Python

Python is an interpreted, high-level, general-purpose programming language. 

About the Course
Python

Python is used for developing both desktop and web applications. Also, you can use Python for developing complex scientific and numeric applications. Python is designed with features to facilitate data analysis and visualization.

Duration: 30 Days

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Requirements

To learn Python, you just need to know basics of programming languages like C and        C++. You should know concepts of Variables, Operators, Conditional Statements, Loops etc.

 What you’ll learn?

  1. Origin of Python
  2. Introduction to Python and what is a Python
  3. What can we do by using Python
  4. Features and versions of Python
  5. Different languages used to develop Python
  6. Interactive mode and Script mode
  7. Interpreter vs Compiler
  8. Scripting vs Programming Languages
  9. Reasons to learn or work Python
  10. Python Indentation
  11. Comments and Quotations
  12. Python Identifiers and Keywords
  13. Variables
  14. Assigning values to variables in different ways
  15. Print(), type() and id()
  16. Reading data from user
  17. Working with input function
  18. Python data types
  19. Type conversions and eval()

Assignment - 1

  1. Introduction to Data Structures
  2. Stringdata Structure
  • Different ways to create a string
  • String indexing and string slicing
  • string concatenation and string multiplication
  • string unpacking
  • splitting the data in different parts as per user
  • capitalize() and tittle() and split()
  • del, count(), find(), swapcase()
  • reverse(),replace() and sort()
  • string immutable
  1. List Data Structure:
  • different ways to create a list
  • creating and working with homogeneous lists
  • creating an working with heterogeneous lists
  • list indexing and list slicing
  • list concatenation and list multiplication
  • generating list by using range function
  • list unpacking and list mutable
  • creating nested lists and indexing nested lists
  • python range() and xrange() functions
  • python insert, append andextend
  • remove, pop and clear
  • python list ascending and descending
  • converting given string data structure into list
  • converting given list data structure into string
  • creating list from user values
  1. Tuple Data Structure    
  • creating a tuple in different ways
  • creating and working with homogeneous tuple
  • creating and working with heterogeneous tuple
  • tuple indexing and tuple slicing
  • tuple concatenation and tuple multiplication
  • tuple unpacking and tuple immutable
  • all, any, len and sort
  • del keyword
  • python tuple ascending and descending
  • creating and working with nested tuples
  • Conversions:
  • advantages of tuple over list data structure
  1. Set Data Structure
  • Creating and working with set data structure in different ways
  • Normal sets and frozen sets
  • Set mutable and unpacking set data structure
  • Creating and working with sets with homogeneous elements
  • Creating and working with sets with heterogeneous elements
  • Creating empty sets and modifying the empty sets
  • Why sets not support indexing and slicing
  • Add, remove and discard the elements to set data structure
  • Issubset, issuperset and isdisjoint
  • Union, intersection and defference
  • Intersection_update and defference_update
  • Symmetric_difference and symmetric_difference_update
  • Conversions:
  1. Set Data Structure    
  • Creating and working with set data structure in different ways
  • Normal sets and frozen sets
  • Set mutable and unpacking set data structure
  • Creating and working with sets with homogeneous elements
  • Creating and working with sets with heterogeneous elements
  • Creating empty sets and modifying the empty sets
  • Why sets not support indexing and slicing
  • Add, remove and discard the elements to set data structure
  • Issubset, issuperset and isdisjoint
  • Union, intersection and defference
  • Intersection_update and defference_update
  • Symmetric_difference and symmetric_difference_update
  • Conversions
  1. Dictionary Data Structure
  • Creating and working with dictionary data structure in different ways
  • Creating empty dictionary and working with empty dictionary
  • Working with key and value pairs
  • Dictionary mutable and unpacking dictionary
  • Adding and deleting key and value pairs to the existing data structure
  • Difference between pop and popitem operations
  • Extracting only keys from the existing data structure
  • Extracting only values from the existing data structure
  • Clear and pop methods
  • Del keyword and pop method
  • Creating a dictionary from existing another data structure like tuple
  • FAQs on all Data Structures

Assignment – 2

     24. Operators

  • Arithmetic operators
  • Logical operators
  • Assignment operators
  • Comparison operators
  • Bitwise operators
  • Identity operators
  • Membership operators

    25. Python Functions and Arguments

  • Defining functions and working with functions
  • Using def keyword for functions
  • Called functions and function definition and calling functions
  • Formal arguments and actual arguments
  • Working with named arguments and keyword arguments
  • Default arguments and positional arguments
  • Working with default arguments and normal arguments
  • *args and **kwargs arguments
  • Argument unpacking
  • Variable length arguments
  • Using data structures to function definitions
  • Nested functions
  • Dir() and Format() functions
  • Enumerate function
  • FAQs on functions and Arguments

    26. Lambda Functions

  • Creating functions by using lambda keyword
  • Difference between def and lambda functions
  • Working with filter functions
  • Working with map functions
  • Working with reduce functions

    27. Control Statements

  • Simple If statement
  • If else statement
  • Elif statement
  • Nested if statement
  • Membership test for string
  • Membership test for tuple
  • Membership test for list
  • Membership test for set
  • Membership test for dictionary
  • FAQs on control statements

    28. Loopings

  • For loop
  • While loop
  • Pass, continue and break statements
  • Iterating over list, tuple, set and dictionary

    29. Advanced Concepts on Data Structures   

  • List comprehension
  • Dictionary comprehension
  • Nested data structures  

Assignment – 3

Advanced Python

    30. File Handling

  • Creating a file in a directory
  • Open the file in the python
  • Different ways to open the file in Python
  • Writing to the file
  • Appending the data to the existing file
  • Modes of operations
  • Seek and tell methods
  • Readline and readlines
  • Working with words and characters in the file
  • Real-time scenarios on files
  • Interview based questions on the file

    31. OOPS Concepts

  • Class and object
  • Class variables and instance variables
  • Constructor
  • Data hiding
  • Method overloading and overriding
  • Abstraction
  • Inheritance
  • Polymorphism
  • Encapsulation

    32. Modules

  • What is module and purpose of modules
  • Different types of modules
  • Different ways to import modules
  • Standard modules and user modules
  • From ... import *
  • Creating own modules
  • Using modules in other modules
  • Working with some standard modules
  • MATH, DATETIME, CALENDAR, SYS, OS Modules

   33. Exception Handling in Python

  • What is an exception
  • Handling exceptions
  • Try and except block
  • Handling multiple exceptions using multiple excepts
  • Handling multiple exceptions using single except
  • Working with default except
  • Handling exceptions with else and finally blocks
  • Using assert for handling exceptions

   34. Logging in python

  • What is logging and purpose of logging
  • Creating a log file
  • Storing runtime events in log file
  • Different modes to store the data in log file
  • DEBUG, INFO, WARNING, ERROR, CRITICAL

   35. Iterators, generators and decorators

  • Working with yield keyword
  • Difference between yield and return
  • Decorating a function with another function

   37. Command Line Arguments

  • Reading command line arguments
  • Using command line arguments

   38. Working with Database Connection

  • Connecting to database from Python application
  • Creating connection to the database from Python application
  • Creating database and tables from Python applications to the database
  • Fetching data and updating data in the entities.
  • Using cursor to execute SQL command in Python application
  • Using Fetchall and Fetchone methods