In this course, you will learn how to program with the popular development language – Python. This course is designed for beginners.

Description

  • No programming experience is required.
  • Basic computer skills
  • Supplemental Resources
  • Lifetime access
  • Access on Mobile Phones
  • Certificate of Completion

Build a solid understanding of Python Programming

Introduction:

  • Five W’s of Python (What,When,Who,Where,Why)
  • Zen of Python
  • Application of python
  • Features of Python
  • Pros and Cons
  • Interoperability and Developer Community
  • Code Environment & Folder Structure
Basic Syntax:

  • Interpreter Vs Scripting
  • Indentation, Whitespace, Lines
  • Basic Output
  • Basic Input
  • Naming Paradigm
  • Keywords
  • Comments, Quotations
  • Single Line Vs Groups
  • Command Line Arguments
  • Operands & Memory
  • Types
  • Creating Data variable and Memory
  • Memory associated with Types
  • Deleting Data Variable and Memory
  • How Python Stores a Variable in Memory
  • Manipulation of Data variable
  • Comparison of Types
  • When,Where,What and How to use data variable
  • Important Type conversion functions
Pros and Cons of each Type Operators:

  • Types of Operators [ Arithmetic ]
  • Types of Operators [ Logical ]
  • Type of Operators [ Comparison ]
  • Types of Operators [ Bitwise ]
  • Python Special Operators [Membership and Identity]
  • Order of Precedence on Operators
Minimisation of Logic Using Operator Decision Statements:

  • “IF” statement basics
  • Computational resource Spent on a “IF”
  • Multi-form of “IF”
  • Fusing “IF” with other elements
Looping:

  • What and Where to use Loops
  • Types of Loops
  • Computational resource needed for each type of Loops
  • Different Types of Loops Basics and Syntax
  • Real world scenario for each loop types
  • Multi- Form of Loops
  • Fusing “Loops” with other elements
  • Loop manipulation and Controls
Control Statements Usage Strings:

  • Python Strings Vs Other Strings
  • Creating, Deleting String and Memory
  • Memory Associated with strings
  • Strings Vs Array
  • Accessing Stings
  • Manipulation of Strings
  • String with Operators
  • Escape Characters
  • Formatting Operator
  • Multi-Line String
  • Encoding of String in Python
  • Important Function for String Manipulation
  • Guardrails for String Usage
Data Structure:

  • Types of Data Structures
  • List vs Tuples vs Dictionaries
  • Where and When to use an data structure
  • Memory associated with the Data Structure
  • CRUD – Create, Read, Update, Delete of Data Structure
  • Data Structures with Operators
  • Built-in important function Data Structure manipulation
Guard rails for Data Structure Functions or Methods:

  • Why Function
  • Syntax for Function
  • Return for Function
  • Accessing a Function
  • Functions with arguments
  • Lambda Functions [Abstract]
Scope of Variables Modules and Package:

  • What are Modules
  • When to use module and function
  • Creating and Accessing Modules
  • Import Statement
  • Built-in Modules
Packages Input and Output:

  • Advanced output and Input
  • What are Files
  • Opening and Closing files
  • Methods of Accessing Files
  • File Object manipulation
  • Read and Write functions
  • What is File Pointer
  • File pointer position [ Seek,Tell]
Renaming and Deleting Files Exception Handling:

  • What is Error
  • How to Debug in Python
  • Different types of Errors
  • What is Exception
  • Handling Exception [ Except, Try,Finally]
  • User-Defined Exceptions
  • Advantages of Exception
  • Real world scenario of Exception
  • Why Exception Handling is the most important part of development
  • Guardrails for Exception Handling
Programming Paradigm in Python:

  • Types of Paradigm in Python [Object-oriented, imperative, functional, procedural, reflective]
  • Think outside the Box of OOP’s using Python
  • Object-oriented vs Imperative vs Functional vs Procedural vs Reflective
  • Object-oriented briefing and usage
  • Imperative briefing and usage
  • Procedural briefing and usage
  • Functional briefing and usage
  • Reflective briefing and usage
  • When to use which Paradigm
  • Real World Examples of Paradigm
  • Guardrails of Paradigm Networking in Python
  • Networking basics
  • Association with Python
  • Socket Connection
  • Protocol Usage with Built-in Function
  • Why mostly your Python Script Cannot Communicate over Internet
  • Framework on Networking for Python [ Twisted ]
  • Real world Application of Python Networking
  • Guardrails of Python Networking
Multi Threading:

  • What is Multithreading
  • How Python Multi Thread
  • Python Multi Thread vs Real Multi Thread
  • Threads
  • Built-In Modules for Threads
  • Synchronising
Multithreaded Priority Queue Ancillary application:

  • Python data and Time
  • Python Regular Expression
  • Python Image Processing
  • Python XML Parser [ Beautiful Soup ]
  • Python GUI Programming
  • Django
  • Numpy
  • Scipy
MatplotlibVersions of Python:

  • Python 2.7 vs 3.0
  • Change Log
  • What to Use
Community and Developers:

  • How to install a Package
  • Python Package Index
  • Pip
  • Virtualenv
  • Python Package Index
  • FreezePython Application, Breaking Stereotypes
  • Internet Application [ Django ]
  • File Server
  • Image Manipulation
  • Speech to Text