1. Python Programming Language
Python is an interpreted, object-oriented, high-level
programming language with dynamic semantics.
Its high-level built in data structures, combined with
dynamic typing and dynamic binding, make it very
attractive for Rapid Application Development.
Python's simple, easy to learn syntax emphasizes
readability and therefore reduces the cost of program
maintenance.
Python supports modules and packages, which
encourages program modularity and code reuse.
The Python interpreter and the extensive standard library
are available in source or binary form without charge for
all major platforms, and can be freely distributed.

2. History Of Python
 ABC is a general-purpose programming language
and programming environment, which was
developed in the Netherlands, Amsterdam.
 Python was conceptualized in the late 1980s.
Guido van Rossum worked that time in a project at
the CWI, called Amoeba, a distributed operating
system.
 “I decided to try to design a simple scripting
language that possessed some of ABC's better
properties, but without its problems. So I started
typing.”
 “I created a basic syntax, used indentation for
statement grouping instead of curly braces or
begin-end blocks, and developed a small number
of powerful data types: a hash table (or dictionary,
as we call it), a list, strings, and numbers."
 “Around Christmas. My office ... would be closed,
but I had a home computer, and not much else on
my hands. I decided to write an interpreter for the
new scripting language I had been thinking about
lately: a descendant of ABC that would appeal to
Unix/C hackers.”
 Guido Van Rossum published the first version of
Python code (version 0.9.0) at alt.sources in
February 1991. This release included already
exception handling, functions, and the core data
types of list, dict, str and others.
 Python version 1.0 was released in January 1994.
The major new features included in this release
were the functional programming tools lambda,
map, filter.
 Six and a half years later in October 2000, Python
2.0 was introduced. This release included list
comprehensions, a full garbage collector and it
was supporting unicode.
 Python flourished for another 8 years in the
versions 2.x before the next major release as
Python 3.0 (also known as "Python 3000" and
"Py3K") was released. Python 3 is not backwards
compatible with Python 2.x.

3. Benefits Of Python Learning
(1) Python Supports Multiple Programming Paradigms.
(2) Python Has Large Set Of Library and Tools—
 Built-in functions, constants, types, and exceptions.
 File formats, file and directory access, multimedia services.
 GUI development tools such as Tkinter
(3) Python Has a Vast Community Support
(4) Python is Designed For Better Code Readability
(5) Python Contains Fewer Lines Of Codes
 Python also offers much more error checking than C,
and, being a very-high-level language.
 it has high-level data types built in, such as flexible
arrays and dictionaries.
 Python allows you to split your program into modules
that can be reused in other Python programs. It comes
with a large collection of standard modules that you
can use as the basis of your programs. Like file I/O,
system calls, sockets.
 Python is an interpreted language, which can save you
considerable time during program development
because no compilation and linking is necessary.
 It is also a handy desk calculator.
 Python enables programs to be written compactly and
readably. Programs written in Python are typically
much shorter than equivalent C, C++, or Java
programs

4. Future Technologies Counting On Python
 Python programming language is extensively used for
web development, application development, system
administration, developing games etc.
 Artificial Intelligence (AI) -- Machine Learning, General
AI, Neural Networks, Natural Language & Text
Processing
 Big Data --- Python has been successfully contributing in
analyzing a large number of data sets across computer
clusters. Pandas, NumPy, SciPy, IPython
 Networking --- Python programming language is used to
read, write and configure routers and switches and perform
other networking automation tasks in a cost-effective and
secure manner. Ansible, Netmiko, Pyeapi
 Australia’s RMA Department D-Link has successfully
implemented python for creating DSL Firmware Recovery
System.
 Gusto.com, an online travel site, in reducing development
costs and time.
 ForecastWatch.com also uses python in rating the
accuracy of weather forecast reports.
 Test&Go uses python scripts for Data Validation.
 Industrial Light & Magic(ILM) also uses python for batch
processing

5. Companies using Python
 Youtube
 Quora
 Instagram
 Pinterest
 Spotify
 Flipkart
 Slack
 Uber
 Cloudera
 Zenefits
Website Developed in Python
 NASA -- Workflow Automation System(WAS), open source
projects such as APOD(Astronomy Picture of the Day) API,
PyTransit, PyMDP Toolbox, EVEREST etc.
 Google -- reports generation, log analysis, A/Q and testing,
writing core search algorithms, and Youtube uses for
viewing a video, accessing canonical data
 Walt Disney Feature Animation -- scripting language for
most of its animation tasks and related production.
 AlphaGene, Inc. -- It uses python for its bioinformatics and
tracking system.
 Nokia -- It uses PyS60(Python for S60) and
PyMaemo(Python for Maemo) for its S60(Symbian) and
Maemo(Linux) software platforms.
 Yahoo! Maps -- It is an online mapping portal developed at
Yahoo!. Many of its mapping lookup services and
addresses were written in python.
Companies Using Python

6. Brief content of this Python course
1. Python installation
2. Printing in Python
3. Strings in Python
4. Variables and types
5. Python as a strongly typed language
6. Numeric Data types in Python
7. Numeric operators
8. Expressions
9. Str string Data type
10. Slicing
11. String Operators
12. String formatting
13. Introduction to Blocks and Statements
14. if else and elif statements
15. Conditional Operators
16. Boolean Expression
17. Loops
18. Random Module and import
19. Binary Search
20. else in loop
21. conditional debugging
22. List, Range and Tuples in Python
23. Lists in Python
24. Understanding range
25. Complex Data Types
26. I/O in Python
27. Reading and writing text files
28. handling binary files in Python
29. Standard Python library
30. WebBrowser module
31. Time and Date time in Python
32. Timezones
33. Introducation to Tkinter
34. GUI
35. Functions in Python
36. importing technique
37. Object oriented programming and classes
38. Polymorphism
39. Database
40. SQL in Python
41. Exceptions
42. Custom exceptions
43. Roll back transactions
44. Database handling using Python
45. Generators and Yield
46. Next and Ranges
47. Searching Filesystem
48. Reading MP3 tags
49. Lamda Expression
50. Project