Build & Deploy 8 Powerful Python Projects: Masterclass 2021

Learn To Develop & Deploy Real World Python Web Application Development Projects With Django PyQt5, SQLite Course

Easy to Use and Read

What you’ll learn

  • Understand how using frameworks like Django will save you a ton of time in web development.
  • Improve your web development and coding resume.
  • Learn how to use Python in Web Development.
  • Learn Function Programming With Python.

Course Content

  • Introduction To The Course –> 1 lecture • 1min.
  • Project-1: Build Crop Guide Application with PyQt5,SQLite –> 8 lectures • 55min.
  • Project-2: Build Password Manager Application with PyQt5,SQLite –> 8 lectures • 1hr 2min.
  • Project-3: Build News App Web Application with Django, Python –> 8 lectures • 1hr 1min.
  • Project-4: Build The Guide Web Application with Django, Python –> 6 lectures • 50min.
  • Project-5: Build The Chef Web Application with Django, Python –> 9 lectures • 1hr 9min.
  • Project-6: Build Syllogism-Rules of Inference Solver Web Application –> 7 lectures • 52min.
  • Project-7: Build Vision Web Application with Django, Python –> 8 lectures • 59min.
  • Project-8: Build Budget Planner Application with Python,PyQt5 –> 8 lectures • 56min.

Build & Deploy 8 Powerful Python Projects: Masterclass 2021


  • Knowledge of Python is required..

Easy to Use and Read

There are several factors that simplify the use of Python for web development:

  • Low entry barrier
    Python is similar to the English language we use in everyday life. The simplicity of the syntax allows you to deal with intricate systems and ensure that all the elements have a clear relationship with each other. Thanks to this, more newbie coders can learn the language and join the programming community faster.
  • Good visualizations
    Representing data in a format that can be easily understood is achieved using different plots and charts. They are an efficient way to visually present and comprehend data. Web development companies utilize Python libraries (e.g., Matplotlib) that make it possible to visualize data and create clear and easy-to-understand reports.

Python is incredibly easy to read, so developers typically have no problems understanding code written by their fellow programmers. This makes the communication between developers working on the same project much more efficient. And the job is even easier thanks to convenient IDE for Python development.

Asynchronous Coding

It doesn’t take much effort to write and maintain asynchronous code using Python since there are no deadlocks or research contention or any other confusing issues. Each unit of such code runs separately, allowing you to handle various situations and problems faster.

Less-Limited Programming Approach

Compared to other coding languages, such as Java, Python has a less-limited programming approach. It has multiple paradigms and can support a multitude of programming styles, including procedural, object-oriented, and functional ones. This makes Python a great language for startups since you might need to change your approach at any given moment.

Here’s what it gives you:

  • Fast development.
    Python is not just one of the most rapidly developing coding languages, but also one that allows for quick prototyping and iterations. This makes the work easier and far more productive for developers. This also makes Python a great language for startups, as often faster time to market means greater competitive advantage.
  • OOP becomes easier.
    Object-oriented programming, also known as OOP, is a paradigm that organizes different behaviors and properties into several objects and classes. Each of these classes has a function, so if an error occurs in some part of the code, the other parts are not affected. The operation of OOP is considerably simplified in Python, which makes development less costly and time-consuming.
  • Rich standard library and ecosystem.
    Python’s libraries feature a huge amount of pre-written code. Hence, developers don’t need to waste time creating basic items. These libraries also allow programmers to handle and transform the data required for continuous data processing in Machine Learning (ML).