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Python in 100 Seconds

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1.Introduction to Python Programming Language

0:00 / 0:40

This chapter introduces Python as a high-level, interpreted programming language known for its readability and versatility. It highlights Python's popularity in web applications, data analysis, and machine learning, and mentions its creator, Guido van Rossum, and the Zen of Python.

  • Python
  • Guido van Rossum
  • Zen of Python
  • Web applications
  • Big Data analysis
  • Machine learning

What's inside this course

  1. 0:00

    1. Introduction to Python Programming Language

    This chapter introduces Python as a high-level, interpreted programming language known for its readability and versatility. It highlights Python's popularity in web applications, data analysis, and machine learning, and mentions its creator, Guido van Rossum, and the Zen of Python.

  2. 0:40

    2. Python Syntax and Basic Data Structures

    This chapter covers the basic syntax of Python, including how to create variables and the concept of strong but dynamic typing. It also explains how Python uses indentation for code scope instead of semicolons or curly braces, and introduces common data structures like tuples, lists, and dictionaries.

  3. 2:07

    3. Advanced Python Features and Ecosystem

    This chapter delves into Python's advanced features, such as functional programming with anonymous functions (lambda) and object-oriented programming with classes and inheritance. It also highlights Python's extensive ecosystem of third-party libraries and the PIP package manager.

Every chapter ends with a checkpoint (quiz, flashcards, retell, diagram, or prediction) and the course closes with a final boss-fight. More courses →

Transcript (72 segments)
0:00python a highlevel interpreted
0:02programming language famous for its
0:04zen-like code it's arguably the most
0:06popular language in the world because
0:08it's easy to learn yet practical for
0:10serious projects in fact you're watching
0:13this YouTube video in a python web
0:15application right now it was created by
0:16Guido van rossom and released in 1991
0:19who named it after Monty Python's Flying
0:21Circus which is why you'll sometimes
0:23find spaming eggs instead of Foo and bar
0:25and code samples it's commonly used to
0:27build serers side applications like web
0:29apps with the framework and is the
0:31language of choice for Big Data analysis
0:33and machine learning many students
0:35choose python to start learning decode
0:37because of its emphasis on readability
0:39as outlined by the Zen of python
0:41beautiful is better than ugly while
0:43explicit is better than implicit python
0:45is very simple but avoids the temptation
0:47to sprinkle in Magic that causes
0:49ambiguity its code is often organized
0:51into notebooks where individual cells
0:53can be executed then documented in the
0:56same place we're currently at version
0:57three of the language and you can get
0:59started by creating a file that ends in
1:01py or iynb to create an interactive
1:04notebook create a variable by setting a
1:06name equal to a value it's strongly
1:08typed which means values won't change in
1:10unexpected ways but Dynamic so type
1:12annotations are not required the syntax
1:14is highly efficient allowing you to
1:16declare multiple variables on a single
1:18line and Define tupal lists and
1:20dictionaries with a literal syntax
1:22semicolons are not required and if you
1:24use them and experience pythonista will
1:26say that your code is not pythonic
1:28instead of semicolons python uses
1:30indentation to terminate or determine
1:32the scope of a line of code Define a
1:34function with the def keyword then
1:36indent the next line usually by four
1:38spaces to define the function body we
1:40might then add a for Loop to it and
1:41indent that by another four spaces this
1:44eliminates the need for curly braces and
1:45semicolons found in many other languages
1:48python is a multiparadigm language we
1:50can apply functional programming
1:51patterns with things like Anonymous
1:53functions using Lambda it also uses
1:55objects as an abstraction for data
1:57allowing you to implement objectoriented
1:59patterns with things like classes and
2:00inheritance it also has a huge ecosystem
2:03of thirdparty libraries such as deep
2:05learning Frameworks like tensorflow and
2:07rappers for many high performance
2:09low-level packages like open computer
2:11vision which are most often installed
2:13with the PIP package manager this has
2:15been the Python programming language in
2:17100 seconds hit the like button if you
2:18want to see more short videos like this
2:20thanks for watching and I will see you
2:22in the next one