Learn Python By Doing 25 Real World Projects Masterclass

Go From Beginner To Expert In Python Web Development: Develop Real Django Applications with SQLite, Tkinter, Opencv
The most appealing characteristic of Python is that it is an interpreted language. Interpreted languages are the programming languages that do not need to be compiled to run. An interpreter can run python code on any kind of computer, by itself. This means the programmer can quickly see the results, if or when they need to modify the code. On the flip side, this also means that Python is slower than a compiled language like C. And that is because it is not running on a machine code directly.
Because Python is an interpreted language, testing small snippets of code and moving them between different platforms is quite simple. Since Python is compatible with most of the operating systems, it is used universally, in a variety of applications.
Python is considered a beginners' programming language. As it is a high-level language, a programmer can focus on what to do instead of how to do it. This is one of the major reasons why writing programs in Python takes less time than in other programming languages.
Because Python is similar to English, many find it easier to learn than other programming languages. Developers can read and remember the Python syntaxes much easier than other programming languages.
Since Python supports scripting as well, it can be used to build large, commercial applications. The main factor behind Python's popularity in the IT world is its reliability. Being a high-level programming language, Python lets the user focus on the core functioning of the application. Meanwhile, the common programming tasks are handled by the language itself.
Now you can probably see why Python is one of the most favored programming languages by developers, data scientists, software engineers, and hackers! And the key factors behind its diverse userbase are flexibility, versatility, and object-oriented features. This is also why Python is used in complex fields like Machine Learning (ML) and Data Science (DS).
In This Course, We Are Going To Work On 25 Real World Projects Listed Below:
Project-1: Image Editor Application With OpenCV And Tkinter
Project-2: Brand Identification Game With Tkinter And Sqlite3
Project-3: Transaction Application With Tkinter And Sqlite3
Project-4: Learning Management System With Django
Project-5: Create A News Portal With Django
Project-6: Create A Student Portal With Django
Project-7: Productivity Tracker With Django And Plotly
Project-8: Create A Study Group With Django
Project-9: Building Crop Guide Application with PyQt5, SQLite
Project-10: Building Password Manager Application With PyQt5, SQLite
Project-11: Create A News Application With Python
Project-12: Create A Guide Application With Python
Project-13: Building The Chef Web Application with Django, Python
Project-14: Syllogism-Rules of Inference Solver Web Application
Project-15: Building Vision Web Application with Django, Python
Project-16: Building Budget Planner Application With Python
Project-17: Tic Tac Toe Game
Project-18: Random Password Generator Website using Django
Project-19: Building Personal Portfolio Website Using Django
Project-20: Todo List Website For Multiple Users
Project-21: Crypto Coin Planner Gui Application
Project-22: Your Own Twitter Bot -python, request, API, deployment, tweepy
Project-23: Create A Python Dictionary Using python, Tkinter, JSON
Project-24: Egg-Catcher Game using python
Project-25: Personal Routine Tracker Application using python