Python

About Python Programming Language

Python is an interpreted, high-level, general-purpose programming language. Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace. It provides constructs that enable clear programming on both small and large scales.

Why this course is required

The software development companies prefer Python language because of its versatile features and fewer programming codes. Nearly 14% of the programmers use it on the operating systems like UNIX, Linux, Windows and Mac OS. The programmers of big companies use Python as it has created a mark for itself in the software development with characteristic features like-Interactive,Interpreted,Modular,Dynamic,Object-oriented,Portable,High level,Extensible in C++ & C.

Pre-requisites for Python Programming

Next Course Recommended

Course Contents

  1. Basics of Python Programming
    • Features of Python
    • History of Python
    • The Future of Python
    • Writing and Executing First Python Program
    • Literal Constants
    • Variables and Identifiers
    • Data Types
    • Input Operation
    • Reserved Words
    • Operators and Expressions
    • Expressions in Python
    • Type Conversion
  2. Decision Control Statements
    • Introduction to Decision Control Statements
    • if Statement
    • if-else Statement
    • Nested if Statements
    • if-elif-else
    • Basic Loop Structures/ Iterative Statements
    • while loop
    • for Loop
    • Nested Loops
    • The break Statement
    • The continue Statement
    • The pass Statement
    • The else Statement used with Loops
  3. Python Strings
    • Concatenating, Appending, and Multiplying Strings
    • Strings are Immutable
    • String Formatting Operator
    • Built-in String Methods and Functions
    • Slice Operation
    • ord() and chr() Functions
    • The String Module
  4. Python List
    • Access List Element
    • Cloning Lists
    • Basic List Operations
    • List Methods
    • Nested List
    • Using Lists as Stack
    • Using Lists as Queues
    • List Comprehensions
    • Looping in Lists
    • filter() Function
    • map() Function
    • reduce() Function
  5. Python Tuple
    • Creating Tuple
    • Utility of Tuples
    • Accessing Values in a Tuple
    • Updating Tuple
    • Deleting Elements in Tuple
    • Basic Tuple Operations
    • Tuple Assignment
    • Tuples for Returning Multiple Values
    • Counting the Elements: count() Method
    • List Comprehension and Tuples
    • Variable-length Argument Tuples
    • Advantages
  6. Python Set
    • Creating a Set
    • Built-in Dictionary Functions and Methods
  7. Python Dictionary
    • Creating a Dictionary
    • Accessing Values
    • Adding and Modifying an Item in a Dictionary
    • Modifying an Entry
    • Deleting Items
    • Sorting Items in a Dictionary
    • Nested Dictionaries
    • Looping over a Dictionary
    • Built-in Dictionary Functions and Methods
    • Difference between a List and a Dictionary
    • String Formatting with Dictionaries
    • When to use which Data Structure?
    • List vs Tuple vs Dictionary vs Set
  8. Class and Object
    • Classes and Objects
    • Class Method and self Argument
    • The __init__() Method (The Class Constructor)
    • Class Variables and Object Variables
    • The __del__() Method
    • Public and Private Data Members
    • Private Methods
    • Calling a Class Method from Another Class Method
    • Built-in Functions to Check, Get, Set,and Delete Class Attributes
    • Built-in Class Attributes
    • Garbage Collection (Destroying Objects)
    • Class Methods
    • Static Methods
  9. Inheritance
    • Inheriting Classes in Python
    • Multiple Inheritance
    • Multi-level Inheritance
    • Multi-path Inheritance
    • Composition or Containership or Complex Objects
    • Abstract Classes and Interfaces
    • Metaclass
  10. Operator Overloading
    • Concept Of Operator Overloading
    • Advantage of Operator Overloading
    • Implementing Operator Overloading
    • Reverse Adding
    • Overriding __getitem__() and __setitem__() Methods
    • Overriding the in Operator
    • Overloading Miscellaneous Functions
    • Overriding the __call__() Method
  11. Error and Exception Handling
    • Introduction to Errors and Exceptions
    • Syntax Errors
    • Exceptions
    • Handling Exceptions
    • Multiple Except Blocks
    • Multiple Exceptions in a Single Block
    • Except Block Without Exception
    • The else Clause
    • Raising Exceptions
    • Handling Exceptions in Invoked Functions
    • Built-in and User-defined Exceptions
    • The finally Block
    • Pre-defined Clean–up Action
    • Re-raising Exception
    • Assertions in Python
  12. Python MySQL
    • Environment Setup
    • Database Connection
    • Creating New Database
    • Creating Tables
    • Insert Operation
    • Read Operation
    • Update Operation
    • Join Operation
    • Performing Transactions
  13. Python Tkinter
    • Tkinter Button
    • Tkinter Canvas
    • Tkinter Checkbutton
    • Tkinter Entry
    • Tkinter Frame
    • Tkinter Label
    • Tkinter Listbox
    • Tkinter Menubutton
    • Tkinter Menu
    • Tkinter Message
    • Tkinter Radiobutton
    • Tkinter Scrollbar
    • Tkinter Text
    • Tkinter MessageBox
    • Tkinter PanedWindow
    • Tkinter Toplevel
    • Tkinter LabelFrame
  14. Networking
    • Socket
    • Socket Module Methods
    • Client and server
    • Internet modules
  15. Multithreading
    • Thread
    • Starting a thread
    • Threading module
    • Synchronizing threads
    • Multithreaded Priority
  16. Regular Expressions
    • Match function
    • Search function
    • Modifiers
    • Patterns
  17. Decorators
    • What’s a Decorator?
    • Managing Calls and Instances
    • Using and Defining Decorators
    • Why Decorators?
    • Function Decorators
    • Class Decorators
    • Decorator Nesting
    • Decorator Arguments
  18. Modules and Packages
    • Module Creation
    • Module Usage
    • The import Statement
    • The from Statement
    • The from * Statement
    • Module Namespaces
    • Namespace Nesting
    • Package __init__.py Files
  19. Introduction to NumPy
    • Understanding Data Types in Python
    • Fixed-Type Arrays in Python
    • Creating Arrays from Python Lists
    • Creating Arrays from Scratch
    • NumPy Array Attributes
    • Reshaping of Arrays
    • Computation on NumPy Arrays: Universal Functions
    • Fancy Indexing
    • Sorting Arrays
    • Structured Data: NumPy’s Structured Arrays
  20. Data Manipulation with Pandas
    • Installing and Using Pandas
    • Introducing Pandas Objects
    • Data Indexing and Selection
    • Operating on Data in Pandas
    • Handling Missing Data
    • Hierarchical Indexing
    • Combining Datasets: Concat and Append
    • Combining Datasets: Merge and Join
    • Aggregation and Grouping
    • Pivot Tables
    • High-Performance Pandas: eval() and query()
  21. Visualization with Matplotlib
    • Importing matplotlib
    • Simple Line Plots
    • Simple Scatter Plots
    • Visualizing Errors
    • Density and Contour Plots
    • Histograms, Binnings, and Density
    • Multiple Subplots
    • Text and Annotation