Python for Beginners (full-course) - 43 sections - 350 videos | P1

Sections (P1):
00:00:15 01. Introduction
00:05:15 02. Software Setup and First Python Script
00:24:35 03. Datatypes
00:40:41 04. Sequence Types
01:30:38 05. Special Types
01:40:57 06. Operators and Operands
01:50:51 07. Input and Output functions
02:03:01 08. More Programs
02:10:58 09. Flow Control Statements
02:48:09 10. More Programs 2
03:08:04 11. Command line arguments
03:19:00 12. Functions
04:01:28 13. Lambdas
04:37:04 14. Modules
04:50:50 15. List Comprehensions
05:02:14 16. Object Oriented Programming
05:41:29 17. Encapsulation
05:49:53 18. Inheritance
06:02:09 19. Polymorphism
06:16:07 20. Abstraction
06:24:41 21. Library Management Usecase
06:38:17 22. Exception Handling Assertions and Logging
07:05:30 23. Files
07:32:35 24. Regular Expressions
08:03:45 25. Date and Time
08:25:45 26. Threads
09:19:36 27. Networking
09:48:39 28. Database Operations
10:19:10 29. Using PostgreSQL

Course Goals:
Python Fundamentals - Python basics: Setting up your environment, learning core data types like lists, tuples, and dictionaries, and learning control flow statements like if-else and loops. You will then gain strong foundational skills in organizing code using functions, modules, and decorators.
Learning Object-Oriented Programming. You will learn the entire OOP paradigm, learning how to build complex, maintainable applications using classes, inheritance, polymorphism, and abstraction. These skills are essential for large-scale, enterprise-level programming.
Advanced Application Skills: Then you will move into practical, specialized areas. You will learn how to handle errors gracefully with exception handling and logging. You will gain knowledge of I/O operations, threads, networking, and vital data tools like SQL, MongoDB, and JSON parsing.
Data Science and Modern Frameworks. The final modules will equip you with the following skills: data manipulation using NumPy and Pandas, data visualization with Matplotlib, fast application building with Streamlit, and robust data validation with Pydantic. These tools help you in the data domain.

Course Requirements:
You should use macOS; if you use another OS, you will have a little difficulty (but I think you can solve it)