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Nareshit Course Content

This document provides an overview and content details for a Python training course offered by Naresh i Technologies. The training aims to teach students Python concepts and constructs over 35 daily 1-hour sessions. Topics include core Python programming, data structures, functions, modules, object-oriented programming, Pandas, and NumPy. No prerequisites are required beyond basic computer programming knowledge. The course is suitable for data professionals, developers, and those interested in building a career with Python.
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0% found this document useful (0 votes)
2K views28 pages

Nareshit Course Content

This document provides an overview and content details for a Python training course offered by Naresh i Technologies. The training aims to teach students Python concepts and constructs over 35 daily 1-hour sessions. Topics include core Python programming, data structures, functions, modules, object-oriented programming, Pandas, and NumPy. No prerequisites are required beyond basic computer programming knowledge. The course is suitable for data professionals, developers, and those interested in building a career with Python.
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as DOC, PDF, TXT or read online on Scribd
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Python Training https://nareshit.

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Contents [hide] Student Enquiry
Python Training Overview
Corporate Training
1 Python Training Overview
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Python is a general-purpose interpreted, interactive, object-oriented, and 1.1 What are the Python Course Pre-requisites
View/Post Testimonials
high-level programming language. Python has been one of the premier, 1.2 Objectives of the Course
Contact Us
flexible, and powerful open-source language that is easy to learn, easy to 1.3 Who should do the course
use, and has powerful libraries for data manipulation and analysis 1.4 Python Training Course Duration
2 Python Course Content REGISTER FOR COURSE !
2.1 Core Python

What are the Python Course Pre-requisites 2.1.1 Introduction to Languages


2.1.2 Introduction to Python Learn from the Real-Time Experts

There are no hard pre-requisites. Basic understanding of Computer 2.1.3 Python Software’s
Programming terminologies is sufficient. Also, basic concepts related to 2.1.4 Python Language Fundamentals
Programming and Database is beeficial but not mandatory. 2.1.5 Different Modes of Python First Name *
2.1.6 Python Variables
2.1.7 Operators

Objectives of the Course 2.1.8 Input & Output Operators Last Name *

2.1.9 Data Structures or Collections


To understand the concepts and constructs of Python 2.1.10 List Collection
To create own Python programs, know the machine learning 2.1.11 Tuple Collection Email *

algorithms in Python and work on a real-time project running on 2.1.12 Set Collection
Python 2.1.13 Dictionary Collection
Phone *
2.1.14 Functions

Who should do the course 2.2 Advanced Python


2.2.1 Python Modules
Mode of Training *
Big Data Professionals 2.2.2 Packages
IT Developers 2.2.3 OOPs
Those who are showing interest to build their career in 2.3 PANDAS State
Python 2.4 NUMPY
2.5 Share this:

Python Training Course Duration Course *

35 Days, Daily 1 Hours

Python Course Content

Core Python

Introduction to Languages
FIND COURSES HERE
What is Language?
Types of languages Android Training
Introduction to Translators iPhone Training
Compiler
Asp.Net Training
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Programming Languages v/s Scripting Languages C++ Training


Difference between Scripting and Programming languages Data Structure Training
What is programming paradigm?
Java Training
Procedural programming paradigm
Core Java Training
Object Oriented Programming paradigm
Advanced Java Training

Hibernate Training
Introduction to Python
J2EE Training

What is Python? Spring 5.x Training


WHY PYTHON? Hibernate Training
History
Web Services Training
Features – Dynamic, Interpreted, Object oriented, Embeddable, Extensible, Large standard libraries, Free and Open source
Struts Training

XML Training
Why Python is General Language?
Java Online Training
Limitations of Python
What is PSF? Oracle Training

Python implementations SQL Server Training


Python applications Selenium Training
Python versions UNIX LINUX Training
PYTHON IN REALTIME INDUSTRY
PHP Training
Difference between Python 2.x and 3.x
HTML5 CSS3 Training
Difference between Python 3.7 and 3.8
jQuery Training
Software Development Architectures
UI Technologies Training

Python Software’s UI UX Training

AngularJS Training
Python Distributions Angular 2 Training
Download &Python Installation Process in Windows, Unix, Linux and Mac
Angular 4 Training
Online Python IDLE
Angular 6 Training
Python Real-time IDEs like Spyder, Jupyter Note Book, PyCharm, Rodeo, Visual Studio Code, ATOM, PyDevetc
Angular 7 Training

Data Science Training


Python Language Fundamentals
Artificial Intelligence Training
Python Implementation Alternatives/Flavors Hadoop Training
Keywords
Apache Spark Training
Identifiers
Python Training
Constants / Literals
Hadoop Online Training
Data types
Python VS JAVA DevOps Training

Python Syntax AWS Training

IoT Training

Different Modes of Python SalesForce CRM Training

Digital Marketing Training


Interactive Mode
RPA Training
Scripting Mode
Blue Prism Training
Programming Elements
Structure of Python program Automation Anywhere Training

First Python Application Automation Anywhere Online Training


Comments in Python Blockchain Training
Python file extensions Realtime Projects
Setting Path in Windows Real Time Java Project
Edit and Run python program without IDE
Real-Time Project on PHP
Edit and Run python program using IDEs
Doubleclick for Publishers Training
INSIDE PYTHON
Software Training in Chennai
Programmers View of Interpreter
Inside INTERPRETER Testing Tools Training

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
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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
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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
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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

1.
2.
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Overloading

1. i) Method Overloading
2. 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
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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()
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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
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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


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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


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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

csv

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)


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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
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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()
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linalg.solve()

NUMPY − MATPLOTLIB

Sine Wave Plot


subplot()
bar()

NUMPY – HISTOGRAM USING MATPLOTLIB

histogram()
plt()

NUMPY − I/O WITH NUMPY

save()
savetxt()

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DevOps Interview Questions Address: 2nd Floor, Durga Bhavani Plaza, 2nd Floor Plot No.172 & 173,
Training Institute Overview Naresh i Technologies
Naresh i Technologies (Pronounced: NareshIT) is a AngularJS Interview Questions Ameerpet, Hyderabad Above Axis Bank, Behind PTC Bus Stop,
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Consulting and Technology Workshops. Using our
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