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Understanding Data Engineering
This is Part 1 for Data Engineering here we will learn Python Basics to Advance. Next course we will do Linux.
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What is the topic you will learn in this course?
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation.
Python is dynamically-typed and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional programming. It is often described as a "batteries included" language due to its comprehensive standard library.
Guido van Rossum began working on Python in the late 1980s as a successor to the ABC programming language and first released it in 1991 as Python 0.9.0. Python 2.0 was released in 2000 and introduced new features such as list comprehensions, cycle-detecting garbage collection, reference counting, and Unicode support. Python 3.0, released in 2008, was a major revision that is not completely backwards-compatible with earlier versions. Python 2 was discontinued in version 2.7.18 in 2020.
As part of this course, the following topics are covered in detail.
1. Language Fundamentals
3. Input and Output Statements
4. Flow Control
5. Pattern Applications For Logic Building
7. String Programming Questions For Logic Building
8. List Data Structure
9. Tuple Data Structure
10. Set Data Structure
11. Dictionary Data Structure
15. Object-Oriented Programming (OOPs)
16. Exception Handling
17. Logging Module
19. File Handling
20. Object Serialization By using PICKLE, JSON, and YAML