Introduction to Python

• What is python
• Why python
• Python history
• Features of python
• Why python is general language
• Limitations of python
• PSF
• Flavors of Python

Python Getting Started

• Installation process in windows, Unix, Linux and Mac
• Online Python IDLE

Python Real-Time IDEs

• Spyder
• Jupyter
• Pycharm
• (Google colab)
• VScode

Variables in Python

• • Python keywords
  • Define variable
  • Define identifiers
  • Variable Names and Rules
  • Illegal variable names
  • Pascal case and Camel case

Python Literals 

• Define constant or literal
• Types of literals

First python Program

• Python programming structure
• Comments in python
  • Single line comments
  • Multi line comments

   Python File Extensions

• Setting python path in windows
• Quotations in python
• Python indentation
• Multi line statements
• Inside python
• Inside interpreter
  • What is byte code

Python Data Types

• Standard data types
  • Numbers
  • Strings
  • List
  • Tuple
  • Set and FrozenSet
  • Dictionary
• Bytes
• Byte array
• String formatting in python
• Math, random and secrets Module

   Data Type Conversion 

• Type conversion or Type casting
• Explicit data type conversion
• List of Python functions

Command Line Arguments

• • Mnemonic variable names
  • Writing numbers in Binary Octal and Hexadecimal

Python Operators

• Different types of operators
• Arithmetic operators
• Comparison operators
• Assignment operators
• Logical operators
• Bitwise operators
• Membership operators
• Identity operators
• Ternary operators
• Operator precedence
• Difference between “is” vs “==”

Control Statements

• Conditional control statements
  • Simple-if
  • If-else
  • If-elif-else
  • Nested if
  • Negative conditions
• Loop control statements
  • While loop
  • For loop
  • Nested loops
• Branching statements
  • Break
  • Continue
  • Pass
• Pattern programming

 Strings

• Introduction
• Assigning and Re-assigning
• Multiple assignment
• String slicing
• String indexing
• UNICODE strings
• Python String library
  • String methods
• Immutability
  • String Immutability
  • Numbers Immutability
• Case studies

List Data Structure

• What is list
• Creating list
• Different types of list
• Negative indexing
• List methods
• Slice of list
• List functions
• List Mutable
• Nested Lists
• List comprehensions
• Hard Copy, Shallow Copy and Deep copy
• Zip() function
• Unzip

Working with Python Arrays

• Create an array
• Access elements of array
• Array index
• Slicing of an array
• Multi dimensional arrays
• Python matrix

Python Tuples

• What is Tuple
• Different ways of creating tuple
• Tuple object methods
• Tuple immutability
• Difference between List and Tuple

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
• Set Mutability
• functions and methods of set
• Python Frozen set
• Difference between set and frozenset ?

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

Python Modules and Packages

• Importance of modular programming
• What is module
• Types of Modules – Pre defined, User defined.
• User defined modules creation
• Functions based modules
• Class based modules
• Connecting modules
• Import module
• From … import
• Module alias / Renaming module
• Built In properties of module

Packages 

• Organizing python project into packages
• Types of packages – pre defined, user defined.
• Package v/s Folder
• py file
• Importing package
• PIP
  • Introduction to PIP
  • Installing PIP
  • Installing Python packages
  • Un installing Python packages

OOPs – Classes & Objects

Exception Handling & Types of Errors

• What is Exception?
• Why exception handling?
• Syntax error v/s Runtime error
• Exception codes – AttributeError, ValueError, IndexError, TypeError…
• Handling exception – try except block
• Try with multi except
• Handling multiple exceptions with single except block
• Finally block
• Try-except-finally
• Try with finally
• Case study of finally block
• Raise keyword
• Custom exceptions / User defined exceptions
• Need to Custom exceptions
• Assertions

Regular Expressions

• Understanding regular expressions
• String v/s Regular expression string
• “re” module functions
• Match()
• Search()
• Split()
• Findall()
• Compile()
• Sub()
• Subn()
• Expressions using operators and symbols
• Simple character matches
• Special characters
• Character classes
• Mobile number extraction
• Mail extraction
• Different Mail ID patterns
• Data extraction
• Password extraction
• URL extraction
• Vehicle number extraction

Regular Expressions

• Understanding regular expressions
• String v/s Regular expression string
• “re” module functions
• Match()
• Search()
• Split()
• Findall()
• Compile()
• Sub()
• Subn()
• Expressions using operators and symbols
• Simple character matches
• Special characters
• Character classes
• Mobile number extraction
• Mail extraction
• Different Mail ID patterns
• Data extraction
• Password extraction
• URL extraction
• Vehicle number extraction

Files in Python

• Introduction to files
• Opening file
• File modes
• Reading data from file
• Writing data into file
• Appending data into file
• Line count in File
• CSV module
• Creating CSV file
• Reading from CSV file
• Writing into CSV file
• Object serialization – pickle module
• Machine learning based File handling
• XML parsing
• JSON parsing

Date & Time Module

• How to use Date & Date Time class
• How to use Time Delta object
• Formatting Date and Time

Python Data Base Communications(PDBC)

• Introduction to DBMS applications
• File system v/s DBMS
• Communicating with MySQL
• Python – MySQL connector
• connector module
• connect() method
• Oracle Database
• Install cx_Oracle
• Cursor Object methods
• execute() method
• executeMany() method
• fetchone()
• fetchmany()
• fetchall()
• Static queries v/s Dynamic queries
• Transaction management

Data Analytics Modules

• Numpy
• Introduction
• Scipy
• Introduction
• Arrays
• Datatypes
• Matrices
• N dimension arrays
• Indexing and Slicing
• Pandas
• Introduction
• Data Frames
• Merge , Join, Concat
• MatPlotLib introduction
• Seaborn
• plotly
• Drawing plots
• Introduction to Machine learning
• Types of Machine Learning?
• Introduction to Data science

Python NumPy

• Introduction
• Environment Setup
• PIP
• Numpy ndarray object
• Numpy Data types
• Array Attributes
• Array Creation Routine
• Array from Existing data
• Array from Numerical Ranges
• Indexing & Slicing
• Advanced Indexing
• Broadcasting
• Iterating over array
• Array manipulation
• Binary Operations
• String Function
• Mathematical Function
• Arithmetic Operation
• Stastical function
• Sort, Search and Counting functions
• Byte swapping
• Numpy Copy & View
• Linear Algebra
• Matplotlib
• Histogram using matplotlib
• IO with Numpy

Python Pandas

• Introduction
• History
• Pandas key features
• Installation on windows and Linux
• Limitations
• Major Applications
• Series
• Data Frame
• Panel
• Descriptive Statistics
• Pandas function application
• Pandas re-indexing
• Pandas Iteration
• Pandas Sorting
• Options & Customization
• Indexing and Selecting the data
• Pandas Statistical function
• Window function
• Aggregation
• Missing Data
• Pandas Group by
• Aggregation Transformation filtration merging & joining
• Concatenation
• Date functionality
• Time delta
• Categorical Data
• Visualizations

• Quick Read on NumPy, Pandas, Matplotlib with Case study