Python Developer Online Training Course [Real-Time]

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Python Developer

Course Overview

Naresh IT provides comprehensive online training for Python developers, encompassing foundational to advanced concepts of the Python programming language. Through a meticulously crafted curriculum, participants embark on a journey that systematically guides them through various modules and hands-on exercises. These practical sessions are designed to immerse learners in Python development, enabling them to gain invaluable experience along the way. The structured approach ensures that participants acquire a well-rounded understanding of Python, covering crucial aspects such as syntax, utilization of libraries, exploration of frameworks, and adoption of industry best practices. With Naresh IT's Python Developer Online Training, individuals not only grasp the theoretical underpinnings but also acquire the practical skills essential for proficient Python development.

Learn software skills with real experts, either in live classes with videos or without videos, whichever suits you best.

Description

The training program includes lectures, interactive sessions, coding exercises, and projects to facilitate effective learning. Participants will learn how to write Python code efficiently, understand data structures and algorithms, work with various Python libraries such as NumPy, Pandas, Matplotlib, and more. Additionally, they will delve into web development using frameworks like Django or Flask, explore data science and machine learning applications, and gain insights into automation, scripting, and system administration tasks using Python.

Course Objectives

The primary objectives of the Python Developer Online Training by Naresh IT are:

To provide a comprehensive understanding of Python programming language from basics to advanced concepts.
To equip participants with practical skills in Python development through hands-on exercises and projects.
To enable learners to work on real-world Python projects, including web development, data analysis, and automation tasks.
To prepare participants for career opportunities as Python developers in various industries such as software development, data science, web development, and more.

Prerequisites

- Basic understanding of computer operations.
- Familiarity with using text editors or IDEs.
- Knowledge of basic mathematics and logical thinking.
- Understanding of fundamental programming concepts (e.g., variables, loops).
- Awareness of problem-solving techniques.
- Experience with navigating online resources for learning.

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Course Curriculum

Importance of Programming Languages in IT Industry
Types of Programming Languages (Machine level to High level languages)
Introduction to Translators
Need of Scripting Languages
Programming Languages Vs. Scripting Languages
Programming paradigm

What is Python
Why Python
History of Python
What is PSF and PEP
Features of Python (Simple, Freeware and Open source, Platform Independent, Dynamically Typed , Interpreted, High Level, Both Functional and Object oriented, Embedded, Extensible, Supports Third Party APIs etc.)
Limitations of Python
Python implementations
Real Time applications developed by Using Python
Various Version of Python(Python2.x,Python 3.x and New Features of current Version)
Software Development Architectures

Various Python Distributions
Download & Installation Process of Python in Windows, Unix, Linux and Mac
Working with Python Command Prompt and IDLE
Working with Python Real-time IDEs

Importance of Literals and constants
Need of Identifiers, Variables
Rules for Identifiers, Variables
Python Syntax Notations
Python and Java Comparisons
Time and Space Complexities

Interactive Mode
Scripting or Batch Mode
Programming Elements
Python file extensions
Structure of Python program
First Python Application
Comments in Python
Setting Path in Windows
Edit and Run python program using IDEs
Edit and Run python program without IDE
Inside Python Software
Programmers View of Interpreter
Inside Interpreter
Importance of Byte Code in PYTHON
Python Debugger

Input and Output statements
Need of Taking Input
input() and Its syntaxes
Need of displaying output
print() ans its Syntaxes
Programming Examples
eval() and Its syntaxes
Programming Examples

Arithmetic Operators
Assignment Operators
Relational OR Comparison Operators
Logical Operators
Bitwise Operators
Membership Operators
Identity Operators
Ternary Operator
Shorthand operators
Operator precedence
Programming Examples / Case Study

Need of Data Types
Classification of Data types

Need Flow Control Statements
Types of Flow Control Statements
Need of Conditional Statements
Types of Conditional Statements
Need of Looping Statements
Types of Looping Statements
Need of of Transfer Flow Statements
Types of Transfer Flow Statements
Nested or Inner Loops
Programming Examples or Case Studies

Importance of strings
Mutable and Immutable Objects
Types of string
Memory Management of string data
Indices Mechanism of string data
Forward Indexing and Backward Indexing
Slicing Operations with Various Syntaxes
String Formatting
Pre-defined Functions of str class
Programming Examples / Case studies

Importance of byte and bytearray
Pre-defined Functions of bytes and bytearray
Pre-defined Functions of range
Programming Examples / Case study

What is List?
Properties of List collection
Different ways of creating List and their types
List indices
Processing and Accessing elements of List through Indexing and Slicing
List object methods or Functions
List is Mutable
Mutable and Immutable elements of List
Inner or Nested Lists
ShallowCopy and DeepCopy
Working zip() in Python
How to unzip?
Programming Example / Case studies

What is tuple?
Properties of Tuple collection
Different ways of creating Tuple
Function / Method of Tuple object
Tuple is Immutable
Mutable and Immutable elements of Tuple
Accessing and Processing tuple data through Indexing and Slicing
List v/s Tuple
Inner or Nested Tuples
Tuple in list, list in tuple, tuple in tuple
Apply the function of list and tuple on Inner tuples and lists
Programming Examples or Case studies

Need of set and Frozenset
Properties of set and Frozenset
Different ways of creating and Frozenset
Difference between list and set and Frozenset
Iteration over Sets
Accessing elements of set
Functions or Methods in Set and Frozenset
Mathematical Methods of set
Difference between set and frozenset
Programming Examples or Case study

Need of dictionary
Difference between list, set and dictionary
Creating a dictionary and their types
Hashing in Python Collections or Data Structures
Accessing Keys and values of dictionary
Methods of dictionary
Shallow and Deep Copy on dictionary
Updating Dictionary
Reading keys from Dictionary
Reading values from Dictionary
Reading items from Dictionary
Sorting the Dictionary
Nested or Nested Dictionaries
List in Dictionary
Tuple and set in dictionary
Dictionary comprehension
Programming Examples or Case Study

Need of Comprehensions
List Comprehensions
Programming Examples of Case Study
Dictionary Comprehensions
Programming Examples of Case Study
Set Comprehensions
Programming Examples of Case Study

None Keyword or Value
Properties of NoneType
Usage of None
Programming Examples

Purpose of Functions
Types of Programming Languages
Advantages of Functions
Definition of Function
Number of approaches to define Functions
Parameters and Arguments
Types of Arguments
Global Variables and Local Variables
Global keyword and globals()
Scope and Lifetime of variables in functions
Anonymous Function or Lambda Functions
Implementation Anonymous Function
Recursive functions
Iterables, Iterators
Nested OR Inner Functions
Generators
Yeild vs return keywords
Generator Expressions
Advantages of Generators over Comprehensions
Monkey patching
Built-in / Special Functions in Python
Programming Examples

Importance of modular programming
What is module
Types of Modules
Stesps for Devloping Programmer-Defined modules
Functions based modules
Class based modules
Number of Approaches to Re-Use Modules
Aliasing of Module Name, Function Name, Variable Names and Class Name.
Built In properties of module
Reloading module
Programming Examples / Case Studies

Need of Packages
Definition of Package
Organizing Python project into packages
Types of Packages
Package v/s Folder
__init__.py file
Importing package
PIP
Installing PIP
Installing Python packages using PIP
Un-installing Python packages
Re-using Packages
By using sys.path append()
By using Python path

Functional(Procedural) v/s Object Oriented programming
Principles of OOP – Encapsulation , Abstraction (Data Hiding), Inheritance, Polymorphism
Need of Classes and Objects
Syntax for Defining a class
Syntax for creating an object
Types of variables
Importance of 'self' and 'cls'
Types of methods
Need Constructors
Need of Destructors
Need inner class
Data Encapsulation
Data Binding
Inheritance(single , multi level, multiple, hierarchical and hybrid inheritance)
Constructors in inheritance
Object class
Polymorphism
Overriding
Method resolution order(MRO)
Method overriding in Multiple inheritance and Hybrid Inheritance
Duck typing
Overloading
Super() and class name approach
Abstract Base Classes
Composition
Aggregation
Object class
Programming Examples / Case studies

Need Of Exception
What is Exception Handling
Types of Errors
Types of Exceptions
Exception Handling Hierarchy Chart
Key words for Handling exception
Syntax for Handling the Exceptions
Various forms of except block
Try with multi specific exception Handling block
Handling all exceptions with except block
Finally block
Nested OR Inner try blocks
Raise keyword
Development of Programmer OR User OR Custom Defined Exception
Programming Examples / Case studies

Need of Regular Expressions
String v/s Regular expression string
Functions in re module
Expressions using operators and symbols
Simple character matches
Special characters
Programmer-Defined Character classes
Pre-Defined Character classes
Need of Quantifiers in re module
Mobile number extraction
Programming Examples / Case studies

Non-persistent and Persistent Applications
Introduction to files
Types of Files (text files / binary files)
File Opening modes
Reading data from file
Writing data into file
Random Access Files
Working with CSV Files (CSV Module)
Object serialization and De-Serialization(Pickle Module)
Pickle Module
XML Parsing
Working with JSON Files
Programming Examples / Case studies

Importance of specialized container data types
Counter
OrderedDict
Defaultdict
ChainMap
Namedtuple()
Deque
Programming Examples / Case studies

Purpose of os Module
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
Programming Examples / Case studies

Need of Multi Threading
Differences between Multi-tasking of OS and Multi-threading of Python
Process Based and Thread Based Applications
Threading module
Life Cycle of thread
Types of threads
Number of Approaches to Creat a thread
Functions in threading module (Thread(), active_count(), current_therad())
Function in Thread class of Threading
Module(start(), is_alive(), run(), join(), name attribute..etc)
Creating Single and Multiple Threads
Implementation of Synchronization Technique in Threading
Lock class of threading module
Function in Lock class(acquire(), release())
Programming Examples or Case studies

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

How to use Date & Date Time class
How to use Time Delta object
Formatting Date and Time
Calendar module
Text calendar
HTML calendar
Programming Examples / Case studies

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

Introduction to DBMS applications
File system v/s DBMS
Installing External Modules by using pip in various IDEs
Steps for Developing Python Data Base Communications
Static queries v/s Dynamic queries
Transaction management
Parameterized queries
Programming Examples / Case Studies

Need of Network Programming
Introduction to Physical address/ IP address/ Port address
Introduction to TCP and UDP protocols
What is Socket
Steps for Developing Server Side Programming
Steps for Developing Client Side Programming
The socket Module
Development of Chatting Applications
Development of Client-Server Applications with Database Communication
Programming Examples / Case Studies

Introduction to GUI programming
Tkinter module
Tk class
Components / Widgets and Widgets properties
Label, Entry, Button, Combo, Radio, Message
Types of Layout Managers
Handling events
Implementing simple applications using Window and Widgets with events
Case studies

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Who can learn this course

This course is suitable for a wide range of individuals, including:

Beginners with no prior programming experience who want to start their journey in software development.
Students pursuing computer science or related degrees seeking to enhance their programming skills with Python.
Professionals looking to switch careers or upskill in Python programming for better job prospects.
Software developers proficient in other programming languages who wish to add Python to their skillset.
Data analysts, data scientists, and researchers interested in utilizing Python for data analysis, visualization, and machine learning.
System administrators and DevOps engineers aiming to automate tasks using Python scripting.