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Python Training Overview

Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language. Python has been one of the premier, flexible, and powerful open-source language that is easy to learn, easy to use, and has powerful libraries for data manipulation and analysis

What are the Python Course Pre-requisites

There are no hard pre-requisites. Basic understanding of Computer Programming terminologies is sufficient. Also, basic concepts related to Programming and Database is beeficial but not mandatory.

Objectives of the Course

  • To understand the concepts and constructs of Python
  • To create own Python programs, know the machine learning algorithms in Python and work on a real-time project running on Python

Who should do the course

  • Big Data Professionals
  • IT Developers
  • Those who are showing interest to build their career in Python

Python Training Course Duration

  • 35 Days, Daily 1 Hours

Python Course Content

Core Python

Introduction to Languages

  • What is Language?
  • Types of languages
  • Introduction to Translators
    • Compiler
    • Interpreter
  • What is Scripting Language?
  • Types of Script
  • Programming Languages v/s Scripting Languages
  • Difference between Scripting and Programming languages
  • What is programming paradigm?
  • Procedural programming paradigm
  • Object Oriented Programming paradigm

Introduction to Python

  • What is Python?
  • WHY PYTHON?
  • History
  • Features – Dynamic, Interpreted, Object oriented, Embeddable, Extensible, Large standard libraries, Free and Open source
  • Why Python is General Language?
  • Limitations of Python
  • What is PSF?
  • Python implementations
  • Python applications
  • Python versions
  • PYTHON IN REALTIME INDUSTRY
  • Difference between Python 2.x and 3.x
  • Difference between Python 3.7 and 3.8
  • Software Development Architectures

Python Software’s

  • Python Distributions
  • Download &Python Installation Process in Windows, Unix, Linux and Mac
  • Online Python IDLE
  • Python Real-time IDEs like Spyder, Jupyter Note Book, PyCharm, Rodeo, Visual Studio Code, ATOM, PyDevetc

Python Language Fundamentals

  • Python Implementation Alternatives/Flavors
  • Keywords
  • Identifiers
  • Constants / Literals
  • Data types
  • Python VS JAVA
  • Python Syntax

Different Modes of Python

  • Interactive Mode
  • Scripting Mode
  • Programming Elements
  • Structure of Python program
  • First Python Application
  • Comments in Python
  • Python file extensions
  • Setting Path in Windows
  • Edit and Run python program without IDE
  • Edit and Run python program using IDEs
  • INSIDE PYTHON
  • Programmers View of Interpreter
  • Inside INTERPRETER
  • What is Byte Code in PYTHON?
  • Python Debugger

Python Variables

  • bytes Data Type
  • byte array
  • String Formatting in Python
  • Math, Random, Secrets Modules
  • Introduction
  • Initialization of variables
  • Local variables
  • Global variables
  • ‘global’ keyword
  • Input and Output operations
  • Data conversion functions – int(), float(), complex(), str(), chr(), ord()

Operators

  • Arithmetic Operators
  • Comparison Operators
  • Python Assignment Operators
  • Logical Operators
  • Bitwise Operators
  • Shift operators
  • Membership Operators
  • Identity Operators
  • Ternary Operator
  • Operator precedence
  • Difference between “is” vs “==”

Input & Output Operators

  • Print
  • Input
  • Command-line arguments

Control Statements

  • Conditional control statements
  • If
  • If-else
  • If-elif-else
  • Nested-if
  • Loop control statements
  • for
  • while
  • Nested loops
  • Branching statements
  • Break
  • Continue
  • Pass
  • Return
  • Case studies

Data Structures or Collections

  • Introduction
  • Importance of Data structures
  • Applications of Data structures
  • Types of Collections
  • Sequence
  • Strings, List, Tuple, range
  • Non sequence
  • Set, Frozen set, Dictionary
  • Strings
  • What is string
  • Representation of Strings
  • Processing elements using indexing
  • Processing elements using Iterators
  • Manipulation of String using Indexing and Slicing
  • String operators
  • Methods of String object
  • String Formatting
  • String functions
  • String Immutability
  • Case studies

List Collection

  • What is List
  • Need of List collection
  • Different ways of creating List
  • List comprehension
  • List indices
  • Processing elements of List through Indexing and Slicing
  • List object methods
  • List is Mutable
  • Mutable and Immutable elements of List
  • Nested Lists
  • List_of_lists
  • Hardcopy, shallowCopy and DeepCopy
  • zip() in Python
  • How to unzip?
  • Python Arrays:
  • Case studies

Tuple Collection

  • What is tuple?
  • Different ways of creating Tuple
  • Method of Tuple object
  • Tuple is Immutable
  • Mutable and Immutable elements of Tuple
  • Process tuple through Indexing and Slicing
  • List v/s Tuple
  • Case studies

Set Collection

  • What is set?
  • Different ways of creating set
  • Difference between list and set
  • Iteration Over Sets
  • Accessing elements of set
  • Python Set Methods
  • Python Set Operations
  • Union of sets
  • functions and methods of set
  • Python Frozen set
  • Difference between set and frozenset ?
  • Case study

Dictionary Collection

  • What is dictionary?
  • Difference between list, set and dictionary
  • How to create a dictionary?
  • PYTHON HASHING?
  • Accessing values of dictionary
  • Python Dictionary Methods
  • Copying dictionary
  • Updating Dictionary
  • Reading keys from Dictionary
  • Reading values from Dictionary
  • Reading items from Dictionary
  • Delete Keys from the dictionary
  • Sorting the Dictionary
  • Python Dictionary Functions and methods
  • Dictionary comprehension

Functions

  • What is Function?
  • Advantages of functions
  • Syntax and Writing function
  • Calling or Invoking function
  • Classification of Functions
    • No arguments and No return values
    • With arguments and No return values
    • With arguments and With return values
    • No arguments and With return values
    • Recursion
  • Python argument type functions :
    • Default argument functions
    • Required(Positional) arguments function
    • Keyword arguments function
    • Variable arguments functions
  • ‘pass’ keyword in functions
  • Lambda functions/Anonymous functions
    • map()
    • filter()
    • reduce()
  • Nested functions
  • Non local variables, global variables
  • Closures
  • Decorators
  • Generators
  • Iterators
  • Monkey patching