources. It will mostly be an investigation about what not to do and how not to make the same mistakes that most blogs and courses make when predicting stocks. By the end of this course, you will be able to build your own build RNNs with TensorFlow 2.
What You Will Learn
Learn about simple RNNs (Elman unit)
Covers GRU (gated recurrent unit)
Learn how to use LSTM (long short-term memory unit)
Learn how to preform time series forecasting
Learn how to predict stock price and stock return with LSTM
Learn how to apply RNNs to NLP
Audience
This course is designed for anyone interested in deep learning and machine learning or for anyone who wants to implement recurrent neural networks in TensorFlow 2. One must have decent Python programming skills, should know how to build a feedforward ANN in TensorFlow 2, and must have experience with data science libraries such as NumPy and Matplotlib.
Approach
In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks. The course is well-balanced with theory that explains the RNN concepts and hands-on coding exercises for practical understanding. The course includes video presentations, coding lessons, hands-on exercises, and links to further resources.
Key Features
Build your own RNNs with TensorFlow 2 * Explains RNNs, time series, and sequence data * Preform text preprocessing and text classification with LSTMs
About the Author
Lazy Programmer
The Lazy Programmer, a distinguished online educator, boasts dual master's degrees in computer engineering and statistics, with a decade-long specialization in machine learning, pattern recognition, and deep learning, where he authored pioneering courses. His professional journey includes enhancing online advertising and digital media, notably increasing click-through rates and revenue. As a versatile full-stack software engineer, he excels in Python, Ruby on Rails, C++, and more. His expansive knowledge covers areas like bioinformatics and algorithmic trading, showcasing his diverse skill set. Dedicated to simplifying complex topics, he stands as a pivotal figure in online education, adeptly navigating students through the nuances of data science and AI.
Course Outline
1. Welcome

1. Introduction
In this video, we will get introduced to recurrent neural networks and understand the course learning objective.
2. Outline
In this video, we will understand the course learning approach and what is required to start with this course. Then we will also understand what is covered in this course.
2. Recurrent Neural Networks (RNNs), Time Series, and Sequence Data

1. Sequence Data
In this video, you will learn about sequence data.
2. Forecasting
In this video, we will discuss about forecasting.
3. Autoregressive Linear Model for Time Series Prediction
In this video, we will dive into coding and learn about the autoregressive linear model for time series prediction.
4. Proof That the Linear Model Works
In this video, you will learn how the linear model is about to forecast for a sine wave.
5. Recurrent Neural Networks (Elman Unit Part 1)
In this video, we will get introduced to simple recurrent neural networks also called as Elman Unit.
6. Recurrent Neural Networks (Elman Unit Part 2)
In this video, you will learn how to use the simple RNN to solve many-to-one tasks and many-to-many problems.
7. RNN Code Preparation
In this video, we will understand how to write code in TensorFlow 2 for a simple RNN.
8. RNN for Time Series Prediction
In this video, we will do the same forecasting exercise that we did with an autoregressive liner model, but with a simple RNN instead.
9. Paying Attention to Shapes
In this video, we will work on shapes in RNN.
10. GRU and LSTM (Part 1)
In this video, you will learn about modern RNN units called GRU.
11. GRU and LSTM (Part 2)
In this video, you will learn about modern RNN units called LSTM.
12. A More Challenging Sequence
In this video, you will learn how to preform time series prediction with a complex signal.
13. Demo of the Long-Distance Problem
In this video, we will understand how LSTMs work for resolving a long-distance problem.
14. RNN for Image Classification (Theory)
In this video, we will understand how to apply RNN for image classification.
15. RNN for Image Classification (Code)
In this video, you will learn how to preform RNN for image classification on the MNIST dataset.
16. Stock Return Predictions Using LSTMs (Part 1)
In this video, we will understand why one-step prediction on stock price is misleading and unconventional.
17. Stock Return Predictions Using LSTMs (Part 2)
In this video, we will work on a more conventional prediction called stock return.
18. Stock Return Predictions Using LSTMs (Part 3)
In this video, we will make use of all the data and try to predict whether the price will go up or down.
19. Other Ways to Forecast
In this video, we will discuss some other ways that might generate multi-step forecast.
20. Suggestion Box
In this video, the author shares how you can get in touch with him through the suggestion box.
3. Natural Language Processing (NLP)

1. Embeddings
In this video, we will understand what embedding is.
2. Code Preparation (NLP)
In this video, you will learn how to write the code to turn a sequence of words into an acceptable format such that they can be converted into a matrix of numbers.
3. Text Preprocessing
In this video, we will work on text preprocessing.
4. Text Classification with LSTMs
In this video, we will work on text classification with LSTMs.

TensorFlow

In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks (RNNs). You will learn about sequence data, forecasting, Elman Unit, GRU, and LSTM. You will also learn how to work with image classification and how to get stock return predictions using LSTMs. We will also cover Natural Language Processing (NLP) and learn about text preprocessing and classification.

Deep Learning - Recurrent Neural Networks with TensorFlow

<strong>Leverage pytest's fast, scalable, and professional-grade framework design to build and run automated test suites like a pro</strong>
        <p>Python is one of the most popular programming languages in the world, with its demand increasing by the minute. Pytest - one of the most actively maintained testing frameworks in the industry - provides an incredible set of tools for faster, less stressful testing. In this course, you'll learn how to eliminate boilerplate setup and teardown code, run multiple tests simultaneously, and track your test run history to identify slow or problematic tests.
Beginning with a brief introduction and a step-by-step setup of pytest, this course will walk you through each session. You'll discover what makes a good framework, and, more importantly, what makes a bad one. As you advance, you'll learn how to use test searching to avoid cumbersome test suites, and how fixtures can eliminate up to 80% of code in case of code bloat. This interactive course is also equipped with information-rich videos to help you grasp the concepts with ease.
By the end of this course, you'll be ready to build high-performance, well-organized, scalable test frameworks on the professional level.

All codes and supporting files are available at-
https://github.com/PacktPublishing/Elegant-Automation-Frameworks-with-Python-and-Pytest</p>
        <h2>What You Will Learn</h2><p>Delve into one of the most in-demand fields in today s tech market - automated testing<br>Build high-performance automated test suites with actionable reporting<br>Discover how to eliminate boilerplate setup and teardown code<br>Find out how to run multiple tests simultaneously<br>Get to grips with tracking the history of your test runs</p>
        <h2>Audience</h2><p>This course is for anyone looking to build or improve an automated testing framework.</p>
        <h2>Approach</h2><p>Complete with code samples and information-rich videos, this course will help you understand the concepts easily.</p>
        <h2>Key Features</h2><p>Become proficient in automated testing using pytest * Create a well-organized, scalable test framework on a professional level * Find out how fixtures can eliminate up to 80% of code in a bloated codebase</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/elegant-automation-frameworks-with-python-and-pytest</p>
        <h2>About the Author</h2><h3>Brandon Blair</h3><p>Brandon Blair is a Software Engineer who designs fast, scalable, and maintainable frameworks for automated testing in the UI (browser), backend/API, and mobile testing domains. He is passionate about delivering critical insights to teams at short notice by giving them powerful automation tools and enjoys teaching strong foundational concepts to others, along with focusing on problem-solving.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This lecture introduces the course.</p></td></tr></tbody></table><br><h4>2. Setting Up Your Environment</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Setup Python 3 (Windows)</p><p style='margin: 0'>Let's set up Python 3 on your Windows machine, and ensure we're working with the same tools, so you don't run into unnecessary hardship.</p></td></tr><tr><td style='padding: 15px;'><p>2. Setting up Your Virtual Environment (Windows)</p><p style='margin: 0'>In order to avoid problems, it's best when we are working with the same tools.</p></td></tr><tr><td style='padding: 15px;'><p>3. Setting up Python 3 and the Virtual Environment (Mac OS / Linux)</p><p style='margin: 0'>For those of you working on Mac OS or linux, we go over setting up Python 3 and your virtual environment.</p></td></tr></tbody></table><br><h4>3. The Pytest Framework</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Getting started with Pytest</p><p style='margin: 0'>In this session we will set up a simple framework around some dummy tests and explain the pytest.ini file.</p></td></tr><tr><td style='padding: 15px;'><p>2. Test Searching</p><p style='margin: 0'>In this session we will discuss why test searching is so amazing, and why you should never run a test case file ever again.</p></td></tr><tr><td style='padding: 15px;'><p>3. Save Time and Code with Test Fixtures</p><p style='margin: 0'>Fixtures are one of the most powerful tools Pytest offers.</p></td></tr><tr><td style='padding: 15px;'><p>4. Reporting Test Results and Tracking Test History</p><p style='margin: 0'>In this video, the author demonstrates a quick reporting recipe using the open source Continuous Integration tool "Jenkins", since many students may work on teams that use Jenkins. The concept is transferable to many other tools that read XML test reports.</p></td></tr><tr><td style='padding: 15px;'><p>5. Customizing Test Runs with the Command Line and Configuration Files</p><p style='margin: 0'>We will learn how to pass data into your test run using the command line and write a self-building configuration file that allows testing in different environments without changing any code.</p></td></tr><tr><td style='padding: 15px;'><p>6. Handling Skips and Expected Failures</p><p style='margin: 0'>How do we skip tests without forgetting we ever wrote them? How do we handle tests that are expected to fail? We cover both solutions in today's lecture</p></td></tr><tr><td style='padding: 15px;'><p>7. Cross-Browser and Data-driven testing with parametrize</p><p style='margin: 0'>In this lecture we learn a recipe for testing multiple browsers without writing additional tests, and how to perform Data-driven testing using the contents of a JSON file.</p></td></tr><tr><td style='padding: 15px;'><p>8. Fast Testing with Pytest-xdist, and Parallel vs Concurrent</p><p style='margin: 0'>Learn the difference between parallelism and concurrency, and how we can leverage parallel testing to slash run-times on our test suites.</p></td></tr></tbody></table><br><h4>4. Writing Great Tests</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Writing Unit Tests (White Box Testing)</p><p style='margin: 0'>We will learn how to write valuable, well-scoped unit tests to expose bugs before we push our changes to the repository.</p></td></tr><tr><td style='padding: 15px;'><p>2. Running Unit Tests with Tox</p><p style='margin: 0'>To set up our unit tests for primetime, it's important to separate our testing harness and cases from the library we are testing. We will use a tool called Tox to make this process fast, fluid, and repeatable.</p></td></tr><tr><td style='padding: 15px;'><p>3. Writing Functional Tests (Black/Grey Box Testing)</p><p style='margin: 0'>When testing something from the "outside", it's important that we structure our tests and framework so that our intent is clear, and so that the tests are maintainable by other people.</p></td></tr></tbody></table>

Leverage pytest's fast, scalable, and professional-grade framework design to build and run automated test suites like a pro
Python is one of the most popular programming languages in the world, with its demand increasing by the minute. Pytest - one of the most actively maintained testing frameworks in the industry - provides an incredible set of tools for faster, less stressful testing. In this course, you'll learn how to eliminate boilerplate setup and teardown code, run multiple tests simultaneously, and track your test run history to identify slow or problematic tests.
Beginning with a brief introduction and a step-by-step setup of pytest, this course will walk you through each session. You'll discover what makes a good framework, and, more importantly, what makes a bad one. As you advance, you'll learn how to use test searching to avoid cumbersome test suites, and how fixtures can eliminate up to 80% of code in case of code bloat. This interactive course is also equipped with information-rich videos to help you grasp the concepts with ease.
By the end of this course, you'll be ready to build high-performance, well-organized, scalable test frameworks on the professional level. All codes and supporting files are available at-
https://github.com/PacktPublishing/Elegant-Automation-Frameworks-with-Python-and-Pytest
What You Will Learn
Delve into one of the most in-demand fields in today s tech market - automated testing
Build high-performance automated test suites with actionable reporting
Discover how to eliminate boilerplate setup and teardown code
Find out how to run multiple tests simultaneously
Get to grips with tracking the history of your test runs
Audience
This course is for anyone looking to build or improve an automated testing framework.
Approach
Complete with code samples and information-rich videos, this course will help you understand the concepts easily.
Key Features
Become proficient in automated testing using pytest * Create a well-organized, scalable test framework on a professional level * Find out how fixtures can eliminate up to 80% of code in a bloated codebase
Github Repo
https://github.com/packtpublishing/elegant-automation-frameworks-with-python-and-pytest
About the Author
Brandon Blair
Brandon Blair is a Software Engineer who designs fast, scalable, and maintainable frameworks for automated testing in the UI (browser), backend/API, and mobile testing domains. He is passionate about delivering critical insights to teams at short notice by giving them powerful automation tools and enjoys teaching strong foundational concepts to others, along with focusing on problem-solving.
Course Outline
1. Introduction

1. Introduction
This lecture introduces the course.
2. Setting Up Your Environment

1. Setup Python 3 (Windows)
Let's set up Python 3 on your Windows machine, and ensure we're working with the same tools, so you don't run into unnecessary hardship.
2. Setting up Your Virtual Environment (Windows)
In order to avoid problems, it's best when we are working with the same tools.
3. Setting up Python 3 and the Virtual Environment (Mac OS / Linux)
For those of you working on Mac OS or linux, we go over setting up Python 3 and your virtual environment.
3. The Pytest Framework

1. Getting started with Pytest
In this session we will set up a simple framework around some dummy tests and explain the pytest.ini file.
2. Test Searching
In this session we will discuss why test searching is so amazing, and why you should never run a test case file ever again.
3. Save Time and Code with Test Fixtures
Fixtures are one of the most powerful tools Pytest offers.
4. Reporting Test Results and Tracking Test History
In this video, the author demonstrates a quick reporting recipe using the open source Continuous Integration tool "Jenkins", since many students may work on teams that use Jenkins. The concept is transferable to many other tools that read XML test reports.
5. Customizing Test Runs with the Command Line and Configuration Files
We will learn how to pass data into your test run using the command line and write a self-building configuration file that allows testing in different environments without changing any code.
6. Handling Skips and Expected Failures
How do we skip tests without forgetting we ever wrote them? How do we handle tests that are expected to fail? We cover both solutions in today's lecture
7. Cross-Browser and Data-driven testing with parametrize
In this lecture we learn a recipe for testing multiple browsers without writing additional tests, and how to perform Data-driven testing using the contents of a JSON file.
8. Fast Testing with Pytest-xdist, and Parallel vs Concurrent
Learn the difference between parallelism and concurrency, and how we can leverage parallel testing to slash run-times on our test suites.
4. Writing Great Tests

1. Writing Unit Tests (White Box Testing)
We will learn how to write valuable, well-scoped unit tests to expose bugs before we push our changes to the repository.
2. Running Unit Tests with Tox
To set up our unit tests for primetime, it's important to separate our testing harness and cases from the library we are testing. We will use a tool called Tox to make this process fast, fluid, and repeatable.
3. Writing Functional Tests (Black/Grey Box Testing)
When testing something from the "outside", it's important that we structure our tests and framework so that our intent is clear, and so that the tests are maintainable by other people.

Leverage pytest's fast, scalable, and professional-grade framework design to build and run automated test suites like a pro

Elegant Automation Frameworks with Python and Pytest

<strong>If you are someone with a background in Python programming and is interested in presenting your analysis in interactive web-based dashboards, then you are in the right place. This course primarily focuses on Dash, along with other key data science libraries, including Pandas and Plotly. Learn to use Dash and Plotly in Python which can help you to visualize your critical insights and KPIs in web apps that are easily sharable.</strong>
        <p>Data visualization is a critical part of data science, in this quick and practical course you will learn how to create a great-looking interactive dashboard with Dash and Python. With this new skill, you will be able to present and share your analysis better with your customers' executives and the rest of your team.

This course is broken down into 5 parts and it is necessary to follow the structure as each part is built on top of the other. The first part is an introduction to Plotly Dash followed by building the layout of dashboards. The third part is how to make dashboards interactive with callbacks, fourth part introduces us to customize the look of dashboards. The last and final part is a business-centric project case study on creating an interactive map dashboard.

Throughout the course, you will be using 3 real-world datasets, which are the World Happiness dataset, FIFA Soccer dataset, and US electricity prices to help you learn Dash more.

By the end of the course, you will learn to build dashboards from scratch, by customizing their look and adding interactive features, with all free Python libraries.

All resources and code files are placed here: https://github.com/PacktPublishing/Python-Interactive-Dashboards-with-Plotly-Dash</p>
        <h2>What You Will Learn</h2><p>Learn to create a grid layout in dashboards<br>Create interactive graphs that are clickable<br>Create data tables in dashboards<br>Create a dashboard with a navigation bar and cards<br>Learn to add buttons to dashboards<br>Learn the basics of Python with this course</p>
        <h2>Audience</h2><p>This course can be taken by any Python programmer who wants to present their analyses in interactive web-based dashboards.</p>
        <h2>Approach</h2><p>This course includes instructional videos that walk you through the process step-by-step. You can learn at your own pace and download the Python scripts to use for your own projects.</p>
        <h2>Key Features</h2><p>Learn how to set up the layout of dashboards with Dash components * Make more dynamic dashboards with chained interactive features * Use Plotly to create plots including line charts, Choropleth maps</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Python-Interactive-Dashboards-with-Plotly-Dash</p>
        <h2>About the Author</h2><h3>Just Into Data</h3><p>Just Into Data is the brainchild of Justin and Lianne. Justin is an experienced data scientist in many different fields, such as marketing, anti-money laundering, and big data technologies. He also has a bachelor's degree in computer engineering and a master's degree in statistics.

Lianne is an experienced statistician who has worked in the central bank as well as commercial banks, where she monitored major financial institutions and conducted fraud analysis. She has both a bachelor's and a master's degree in statistics.</p>
        <h2>Course Outline</h2><h4>1. Let's Get Started</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video introduces you to the course and the author.</p></td></tr><tr><td style='padding: 15px;'><p>2. Course Overview</p><p style='margin: 0'>This video introduces you to the course overview.</p></td></tr></tbody></table><br><h4>2. Python Crash Course</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Setting Up Python Environment</p><p style='margin: 0'>This video explains how to set up a Python environment.</p></td></tr><tr><td style='padding: 15px;'><p>2. Overview of Data Types, Numeric, Define Variables</p><p style='margin: 0'>This video explains an overview of data types, numeric, define variables.</p></td></tr><tr><td style='padding: 15px;'><p>3. Strings, Common Functions, and Methods</p><p style='margin: 0'>This video explains strings, common functions, and methods.</p></td></tr><tr><td style='padding: 15px;'><p>4. Lists, Tuples, Sets, Dictionaries, Booleans</p><p style='margin: 0'>This video explains lists, tuples, sets, dictionaries, Booleans.</p></td></tr><tr><td style='padding: 15px;'><p>5. If Statements, Loops</p><p style='margin: 0'>This video explains if statements, loops.</p></td></tr><tr><td style='padding: 15px;'><p>6. Define Functions, Use Packages</p><p style='margin: 0'>This video defines functions, use packages.</p></td></tr></tbody></table><br><h4>3. Introduction to Plotly Dash</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What is Dash</p><p style='margin: 0'>This video explains what Dash is.</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating Your First Dashboard</p><p style='margin: 0'>This video explains how to create your first dashboard.</p></td></tr></tbody></table><br><h4>4. Building the Layout of Dashboards</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. HTML Components Overview</p><p style='margin: 0'>This video explains HTML components overview.</p></td></tr><tr><td style='padding: 15px;'><p>2. Core Components Overview</p><p style='margin: 0'>This video explains the overview of core components.</p></td></tr></tbody></table><br><h4>5. Making Dashboards Interactive with Callbacks</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to Callbacks</p><p style='margin: 0'>This video introduces you to callbacks.</p></td></tr><tr><td style='padding: 15px;'><p>2. Building Callbacks with Single Input and Output</p><p style='margin: 0'>This video introduces you to building callbacks with single input and output.</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating Interactive Plotly Figures</p><p style='margin: 0'>This video explains how to create interactive Plotly figures.</p></td></tr><tr><td style='padding: 15px;'><p>4. Building Callbacks with Multiple Inputs and Outputs</p><p style='margin: 0'>This video explains how to build callbacks with multiple inputs and outputs.</p></td></tr><tr><td style='padding: 15px;'><p>5. Chaining Callbacks' Inputs and Outputs</p><p style='margin: 0'>This video explains how to chain callbacks' inputs and outputs.</p></td></tr><tr><td style='padding: 15px;'><p>6. Controlling Callbacks with States (Button)</p><p style='margin: 0'>This video explains how to control callbacks with States (button).</p></td></tr></tbody></table><br><h4>6. Capstone Project I</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Avocado Prices Dashboard Overview</p><p style='margin: 0'>This video explains an overview of the Avocado prices dashboard.</p></td></tr></tbody></table><br><h4>7. Customizing the Look of Dashboards</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Customizing with Inline CSS</p><p style='margin: 0'>This video explains customizing with inline CSS.</p></td></tr><tr><td style='padding: 15px;'><p>2. Customizing with External CSS</p><p style='margin: 0'>This video explains customizing with external CSS.</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating a Grid Layout</p><p style='margin: 0'>This video explains how to create a grid layout.</p></td></tr><tr><td style='padding: 15px;'><p>4. Building a Navigation Bar</p><p style='margin: 0'>This video explains how to build a navigation bar.</p></td></tr><tr><td style='padding: 15px;'><p>5. Building a Deck of Cards</p><p style='margin: 0'>This video explains how to build a deck of cards.</p></td></tr></tbody></table><br><h4>8. Case Study I: Creating an Interactive Map Dashboard</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Setting Up the Layout: RangeSlider</p><p style='margin: 0'>This video explains setting up the layout: RangeSlider.</p></td></tr><tr><td style='padding: 15px;'><p>2. Setting Up the Layout: Choropleth Map</p><p style='margin: 0'>This video explains Choropleth map.</p></td></tr><tr><td style='padding: 15px;'><p>3. Setting Up the Layout: DataTable</p><p style='margin: 0'>This video explains DataTable.</p></td></tr><tr><td style='padding: 15px;'><p>4. Adding Callbacks: Update the Map</p><p style='margin: 0'>This video explains how to update the map.</p></td></tr><tr><td style='padding: 15px;'><p>5. Adding Callbacks: Update the DataTable</p><p style='margin: 0'>This video explains how to update the DataTable.</p></td></tr></tbody></table><br><h4>9. Case Study II: Building a Live Updating Financial Dashboard</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Setting Up the Layout: Input and Button</p><p style='margin: 0'>This video explains setting up the layout: Input and Button.</p></td></tr><tr><td style='padding: 15px;'><p>2. Setting Up the Layout: Candlestick and DataTable</p><p style='margin: 0'>This video explains setting up the layout: Candlestick and DataTable.</p></td></tr><tr><td style='padding: 15px;'><p>3. Setting Up the Layout: Tabs</p><p style='margin: 0'>This video explains setting up the layout: Tabs.</p></td></tr><tr><td style='padding: 15px;'><p>4. Setting Up the Layout: Interval</p><p style='margin: 0'>This video explains setting up the layout: Interval.</p></td></tr><tr><td style='padding: 15px;'><p>5. Adding Callbacks: Live Update the Chart</p><p style='margin: 0'>This video explains adding callbacks: live update the chart.</p></td></tr><tr><td style='padding: 15px;'><p>6. Adding Callbacks: Live Update the DataTable</p><p style='margin: 0'>This video explains how to update the DataTable.</p></td></tr></tbody></table><br><h4>10. Capstone Project II</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Life Expectancy Dashboard Overview</p><p style='margin: 0'>This video gives an overview of the life expectancy dashboard.</p></td></tr></tbody></table><br><h4>11. Bonus Materials</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to Jupyter Dash</p><p style='margin: 0'>This video introduces you to the Jupyter dashboard.</p></td></tr></tbody></table>

If you are someone with a background in Python programming and is interested in presenting your analysis in interactive web-based dashboards, then you are in the right place. This course primarily focuses on Dash, along with other key data science libraries, including Pandas and Plotly. Learn to use Dash and Plotly in Python which can help you to visualize your critical insights and KPIs in web apps that are easily sharable.
Data visualization is a critical part of data science, in this quick and practical course you will learn how to create a great-looking interactive dashboard with Dash and Python. With this new skill, you will be able to present and share your analysis better with your customers' executives and the rest of your team. This course is broken down into 5 parts and it is necessary to follow the structure as each part is built on top of the other. The first part is an introduction to Plotly Dash followed by building the layout of dashboards. The third part is how to make dashboards interactive with callbacks, fourth part introduces us to customize the look of dashboards. The last and final part is a business-centric project case study on creating an interactive map dashboard. Throughout the course, you will be using 3 real-world datasets, which are the World Happiness dataset, FIFA Soccer dataset, and US electricity prices to help you learn Dash more. By the end of the course, you will learn to build dashboards from scratch, by customizing their look and adding interactive features, with all free Python libraries. All resources and code files are placed here: https://github.com/PacktPublishing/Python-Interactive-Dashboards-with-Plotly-Dash
What You Will Learn
Learn to create a grid layout in dashboards
Create interactive graphs that are clickable
Create data tables in dashboards
Create a dashboard with a navigation bar and cards
Learn to add buttons to dashboards
Learn the basics of Python with this course
Audience
This course can be taken by any Python programmer who wants to present their analyses in interactive web-based dashboards.
Approach
This course includes instructional videos that walk you through the process step-by-step. You can learn at your own pace and download the Python scripts to use for your own projects.
Key Features
Learn how to set up the layout of dashboards with Dash components * Make more dynamic dashboards with chained interactive features * Use Plotly to create plots including line charts, Choropleth maps
Github Repo
https://github.com/PacktPublishing/Python-Interactive-Dashboards-with-Plotly-Dash
About the Author
Just Into Data
Just Into Data is the brainchild of Justin and Lianne. Justin is an experienced data scientist in many different fields, such as marketing, anti-money laundering, and big data technologies. He also has a bachelor's degree in computer engineering and a master's degree in statistics. Lianne is an experienced statistician who has worked in the central bank as well as commercial banks, where she monitored major financial institutions and conducted fraud analysis. She has both a bachelor's and a master's degree in statistics.
Course Outline
1. Let's Get Started

1. Introduction
This video introduces you to the course and the author.
2. Course Overview
This video introduces you to the course overview.
2. Python Crash Course

1. Setting Up Python Environment
This video explains how to set up a Python environment.
2. Overview of Data Types, Numeric, Define Variables
This video explains an overview of data types, numeric, define variables.
3. Strings, Common Functions, and Methods
This video explains strings, common functions, and methods.
4. Lists, Tuples, Sets, Dictionaries, Booleans
This video explains lists, tuples, sets, dictionaries, Booleans.
5. If Statements, Loops
This video explains if statements, loops.
6. Define Functions, Use Packages
This video defines functions, use packages.
3. Introduction to Plotly Dash

1. What is Dash
This video explains what Dash is.
2. Creating Your First Dashboard
This video explains how to create your first dashboard.
4. Building the Layout of Dashboards

1. HTML Components Overview
This video explains HTML components overview.
2. Core Components Overview
This video explains the overview of core components.
5. Making Dashboards Interactive with Callbacks

1. Introduction to Callbacks
This video introduces you to callbacks.
2. Building Callbacks with Single Input and Output
This video introduces you to building callbacks with single input and output.
3. Creating Interactive Plotly Figures
This video explains how to create interactive Plotly figures.
4. Building Callbacks with Multiple Inputs and Outputs
This video explains how to build callbacks with multiple inputs and outputs.
5. Chaining Callbacks' Inputs and Outputs
This video explains how to chain callbacks' inputs and outputs.
6. Controlling Callbacks with States (Button)
This video explains how to control callbacks with States (button).
6. Capstone Project I

1. Avocado Prices Dashboard Overview
This video explains an overview of the Avocado prices dashboard.
7. Customizing the Look of Dashboards

1. Customizing with Inline CSS
This video explains customizing with inline CSS.
2. Customizing with External CSS
This video explains customizing with external CSS.
3. Creating a Grid Layout
This video explains how to create a grid layout.
4. Building a Navigation Bar
This video explains how to build a navigation bar.
5. Building a Deck of Cards
This video explains how to build a deck of cards.
8. Case Study I: Creating an Interactive Map Dashboard

1. Setting Up the Layout: RangeSlider
This video explains setting up the layout: RangeSlider.
2. Setting Up the Layout: Choropleth Map
This video explains Choropleth map.
3. Setting Up the Layout: DataTable
This video explains DataTable.
4. Adding Callbacks: Update the Map
This video explains how to update the map.
5. Adding Callbacks: Update the DataTable
This video explains how to update the DataTable.
9. Case Study II: Building a Live Updating Financial Dashboard

1. Setting Up the Layout: Input and Button
This video explains setting up the layout: Input and Button.
2. Setting Up the Layout: Candlestick and DataTable
This video explains setting up the layout: Candlestick and DataTable.
3. Setting Up the Layout: Tabs
This video explains setting up the layout: Tabs.
4. Setting Up the Layout: Interval
This video explains setting up the layout: Interval.
5. Adding Callbacks: Live Update the Chart
This video explains adding callbacks: live update the chart.
6. Adding Callbacks: Live Update the DataTable
This video explains how to update the DataTable.
10. Capstone Project II

1. Life Expectancy Dashboard Overview
This video gives an overview of the life expectancy dashboard.
11. Bonus Materials

1. Introduction to Jupyter Dash
This video introduces you to the Jupyter dashboard.

Data Visualization

If you are someone with a background in Python programming and is interested in presenting your analysis in interactive web-based dashboards, then you are in the right place. This course primarily focuses on Dash, along with other key data science libraries, including Pandas and Plotly. Learn to use Dash and Plotly in Python which can help you to visualize your critical insights and KPIs in web apps that are easily sharable.

Python Interactive Dashboards with Plotly Dash

<strong>This course covers the Django web framework from the beginning and also covers advanced Django features. Besides Django, the course also covers HTML, CSS, and Bootstrap, which will introduce full-stack development with Django so that you can build complete web apps from scratch. Learn to develop your own web applications with the help of this course.</strong>
        <p>The course teaching approach is learn-by-doing. You will learn to build two different apps: a modern Bootstrap blog website with a complete blog author interface and a dynamic Google Translate-like translator web app. The two apps have been chosen carefully to cover all core Django features. The apps are also extendible, allowing you to improve and add features to the apps while sharpening your Django skills and building your own GitHub portfolio.

Among other topics, you will learn the model-view-template app structure of Django. You will also learn to set up SQL databases and connect the database with your app. You will learn to build complete web pages equipped with HTML widgets and create HTML forms that handle GET and POST HTTP requests. In addition, you will learn how to create and manage URL patterns for your app pages. You will also learn how to build an admin interface, which is useful when building content websites such as blogs, where content creators and other admins can use the admin interface to add content to the website without interfering with the codebase.

You will also get an introduction to HTML and learn to create front-end widgets such as input boxes, buttons, and HTML forms. You will learn to give your web app a modern look by adding Bootstrap styling to your website.

By the end of the course, you will have all the skills to build your own web apps using Django, and you will know where to look whenever you need to add new Django features to your apps.

All resources and code files are placed here: https://github.com/PacktPublishing/Django-Crash-Course-with-Examples</p>
        <h2>What You Will Learn</h2><p>Understand the Django app architecture<br>Learn to use the model-view-template design<br>Handle GET and POST HTTP requests<br>Learn to create admin interfaces<br>Learn to create HTML forms<br>Learn about template filters and template inheritance</p>
        <h2>Audience</h2><p>The course is beneficial for those who want to turn their ideas into web apps. You will be able to create your own web apps in no time. You will also be able to start your web development career with this course. Finally, the program assumes you know Python basics already. If you know Python basics, you can understand and use the Django codebase to build web applications, and this course will take you step-by-step through that process.</p>
        <h2>Approach</h2><p>The course follows a hands-on approach where students learn by building real-world web apps. You will create a blog app and a translator web app. You will also learn how to integrate the two, so you know how to reuse and extend apps. You will have your own unique apps to create your own GitHub portfolio by the end of the course.</p>
        <h2>Key Features</h2><p>Learn the different components of the Django web framework using real-world examples * Learn and test for yourself and understand how every component behaves by running them on your browser * Understand and apply the communication between Django and the SQL database</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Django-Crash-Course-with-Examples</p>
        <h2>About the Author</h2><h3>PythonHow, Ardit Sulce</h3><p>Ardit Sulce is a Python programmer, teacher, and founder of PythonHow. He graduated in 2013 with a master's degree in science (geospatial technologies) from the University of Muenster in Germany, focusing on using Python for remote sensing. Ardit has worked with companies such as the Center for Conservation Geography to map and understand Australian ecosystems, image processing with the Swiss in-Terra, and data mining to gain business insights with the Australian Rapid Intelligence.</p>
        <h2>Course Outline</h2><h4>1. Getting Started</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video introduces you to the course outcomes.</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing Python and IDE on Windows</p><p style='margin: 0'>This video introduces you to Installing Python and IDE on Windows.</p></td></tr><tr><td style='padding: 15px;'><p>3. Installing Python and IDE on Mac</p><p style='margin: 0'>This video explains installing Python and IDE on Mac.</p></td></tr><tr><td style='padding: 15px;'><p>4. Installing Python and IDE on Linux</p><p style='margin: 0'>This video introduces you to installing Python and IDE on Linux.</p></td></tr><tr><td style='padding: 15px;'><p>5. Setting Up a Virtual Environment and Installing Django 4</p><p style='margin: 0'>This video introduces you to setting up a virtual environment and installing Django 4.</p></td></tr><tr><td style='padding: 15px;'><p>6. Django Versus Other Python Web Frameworks</p><p style='margin: 0'>This video introduces you to Django versus other Python web frameworks.</p></td></tr></tbody></table><br><h4>2. Creating Models</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Creating a Django Project</p><p style='margin: 0'>This video explains creating a Django project.</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating an Admin User</p><p style='margin: 0'>This video explains creating an admin user.</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating a Blog App</p><p style='margin: 0'>This video explains creating a blog app.</p></td></tr><tr><td style='padding: 15px;'><p>4. Creating the Post Model</p><p style='margin: 0'>This video explains creating the post model.</p></td></tr><tr><td style='padding: 15px;'><p>5. The Architecture of a Django App - Understanding Django</p><p style='margin: 0'>This video explains the architecture of a Django app - understanding Django.</p></td></tr></tbody></table><br><h4>3. HTML Templates and URL Patterns</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Creating an HTML Template</p><p style='margin: 0'>This video explains creating an HTML template.</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating a View to Connect the Model to the Template</p><p style='margin: 0'>This video explains creating a view to connect the model to the template.</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating URL Patterns</p><p style='margin: 0'>This video explains creating URL patterns.</p></td></tr></tbody></table><br><h4>4. The Admin Interfaces</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Creating Posts from the Admin Interface</p><p style='margin: 0'>This video explains creating posts from the admin interface.</p></td></tr></tbody></table><br><h4>5. Creating Web Pages</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Creating a Homepage</p><p style='margin: 0'>This video introduces you to creating a homepage.</p></td></tr><tr><td style='padding: 15px;'><p>2. Adding an About Page</p><p style='margin: 0'>This video explains adding an about page.</p></td></tr><tr><td style='padding: 15px;'><p>3. Showing a List of Posts on the Homepage</p><p style='margin: 0'>This video explains showing a list of posts on the homepage.</p></td></tr><tr><td style='padding: 15px;'><p>4. Using URL Tags to Create Links</p><p style='margin: 0'>This video explains using URL tags to create links.</p></td></tr></tbody></table><br><h4>6. Integrating Bootstrap</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Making the Webpage Modern with Bootstrap</p><p style='margin: 0'>This video explains making the webpage modern with Bootstrap.</p></td></tr></tbody></table><br><h4>7. Template Filters and Template Inheritance</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Django Template Filters</p><p style='margin: 0'>This video introduces you to Django template filters.</p></td></tr><tr><td style='padding: 15px;'><p>2. Template Inheritance</p><p style='margin: 0'>This video explains the template inheritance.</p></td></tr><tr><td style='padding: 15px;'><p>3. Styling the Navigation Menu</p><p style='margin: 0'>This video explains styling the navigation menu.</p></td></tr></tbody></table><br><h4>8. Building a Translator Web App</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction to the Translator App</p><p style='margin: 0'>This video introduces the translator app.</p></td></tr><tr><td style='padding: 15px;'><p>2. The Steps to Complete the Translator App</p><p style='margin: 0'>This video explains the steps to complete the translator app.</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating the Empty Translator App</p><p style='margin: 0'>This video explains creating the empty translator app.</p></td></tr><tr><td style='padding: 15px;'><p>4. Creating the HTML Form</p><p style='margin: 0'>This video explains how to create the HTML form.</p></td></tr><tr><td style='padding: 15px;'><p>5. Configuring the URLs</p><p style='margin: 0'>This video explains configuring the URLs.</p></td></tr><tr><td style='padding: 15px;'><p>6. Creating the Form-View</p><p style='margin: 0'>This video explains how to create a form-view.</p></td></tr><tr><td style='padding: 15px;'><p>7. Getting and Returning User Input Through a Form</p><p style='margin: 0'>This video explains getting and returning user input through a form.</p></td></tr><tr><td style='padding: 15px;'><p>8. Finishing the Translator App</p><p style='margin: 0'>This video explains finishing the translator app.</p></td></tr></tbody></table>

This course covers the Django web framework from the beginning and also covers advanced Django features. Besides Django, the course also covers HTML, CSS, and Bootstrap, which will introduce full-stack development with Django so that you can build complete web apps from scratch. Learn to develop your own web applications with the help of this course.
The course teaching approach is learn-by-doing. You will learn to build two different apps: a modern Bootstrap blog website with a complete blog author interface and a dynamic Google Translate-like translator web app. The two apps have been chosen carefully to cover all core Django features. The apps are also extendible, allowing you to improve and add features to the apps while sharpening your Django skills and building your own GitHub portfolio. Among other topics, you will learn the model-view-template app structure of Django. You will also learn to set up SQL databases and connect the database with your app. You will learn to build complete web pages equipped with HTML widgets and create HTML forms that handle GET and POST HTTP requests. In addition, you will learn how to create and manage URL patterns for your app pages. You will also learn how to build an admin interface, which is useful when building content websites such as blogs, where content creators and other admins can use the admin interface to add content to the website without interfering with the codebase. You will also get an introduction to HTML and learn to create front-end widgets such as input boxes, buttons, and HTML forms. You will learn to give your web app a modern look by adding Bootstrap styling to your website. By the end of the course, you will have all the skills to build your own web apps using Django, and you will know where to look whenever you need to add new Django features to your apps. All resources and code files are placed here: https://github.com/PacktPublishing/Django-Crash-Course-with-Examples
What You Will Learn
Understand the Django app architecture
Learn to use the model-view-template design
Handle GET and POST HTTP requests
Learn to create admin interfaces
Learn to create HTML forms
Learn about template filters and template inheritance
Audience
The course is beneficial for those who want to turn their ideas into web apps. You will be able to create your own web apps in no time. You will also be able to start your web development career with this course. Finally, the program assumes you know Python basics already. If you know Python basics, you can understand and use the Django codebase to build web applications, and this course will take you step-by-step through that process.
Approach
The course follows a hands-on approach where students learn by building real-world web apps. You will create a blog app and a translator web app. You will also learn how to integrate the two, so you know how to reuse and extend apps. You will have your own unique apps to create your own GitHub portfolio by the end of the course.
Key Features
Learn the different components of the Django web framework using real-world examples * Learn and test for yourself and understand how every component behaves by running them on your browser * Understand and apply the communication between Django and the SQL database
Github Repo
https://github.com/PacktPublishing/Django-Crash-Course-with-Examples
About the Author
PythonHow, Ardit Sulce
Ardit Sulce is a Python programmer, teacher, and founder of PythonHow. He graduated in 2013 with a master's degree in science (geospatial technologies) from the University of Muenster in Germany, focusing on using Python for remote sensing. Ardit has worked with companies such as the Center for Conservation Geography to map and understand Australian ecosystems, image processing with the Swiss in-Terra, and data mining to gain business insights with the Australian Rapid Intelligence.
Course Outline
1. Getting Started

1. Introduction
This video introduces you to the course outcomes.
2. Installing Python and IDE on Windows
This video introduces you to Installing Python and IDE on Windows.
3. Installing Python and IDE on Mac
This video explains installing Python and IDE on Mac.
4. Installing Python and IDE on Linux
This video introduces you to installing Python and IDE on Linux.
5. Setting Up a Virtual Environment and Installing Django 4
This video introduces you to setting up a virtual environment and installing Django 4.
6. Django Versus Other Python Web Frameworks
This video introduces you to Django versus other Python web frameworks.
2. Creating Models

1. Creating a Django Project
This video explains creating a Django project.
2. Creating an Admin User
This video explains creating an admin user.
3. Creating a Blog App
This video explains creating a blog app.
4. Creating the Post Model
This video explains creating the post model.
5. The Architecture of a Django App - Understanding Django
This video explains the architecture of a Django app - understanding Django.
3. HTML Templates and URL Patterns

1. Creating an HTML Template
This video explains creating an HTML template.
2. Creating a View to Connect the Model to the Template
This video explains creating a view to connect the model to the template.
3. Creating URL Patterns
This video explains creating URL patterns.
4. The Admin Interfaces

1. Creating Posts from the Admin Interface
This video explains creating posts from the admin interface.
5. Creating Web Pages

1. Creating a Homepage
This video introduces you to creating a homepage.
2. Adding an About Page
This video explains adding an about page.
3. Showing a List of Posts on the Homepage
This video explains showing a list of posts on the homepage.
4. Using URL Tags to Create Links
This video explains using URL tags to create links.
6. Integrating Bootstrap

1. Making the Webpage Modern with Bootstrap
This video explains making the webpage modern with Bootstrap.
7. Template Filters and Template Inheritance

1. Django Template Filters
This video introduces you to Django template filters.
2. Template Inheritance
This video explains the template inheritance.
3. Styling the Navigation Menu
This video explains styling the navigation menu.
8. Building a Translator Web App

1. Introduction to the Translator App
This video introduces the translator app.
2. The Steps to Complete the Translator App
This video explains the steps to complete the translator app.
3. Creating the Empty Translator App
This video explains creating the empty translator app.
4. Creating the HTML Form
This video explains how to create the HTML form.
5. Configuring the URLs
This video explains configuring the URLs.
6. Creating the Form-View
This video explains how to create a form-view.
7. Getting and Returning User Input Through a Form
This video explains getting and returning user input through a form.
8. Finishing the Translator App
This video explains finishing the translator app.

Web Development

HTML

This course covers the Django web framework from the beginning and also covers advanced Django features. Besides Django, the course also covers HTML, CSS, and Bootstrap, which will introduce full-stack development with Django so that you can build complete web apps from scratch. Learn to develop your own web applications with the help of this course.

Django Crash Course with Examples

<strong>Learn Python OOP language used diversely in applications like data science, game/web development, machine learning, and AI. This course provides all you need to master OOPs like classes, objects, data abstraction, methods, overloading, and inheritance. The course primarily aims to help you tackle complex programming and use OOP paradigms efficiently.</strong>
        <p>Python is a fantastic OOP language that lets you use functional and OOP paradigms. Python offers several benefits compared to other programming languages like Java, C++ or R. It is a dynamic language, with high-level data types. Python is easier to learn for beginners as its codes are more readable and intuitive.

This course is designed to take you through the fundamentals of OOPs and understanding how it works. During this course, you will learn about important concepts such as classes, objects, abstraction, method overloading, and inheritance in sufficient detail. The course will also take you through the concepts of objects and attributes, mathematical operators, callable functions, encapsulation, inheritance and method resolution comprehensively. The course explains the OOP paradigm and lets you create class hierarchies using the OOP design process.

By the end of the course, you will be able to design and implement Python programs for complex issues and make good use of the OOP features like classes and inheritance and apply your knowledge completing assignments that simulate real-world scenarios.

All resources are available at: https://github.com/PacktPublishing/Python---Object-Oriented-Programming</p>
        <h2>What You Will Learn</h2><p>Create class hierarchies using the object-oriented design process<br>Understand the difference between class and instance variables<br>Make an object indexable, callable, and comparable<br>Design and implement Python programs for complex problems<br>Put to code the language features such as classes and inheritance<br>Tackle complex code with OOP paradigm, design, and implementation</p>
        <h2>Audience</h2><p>This course provides new developers who know Python basics to expand their knowledge and developers and learners who wish to learn OOP in Python. Developers involved with game development, GUI programming, AI, machine learning, and other computed automation can benefit from this course. The concepts and techniques can be applied to other programming languages, so intermediate-level developers wishing to advance their programming skillsets can also learn from this course for career advancement. To get the most from this course, you need to be an intermediate-level programmer in Python.</p>
        <h2>Approach</h2><p>This course provides high-quality video lectures that help you learn at your pace and work on the concepts learned with practice assignments. During this course, you will see several examples that allow you to fully understand the concepts and develop your code for real-world apps. Coding exercises let you practice with solutions. Each coding exercise provides corresponding solutions and quizzes.</p>
        <h2>Key Features</h2><p>High-definition video training with exercises and assignments included, works on Mac or Windows * This course lets you master OOP concepts, classes, lists, functions, abstraction and inheritance * Self-paced learning with exercises, assignments, solutions and quizzes for better understanding</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Python---Object-Oriented-Programming</p>
        <h2>About the Author</h2><h3>Simon Sez IT</h3><p>Simon Sez IT has offered technical courses for individuals, small businesses, and Fortune 500 companies since 2008, with thousands of employees who can benefit from the easy-to-learn and hands-on software training. It offers over 8,000 video tutorials on a range of software programs.

Simon Sez IT ensures stress-free eLearning and enhanced employee productivity-whether you implement new software or a technological upgrade in your work environment. With over 600,000 students from 180 countries, Simon Sez IT is the preferred online learning choice for individuals and businesses worldwide.</p>
        <h2>Course Outline</h2><h4>1. Basics of Object-Oriented Programming</h4><p>This section provides an introductory overview of the concept of object-oriented programming. We learn how to create objects, print objects, and use classes inside classes in Python OOP.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course Introduction</p><p style='margin: 0'>This video is a general introduction to the course, the concepts we learn from the course, and the complete course as an overview.</p></td></tr><tr><td style='padding: 15px;'><p>2. Introduction to OOP</p><p style='margin: 0'>In this video, you will learn about basic concepts of object-oriented programming. We will understand the concept of an object, how to create an object, how to print an object, and the advantages and capabilities of OOP.</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating Bank Account Object: Attributes</p><p style='margin: 0'>After learning how to define an object, we will consider a bank account as an object and learn how to create it and understand its attributes.</p></td></tr><tr><td style='padding: 15px;'><p>4. Creating Bank Account Object - Methods</p><p style='margin: 0'>In the previous video, you learned about creating a bank account object and setting its attributes. In this lesson, you will learn more about the methods and understand how the object behaves with the methods imparted.</p></td></tr><tr><td style='padding: 15px;'><p>5. Printing Objects</p><p style='margin: 0'>This lecture will teach us how to use the "_str_" string object, which is responsible for printing objects. Here, you learn to use this to define our string object and print it.</p></td></tr><tr><td style='padding: 15px;'><p>6. Using A Class Inside Another Class</p><p style='margin: 0'>After learning how to define objects with attributes and methods, you will learn how to use an object within an object.</p></td></tr></tbody></table><br><h4>2. Inheritance and Abstraction</h4><p>This section demonstrates an inheritance in OOP, and you will learn about the method resolutions and abstract methods.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Class Inheritance</p><p style='margin: 0'>In this video, you will learn about inheritance in OOP, and we will look at how an object behaves after inheriting the attributes of another object and why this is useful.</p></td></tr><tr><td style='padding: 15px;'><p>2. Inheritance and Method Resolution Order Part 1</p><p style='margin: 0'>Here, we will understand inheritance and how an object's attributes and methods are inherited into another object.</p></td></tr><tr><td style='padding: 15px;'><p>3. Inheritance and Method Resolution Order Part 2</p><p style='margin: 0'>In this lesson, we will look at inheritance in further detail and understand accessing object attributes and multi-inheritance.</p></td></tr><tr><td style='padding: 15px;'><p>4. Abstract Methods</p><p style='margin: 0'>This video teaches us the implementation of methods for different classes. You will learn about parent and child classes. We will understand what abstract methods are.</p></td></tr></tbody></table><br><h4>3. Class Level Versus Object Level</h4><p>This section delves into classes in detail, and you will learn about the different classes and define their attributes. You will also learn in detail the various methods used inside classes.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Class Attribute Versus Object Attribute</p><p style='margin: 0'>In this video, you will learn about a class attribute, which is a property of a class. You learn about instance attributes. We will differentiate between instance attributes and class attributes and define class attributes.</p></td></tr><tr><td style='padding: 15px;'><p>2. Different Methods Inside the Class</p><p style='margin: 0'>Here, we will look at methods in detail, such as instance, class, and static. We will create a simple class and differentiate between the three methods.</p></td></tr><tr><td style='padding: 15px;'><p>3. Different Methods Inside the Class Part 2: Use Cases</p><p style='margin: 0'>In this video, we will use the other two methods, namely the class and static methods. We will code classes and look at the attributes of these classes with examples.</p></td></tr><tr><td style='padding: 15px;'><p>4. Assignment 1</p><p style='margin: 0'>In this assignment, we will define an object called "player" and understand the player object's behavior.</p></td></tr><tr><td style='padding: 15px;'><p>5. Assignment 2</p><p style='margin: 0'>In this assignment, we will work with lists and use the "from_string" to create a list of items in an object. You will learn how to create a shopping list class and print the items.</p></td></tr></tbody></table><br><h4>4. Encapsulation</h4><p>This chapter will discuss the essential concepts of object-oriented programming and encapsulation that combine attributes and methods.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Public and Private</p><p style='margin: 0'>In this video, we will understand a key concept called encapsulation in OOP. You will learn about public and private attributes, hide information from code, and protect data.</p></td></tr><tr><td style='padding: 15px;'><p>2. Getters and Setters</p><p style='margin: 0'>This lesson takes us through creating a way to interact with objects, getting attributes, and setting new values to private attributes. We will look at the two methods, getter and setter, to obtain private attributes.</p></td></tr><tr><td style='padding: 15px;'><p>3. Methods as Attributes</p><p style='margin: 0'>You will learn to use getter and setter methods; instead, you will learn to access an attribute like a getter or setter method, and we will use an assigner method.</p></td></tr><tr><td style='padding: 15px;'><p>4. Assignment 3</p><p style='margin: 0'>In this assignment, you will learn to create a class for the weather condition. We will use two attributes such as temperature and status.</p></td></tr></tbody></table><br><h4>5. Magic Functions</h4><p>This section demonstrates the magic methods in Python programming. You will learn how to make objects callable, iterable, and comparable.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Making Your Objects Callable</p><p style='margin: 0'>In this video, you will learn about the "_call_" method, which can be used to make an object callable.</p></td></tr><tr><td style='padding: 15px;'><p>2. Making Your Objects Iterable</p><p style='margin: 0'>In this lesson, you will learn about a new method that helps us to create an object like lists in Python. You will also learn about iterable objects, indexing, and the "_getitem_" method.</p></td></tr><tr><td style='padding: 15px;'><p>3. Make Your Objects Comparable.</p><p style='margin: 0'>Here, you will learn to implement comparison methods. You will learn to invoke the magic methods internally in a class on a specific action like creating an object, printing an object, or comparing two objects.</p></td></tr><tr><td style='padding: 15px;'><p>4. Arithmetic Operations on Objects</p><p style='margin: 0'>You will learn about the different types of operators like the +, /, -, and * and how to concatenate strings. You will learn to use magic methods for mathematical operators.</p></td></tr><tr><td style='padding: 15px;'><p>5. Assignment 4</p><p style='margin: 0'>In this assignment, you will learn to define a text encryption method called Caesar cypher.</p></td></tr><tr><td style='padding: 15px;'><p>6. Assignment 5</p><p style='margin: 0'>In this assignment, we will understand how to create an object called a library with indexing using title and category.</p></td></tr><tr><td style='padding: 15px;'><p>7. Assignment 6</p><p style='margin: 0'>In this assignment, you will learn how to create comparable objects. We will create two objects that have similar attributes and compare them.</p></td></tr><tr><td style='padding: 15px;'><p>8. Assignment 7</p><p style='margin: 0'>In the final assignment, we will understand the implementation of arithmetic operations. We will work on addition and subtraction for the bank account assignment.</p></td></tr></tbody></table>

Learn Python OOP language used diversely in applications like data science, game/web development, machine learning, and AI. This course provides all you need to master OOPs like classes, objects, data abstraction, methods, overloading, and inheritance. The course primarily aims to help you tackle complex programming and use OOP paradigms efficiently.
Python is a fantastic OOP language that lets you use functional and OOP paradigms. Python offers several benefits compared to other programming languages like Java, C++ or R. It is a dynamic language, with high-level data types. Python is easier to learn for beginners as its codes are more readable and intuitive. This course is designed to take you through the fundamentals of OOPs and understanding how it works. During this course, you will learn about important concepts such as classes, objects, abstraction, method overloading, and inheritance in sufficient detail. The course will also take you through the concepts of objects and attributes, mathematical operators, callable functions, encapsulation, inheritance and method resolution comprehensively. The course explains the OOP paradigm and lets you create class hierarchies using the OOP design process. By the end of the course, you will be able to design and implement Python programs for complex issues and make good use of the OOP features like classes and inheritance and apply your knowledge completing assignments that simulate real-world scenarios. All resources are available at: https://github.com/PacktPublishing/Python---Object-Oriented-Programming
What You Will Learn
Create class hierarchies using the object-oriented design process
Understand the difference between class and instance variables
Make an object indexable, callable, and comparable
Design and implement Python programs for complex problems
Put to code the language features such as classes and inheritance
Tackle complex code with OOP paradigm, design, and implementation
Audience
This course provides new developers who know Python basics to expand their knowledge and developers and learners who wish to learn OOP in Python. Developers involved with game development, GUI programming, AI, machine learning, and other computed automation can benefit from this course. The concepts and techniques can be applied to other programming languages, so intermediate-level developers wishing to advance their programming skillsets can also learn from this course for career advancement. To get the most from this course, you need to be an intermediate-level programmer in Python.
Approach
This course provides high-quality video lectures that help you learn at your pace and work on the concepts learned with practice assignments. During this course, you will see several examples that allow you to fully understand the concepts and develop your code for real-world apps. Coding exercises let you practice with solutions. Each coding exercise provides corresponding solutions and quizzes.
Key Features
High-definition video training with exercises and assignments included, works on Mac or Windows * This course lets you master OOP concepts, classes, lists, functions, abstraction and inheritance * Self-paced learning with exercises, assignments, solutions and quizzes for better understanding
Github Repo
https://github.com/PacktPublishing/Python---Object-Oriented-Programming
About the Author
Simon Sez IT
Simon Sez IT has offered technical courses for individuals, small businesses, and Fortune 500 companies since 2008, with thousands of employees who can benefit from the easy-to-learn and hands-on software training. It offers over 8,000 video tutorials on a range of software programs. Simon Sez IT ensures stress-free eLearning and enhanced employee productivity-whether you implement new software or a technological upgrade in your work environment. With over 600,000 students from 180 countries, Simon Sez IT is the preferred online learning choice for individuals and businesses worldwide.
Course Outline
1. Basics of Object-Oriented Programming
This section provides an introductory overview of the concept of object-oriented programming. We learn how to create objects, print objects, and use classes inside classes in Python OOP.
1. Course Introduction
This video is a general introduction to the course, the concepts we learn from the course, and the complete course as an overview.
2. Introduction to OOP
In this video, you will learn about basic concepts of object-oriented programming. We will understand the concept of an object, how to create an object, how to print an object, and the advantages and capabilities of OOP.
3. Creating Bank Account Object: Attributes
After learning how to define an object, we will consider a bank account as an object and learn how to create it and understand its attributes.
4. Creating Bank Account Object - Methods
In the previous video, you learned about creating a bank account object and setting its attributes. In this lesson, you will learn more about the methods and understand how the object behaves with the methods imparted.
5. Printing Objects
This lecture will teach us how to use the "_str_" string object, which is responsible for printing objects. Here, you learn to use this to define our string object and print it.
6. Using A Class Inside Another Class
After learning how to define objects with attributes and methods, you will learn how to use an object within an object.
2. Inheritance and Abstraction
This section demonstrates an inheritance in OOP, and you will learn about the method resolutions and abstract methods.
1. Class Inheritance
In this video, you will learn about inheritance in OOP, and we will look at how an object behaves after inheriting the attributes of another object and why this is useful.
2. Inheritance and Method Resolution Order Part 1
Here, we will understand inheritance and how an object's attributes and methods are inherited into another object.
3. Inheritance and Method Resolution Order Part 2
In this lesson, we will look at inheritance in further detail and understand accessing object attributes and multi-inheritance.
4. Abstract Methods
This video teaches us the implementation of methods for different classes. You will learn about parent and child classes. We will understand what abstract methods are.
3. Class Level Versus Object Level
This section delves into classes in detail, and you will learn about the different classes and define their attributes. You will also learn in detail the various methods used inside classes.
1. Class Attribute Versus Object Attribute
In this video, you will learn about a class attribute, which is a property of a class. You learn about instance attributes. We will differentiate between instance attributes and class attributes and define class attributes.
2. Different Methods Inside the Class
Here, we will look at methods in detail, such as instance, class, and static. We will create a simple class and differentiate between the three methods.
3. Different Methods Inside the Class Part 2: Use Cases
In this video, we will use the other two methods, namely the class and static methods. We will code classes and look at the attributes of these classes with examples.
4. Assignment 1
In this assignment, we will define an object called "player" and understand the player object's behavior.
5. Assignment 2
In this assignment, we will work with lists and use the "from_string" to create a list of items in an object. You will learn how to create a shopping list class and print the items.
4. Encapsulation
This chapter will discuss the essential concepts of object-oriented programming and encapsulation that combine attributes and methods.
1. Public and Private
In this video, we will understand a key concept called encapsulation in OOP. You will learn about public and private attributes, hide information from code, and protect data.
2. Getters and Setters
This lesson takes us through creating a way to interact with objects, getting attributes, and setting new values to private attributes. We will look at the two methods, getter and setter, to obtain private attributes.
3. Methods as Attributes
You will learn to use getter and setter methods; instead, you will learn to access an attribute like a getter or setter method, and we will use an assigner method.
4. Assignment 3
In this assignment, you will learn to create a class for the weather condition. We will use two attributes such as temperature and status.
5. Magic Functions
This section demonstrates the magic methods in Python programming. You will learn how to make objects callable, iterable, and comparable.
1. Making Your Objects Callable
In this video, you will learn about the "_call_" method, which can be used to make an object callable.
2. Making Your Objects Iterable
In this lesson, you will learn about a new method that helps us to create an object like lists in Python. You will also learn about iterable objects, indexing, and the "_getitem_" method.
3. Make Your Objects Comparable.
Here, you will learn to implement comparison methods. You will learn to invoke the magic methods internally in a class on a specific action like creating an object, printing an object, or comparing two objects.
4. Arithmetic Operations on Objects
You will learn about the different types of operators like the +, /, -, and * and how to concatenate strings. You will learn to use magic methods for mathematical operators.
5. Assignment 4
In this assignment, you will learn to define a text encryption method called Caesar cypher.
6. Assignment 5
In this assignment, we will understand how to create an object called a library with indexing using title and category.
7. Assignment 6
In this assignment, you will learn how to create comparable objects. We will create two objects that have similar attributes and compare them.
8. Assignment 7
In the final assignment, we will understand the implementation of arithmetic operations. We will work on addition and subtraction for the bank account assignment.

Learn Python OOP language used diversely in applications like data science, game/web development, machine learning, and AI. This course provides all you need to master OOPs like classes, objects, data abstraction, methods, overloading, and inheritance. The course primarily aims to help you tackle complex programming and use OOP paradigms efficiently.

Python - Object-Oriented Programming

<strong>In this course, we will be using Django 3 to build 3 stunning websites with HTML5, CSS3, and Bootstrap 4. This format will allow you to learn Django and not just follow along like a robot. We will use Python in this course, so if you have never used Python before, we will start with a Python refresher to get you up to speed (no other Python experience required).</strong>
        <p>Django is an amazing framework for web developers because it provides the infrastructure required for database-driven websites that have user authentication, content administration, contact forms, file uploads, and more.

In this course, we will be using Django 3 to build 3 stunning websites. This will help you learn Django and implement it in your projects. We will also use Python, so if you have never used it before, we will start with a Python refresher to get you up to speed.

We will then dive into making three complete websites:

1) Password Generator: A simple website to create a random password with several options
2) Personal Portfolio: Create your own portfolio to show to potential employers showing off your resume, previous projects, and a fully functional blog
3) Todo Woo: A website where a user can sign up for an account, and fully manage a Todo list with the ability to create, edit, and delete

We will also walk through Git, which is an awesome tool for developers that allows creating multiple versions of the code. Additionally, we will learn how to publish our projects live.

By the end of this course, you'll be able to use Django to create your own websites and deploy them on a server.

The code bundle for this course is available at https://github.com/PacktPublishing/Django-3-Full-Stack-Websites-with-Python-Web-Development</p>
        <h2>What You Will Learn</h2><p>Understand Django basics such as function base views, URL routing, and models<br>Create a random password generating website<br>Create your own personal portfolio site<br>Create a fully functional Todo list manager website where users can login<br>Work with static and media files, and forms<br>Publish your website online with PythonAnywhere</p>
        <h2>Audience</h2><p>This course is for anyone who wants to work with Python, especially for web applications or web design, and wants to learn the Django framework. Some Python knowledge is helpful but not required. We have a section at the beginning of the course called The Python Refresher to get you up to speed in no time.</p>
        <h2>Approach</h2><p>This is a complete hands-on course where we will be building 3 full-stack websites with Python web development and Django 3.</p>
        <h2>Key Features</h2><p>Build 3 full-stack websites with the Django 3 framework * Learn back- and front-end web development * Deploy your site with HTML5, CSS3, and Bootstrap 4</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Django-3-Full-Stack-Websites-with-Python-Web-Development</p>
        <h2>About the Author</h2><h3>Nick Walter</h3><p>Nick Walter is an experienced mobile and web developer and has worked with technologies such as iOS, Android, Django, and Python.

He learned to code about seven years ago. He had limited access to training resources back then. Whilst he learned to code, he also realized the need to change the way that people learn to code. That's when Nick took up teaching. His experience as an online student has definitely influenced his teaching style-he knows what it is like to be in their shoes.

He started his teaching career in 2014, with the Internet's first Swift course. He now teaches a range of technologies such as iOS, Android, Django, Kotlin, Python, HTML, and Blockchain.</p>
        <h2>Course Outline</h2><h4>1. 0px;padding:0px;clear:both;font-family:'Segoe UI', 'Segoe UI Web', Arial, Verdana, sans-serif;font-size:12px;">
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<p class="Paragraph ParagraphLite BCX0 SCXW182839130" style="margin:0px;padding:0px;background-color:transparent;</h4><p></p><br><h4>5. Site 2 - Personal Portfolio</h4><p></p><br><h4>6. 0px;padding:0px;clear:both;font-family:'Segoe UI', 'Segoe UI Web', Arial, Verdana, sans-serif;font-size:12px;">
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In this course, we will be using Django 3 to build 3 stunning websites with HTML5, CSS3, and Bootstrap 4. This format will allow you to learn Django and not just follow along like a robot. We will use Python in this course, so if you have never used Python before, we will start with a Python refresher to get you up to speed (no other Python experience required).
Django is an amazing framework for web developers because it provides the infrastructure required for database-driven websites that have user authentication, content administration, contact forms, file uploads, and more. In this course, we will be using Django 3 to build 3 stunning websites. This will help you learn Django and implement it in your projects. We will also use Python, so if you have never used it before, we will start with a Python refresher to get you up to speed. We will then dive into making three complete websites: 1) Password Generator: A simple website to create a random password with several options
2) Personal Portfolio: Create your own portfolio to show to potential employers showing off your resume, previous projects, and a fully functional blog
3) Todo Woo: A website where a user can sign up for an account, and fully manage a Todo list with the ability to create, edit, and delete We will also walk through Git, which is an awesome tool for developers that allows creating multiple versions of the code. Additionally, we will learn how to publish our projects live. By the end of this course, you'll be able to use Django to create your own websites and deploy them on a server. The code bundle for this course is available at https://github.com/PacktPublishing/Django-3-Full-Stack-Websites-with-Python-Web-Development
What You Will Learn
Understand Django basics such as function base views, URL routing, and models
Create a random password generating website
Create your own personal portfolio site
Create a fully functional Todo list manager website where users can login
Work with static and media files, and forms
Publish your website online with PythonAnywhere
Audience
This course is for anyone who wants to work with Python, especially for web applications or web design, and wants to learn the Django framework. Some Python knowledge is helpful but not required. We have a section at the beginning of the course called The Python Refresher to get you up to speed in no time.
Approach
This is a complete hands-on course where we will be building 3 full-stack websites with Python web development and Django 3.
Key Features
Build 3 full-stack websites with the Django 3 framework * Learn back- and front-end web development * Deploy your site with HTML5, CSS3, and Bootstrap 4
Github Repo
https://github.com/PacktPublishing/Django-3-Full-Stack-Websites-with-Python-Web-Development
About the Author
Nick Walter
Nick Walter is an experienced mobile and web developer and has worked with technologies such as iOS, Android, Django, and Python. He learned to code about seven years ago. He had limited access to training resources back then. Whilst he learned to code, he also realized the need to change the way that people learn to code. That's when Nick took up teaching. His experience as an online student has definitely influenced his teaching style-he knows what it is like to be in their shoes. He started his teaching career in 2014, with the Internet's first Swift course. He now teaches a range of technologies such as iOS, Android, Django, Kotlin, Python, HTML, and Blockchain.
Course Outline
1. 0px;padding:0px;clear:both;font-family:'Segoe UI', 'Segoe UI Web', Arial, Verdana, sans-serif;font-size:12px;">















In this course, we will be using Django 3 to build 3 stunning websites with HTML5, CSS3, and Bootstrap 4. This format will allow you to learn Django and not just follow along like a robot. We will use Python in this course, so if you have never used Python before, we will start with a Python refresher to get you up to speed (no other Python experience required).

Django 3 - Full Stack Websites with Python Web Development

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