Python Tutorial

Python Tutorial

Well organized and easy to understand basic tutorials with lots of examples of how to use Python .

The Python Tutorial¶. Python is an easy to learn, powerful programming language.

Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. It was created by Guido van Rossum during 1985- 1990. Like Perl, Python source code is also available under the GNU General Public License (GPL). This tutorial gives enough understanding on Python programming language.

Why to Learn Python?

Python is a high-level, interpreted, interactive and object-oriented scripting language. Python is designed to be highly readable. It uses English keywords frequently where as other languages use punctuation, and it has fewer syntactical constructions than other languages.

Python is a MUST for students and working professionals to become a great Software Engineer specially when they are working in Web Development Domain. I will list down some of the key advantages of learning Python:

Anna University

Common to all Department

First Semester

GE8151 PROBLEM SOLVING AND PYTHON PROGRAMMING

(Regulation 2017) 

Syllabus

Syllabus Regulation : 2017

Semester : 1

Department : Common to All Department

Subject Code : GE8151

Subject Name : PROBLEM SOLVING AND PYTHON PROGRAMMING

Type : Syllabus

Edition Details : 2017 Edition (Original Version)

Attachment Type : pdf

Details : GE8151 PROBLEM SOLVING AND PYTHON PROGRAMMING (REG 2017)

GE8151                      PROBLEM SOLVING AND PYTHON PROGRAMMING            L T P C 

Introduction to Python-  pdf video 

Python Interpreter And Interactive Mode;

Basic Syntax and Variables pdf     video 

List; Variables, Tuple Assignment, String, Dictionary pdf     video 

for loop statement And Functions, pdf     video 

If condition statement with example pdf     video 

Function Definition And Use, Flow Of Execution,

Parameters And  Arguments;  Illustrative Programs:

Exchange The Values Of Two Variables,

Circulate The Values Of N Variables,

Distance Between Two Points.

CONTROL FLOW, FUNCTIONS                                                                              

String Module pdf     video ;

Lists As Arrays. pdf     video ;

Illustrative Programs: Square Root, Gcd, Exponentiation,

Sum An Array Of Numbers, 

Linear Search, pdf     video 

Binary Search.pdf     video 

Math Function pdf     video ;

Date Module pdf     video 

Conditionals: Boolean Values And Operators, Conditional (If), Alternative (If-Else), Chained Conditional (If-Elif-Else);

Iteration: State, While, For, Break, Continue, Pass;

Fruitful Functions: Return Values, Parameters, Local And Global Scope,

Function Composition, Recursion;

Strings:  String Slices, Immutability, String Functions And Methods, 

 LISTS, TUPLES, DICTIONARIES                                                                            

Set  pdf     video 

 List Comprehension; Illustrative Programs:

 Selection Sort, pdf     video 

Insertion Sort, 

Mergesort, pdf     video 

Histogram.

Lists: List Operations, List Slices, List Methods, List Loop, Mutability, Aliasing, Cloning Lists, List Parameters;

Tuples: Tuple Assignment, Tuple As Return Value;

Dictionaries: Operations And Methods; Advanced List Processing –

FILES, MODULES, PACKAGES                                                                            

Files And Exception: Text Files, Reading And Writing Files,

Format Operator; Command Line Arguments,

Errors And Exceptions, Handling Exceptions, Modules,

Packages; Illustrative Programs: Word Count, Copy File.

NumPy - Numerical Python 

NumPy is a python library used for working with arrays.

It also has functions for working in domain of linear algebra, fourier transform, and matrices.

NumPy was created in 2005 by Travis Oliphant. It is an open source project and you can use it freely.

NumPy stands for Numerical Python.

Numpy Introduction     pdf     video 

 Numpy Creating Array     pdf     video 

Numpy Array Indexing     pdf     video 

Numpy Array Slicing         pdf     video 

Numpy Datatypes             pdf     video 

Numpy Copy and View              pdf     video 

Numpy Shape and Reshape         pdf     video 

Numpy Joining                             pdf     video 

Numpy Sorting and Filtering         pdf     video 

Numpy Random and Search          pdf     video 

Python Machine Learning             

Introduction                                    pdf     video 

Machine Learning  Standard Deviation pdf     video 

Machine Learning Percentile         pdf     video 

Machine Learning Scatter Plot         pdf     video 

Machine Learning Linear  regression pdf   video

Machine learning Polynomial Regression    pdf     video

Machine learning Test and Training Data   pdf      video  

Machine learning How to insert or import CSV file and Stat model pdf   video