LEARN PYTHON IN 1 WEEK  AND WHAT FRAMEWORKS TO STUDY

📅 Day-1: Basic Concepts (3hours)

    → Variable

    → Display output (print  command)

    → Take user input (input command)

    → Conditionals

📅 Day-2: Basic Concepts (3hours)

→ List (index, append, approval, remove)
→ for loop
→ while loop
→ function

📅 Day-3: Simple coding problems (5hours)

 → Convert miles into kilometer 
 → Calculate simple Interest
 → Find the largest number in a list
 → Check a number is a prime number or not
 → Sum if all digit numbers
 → Reverse string (check palindrome)
 → Calculate age
 → Build a simple Calculator

📅 Day-4: Data Structures (3hours)

→  Stack and Queue
→ Dictionary
→ Tuples

📅 Day-5: OOP (4hours)

→ Object
→ Class
→ Method and Constructer
→ OOP- Inheritance

📅 Day-6: Algorithm (4hours)

→ Binary Search
→ Bubble Sort
→ Selection Sort

📅 Day-7: Project (6hours)

→ Build a Web Crawler
→ or a news aggregator
→ or a simple game using pygame

Now I will show you some Frameworks to learn after completing 

Basics

1)  FRAMEWORKS FOR WEB

DEVELOPMENT

There are so many frameworks for web

applications in Python some of them are

Django, Flask, Bottle, Tornado, and Pyramid.

✏  Django: A high-level web framework mostly

used in startups and enterprises for web

development. It follows the MVC pattern and

you can use multiple databases such as

PostgreSQL, MySQL, SQLite, and Oracle.

✏  Flask: Flask is one of the easiest

microframeworks to learn in Python. If you wish

to develop a simple and lightweight web

application then Flask is suitable for that.

2) FOR BUILDING DESKTOP

APPLICATIONS

✏ Tkinter: Tkinter is an open-source library and it

allows you to build desktop GUI applications

using Python. Learning Tkinter is simple and

provides a graphical interface. It will take

around 1 week to learn Tkinter.

✏ PyQt: PyQt is one of the most powerful cross-platform GUI library owned by Nokia. combines Python programming and the Qt library. It can be used to design graphical user

interfaces for a desktop application.

✏ Kivy: It can be used to create desktop

applications also support platforms like

Android, iOS, Linux & Raspberry Pi.

5) FOR DATA ANALYSIS

Numpy, Pandas, Seaborn, Bokeh, SciPy,

Matplotlib these libraries are good for data

analysis. These libraries are helpful for those

who want to become data analysts/ data

scientists.

✏ Numpy: It is an array-processing package and

provides high-performance array object. It is

widely used for scientific computing with Python

and provides essential features.

✏ Pandas: Pandas is also a very good open-

source library that is used for data analysis. It

provides high-level data structures (such as

DataFrame) and a vast variety of tools for

analysis.

6) FOR MACHINE LEARNING

✏ TensorFlow: Most popular deep learning

library developed by Google. It is a

the computational framework used to express

algorithms that involve numerous Tensor

operations.

✏ Scikit-Learn: A machine learning library for

Python, designed to work with numerical

libraries such as SciPy & NumPy.

✏ PyTorch: It can handle dynamic computation

graphs on the go. It also provides easy to use

API.

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