Python Online Training

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 beneficial 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

Advanced Python

Python Modules

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

Procedural v/s Object oriented programming
Principles of OOP – Encapsulation , Abstraction (Data Hiding)
Classes and Objects
How to define class in python
Types of variables – instance variables, class variables.
Types of methods – instance methods, class method, static method
Object initialization
‘self’ reference variable
‘cls’ reference variable
Access modifiers – private(__) , protected(_), public
AT property class
Property() object
Creating object properties using setaltr, getaltr functions
Encapsulation(Data Binding)
What is polymorphism?
Overriding

i) Method overriding
ii) Constructor overriding

Overloading

i) Method Overloading
ii) Constructor Overloading

iii) Operator Overloading

Class re-usability
Composition
Aggregation
Inheritance – single , multi level, multiple, hierarchical and hybrid inheritance and Diamond inheritance
Constructors in inheritance
Object class
super()
Runtime polymorphism
Method overriding
Method resolution order(MRO)
Method overriding in Multiple inheritance and Hybrid Inheritance
Duck typing
Concrete Methods in Abstract Base Classes
Difference between Abstraction & Encapsulation
Inner classes
Introduction
Writing inner class
Accessing class level members of inner class
Accessing object level members of inner class
Local inner classes
Complex inner classes
Case studies

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
Case studies

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
Case study

File &Directory handling

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
XML parsing
JSON parsing

Python Logging

Logging Levels
implement Logging
Configure Log File in over writing Mode
Timestamp in the Log Messages
Python Program Exceptions to the Log File
Requirement of Our Own Customized Logger
Features of Customized Logger

Date & Time module

How to use Date & Date Time class
How to use Time Delta object
Formatting Date and Time
Calendar module
Text calendar
HTML calendar

OS module

Shell script commands
Various OS operations in Python
Python file system shell methods
Creating files and directories
Removing files and directories
Shutdown and Restart system
Renaming files and directories
Executing system commands

Multi-threading & Multi Processing

Introduction
Multi tasking v/s Multi threading
Threading module
Creating thread – inheriting Thread class , Using callable object
Life cycle of thread
Single threaded application
Multi threaded application
Can we call run() directly?
Need to start() method
Sleep()
Join()
Synchronization – Lock class – acquire(), release() functions
Case studies

Garbage collection

Introduction
Importance of Manual garbage collection
Self reference objects garbage collection
‘gc’ module
Collect() method
Threshold function
Case studies

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
Case studies

Python – Network Programming

What is Sockets?
What is Socket Programming?
The socket Module
Server Socket Methods
Connecting to a server
A simple server-client program
Server
Client

Tkinter & Turtle

Introduction to GUI programming
Tkinter module
Tk class
Components / Widgets
Label , Entry , Button , Combo, Radio
Types of Layouts
Handling events
Widgets properties
Case studies

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
Drawing plots
Introduction to Machine learning
Types of Machine Learning?
Introduction to Data science

DJANGO

Introduction to PYTHON Django
What is Web framework?
Why Frameworks?
Define MVT Design Pattern
Difference between MVC and MVT

PANDAS

Pandas – Introduction

Pandas – Environment Setup

Pandas – Introduction to Data Structures

Dimension & Description
Series
DataFrame
Data Type of Columns
Panel

Pandas — Series

Series
Create an Empty Series
Create a Series f
rom ndarray
rom dict
rom Scalar
Accessing Data from Series with Position
Retrieve Data Using Label (Index)

Pandas – DataFrame

DataFrame
Create DataFrame
Create an Empty DataFrame
Create a DataFrame from Lists
Create a DataFrame from Dict of ndarrays / Lists
Create a DataFrame from List of Dicts
Create a DataFrame from Dict of Series
Column Selection
Column Addition
Column Deletion
Row Selection, Addition, and Deletion

Pandas – Panel

Panel()
Create Panel
Selecting the Data from Panel

Pandas – Basic Functionality

DataFrame Basic Functionality

Pandas – Descriptive Statistics

Functions & Description
Summarizing Data

Pandas – Function Application

Table-wise Function Application
Row or Column Wise Function Application
Element Wise Function Application

Pandas – Reindexing

Reindex to Align with Other Objects
Filling while ReIndexing
Limits on Filling while Reindexing
Renaming

Pandas – Iteration

Iterating a DataFrame
iteritems()
iterrows()
itertuples()

Pandas – Sorting

By Label
Sorting Algorithm

Pandas – Working with Text Data

Pandas – Options and Customization

get_option(param)
set_option(param,value)
reset_option(param)
describe_option(param)
option_context()

Pandas – Indexing and Selecting Data

.loc()
.iloc()
.ix()
Use of Notations

Pandas – Statistical Functions

Percent_change
Covariance
Correlation
Data Ranking

Pandas – Window Functions

.rolling() Function
.expanding() Function
.ewm() Function

Pandas – Aggregations

Applying Aggregations on DataFrame

Pandas – Missing Data

Cleaning / Filling Missing Data
Replace NaN with a Scalar Value
Fill NA Forward and Backward
Drop Missing Values
Replace Missing (or) Generic Values

Pandas – GroupBy

Split Data into Groups
View Groups
Iterating through Groups
Select a Group
Aggregations
Transformations
Filtration

Pandas – Merging/Joining

Merge Using ‘how’ Argument

Pandas – Concatenation

Concatenating Objects
Time Series

Pandas – Date Functionality

Pandas – Timedelta

Pandas – Categorical Data

Object Creation

Pandas – Visualization

Bar Plot
Histograms
Box Plots
Area Plot
Scatter Plot
Pie Chart

Pandas – IO Tools

Pandas – Sparse Data

Pandas – Caveats & Gotchas

Pandas – Comparison with SQL

NUMPY

NUMPY − INTRODUCTION

NUMPY − ENVIRONMENT

NUMPY − NDARRAY OBJECT

NUMPY − DATA TYPES

Data Type Objects (dtype)

NUMPY − ARRAY ATTRIBUTES

shape
ndim
itemsize
flags

NUMPY − ARRAY CREATION ROUTINES

empty
zeros
ones

NUMPY − ARRAY FROM EXISTING DATA

asarray
frombuffer
fromiter

NUMPY − ARRAY FROM NUMERICAL RANGES

arange
linspace
logspace

NUMPY − INDEXING & SLICING

NUMPY − ADVANCED INDEXING

Integer Indexing
Boolean Array Indexing

NUMPY − BROADCASTING

NUMPY − ITERATING OVER ARRAY

Iteration
Order
Modifying Array Values
External Loop
Broadcasting Iteration

NUMPY – ARRAY MANIPULATION

reshape
ndarray.flat
ndarray.flatten
ravel
transpose
ndarray.T
swapaxes
rollaxis
broadcast
broadcast_to
expand_dims
squeeze
concatenate
stack
hstack and numpy.vstack
split
hsplit and numpy.vsplit
resize
append
insert
delete
unique

NUMPY – BINARY OPERATORS

bitwise_and
bitwise_or
invert()
left_shift
right_shift

NUMPY − STRING FUNCTIONS

NUMPY − MATHEMATICAL FUNCTIONS

Trigonometric Functions
Functions for Rounding

NUMPY − ARITHMETIC OPERATIONS

reciprocal()
power()
mod()

NUMPY − STATISTICAL FUNCTIONS

amin() and numpy.amax()
ptp()
percentile()
median()
mean()
average()
Standard Deviation
Variance

NUMPY − SORT, SEARCH & COUNTING FUNCTIONS

sort()
argsort()
lexsort()
argmax() and numpy.argmin()
nonzero()
where()
extract()

NUMPY − BYTE SWAPPING

ndarray.byteswap()

NUMPY − COPIES & VIEWS

No Copy
View or Shallow Copy
Deep Copy

NUMPY − MATRIX LIBRARY

empty()
matlib.zeros()
matlib.ones()
matlib.eye()
matlib.identity()
matlib.rand()

NUMPY − LINEAR ALGEBRA

dot()
vdot()
inner()
matmul()
Determinant
linalg.solve()

NUMPY − MATPLOTLIB

Sine Wave Plot
subplot()
bar()

NUMPY – HISTOGRAM USING MATPLOTLIB

histogram()
plt()

NUMPY − I/O WITH NUMPY

save()
savetxt()

You may be also interested in

Register for FREE Demo

Fields marked with (*) are mandatory

Client Feedback

Thanks, you guys provided the best online training in SAP BODS. The hands on training is very informative and helpful.

- David Sergi, Camaga Ltd; U.K