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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
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
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.

General Certificate (NASSCOM Approved Courses)



  • Accredited by NASCCOM
  • Industry-recognized
  • Developed in consultation with industry experts
  • Focus on future skills
  • Aligned with industry demands
  • Comprehensive curriculum
  • Hands-on training
  • Career-oriented
  • Enhances employability
  • Endorsed by NASCCOM

Average package of course (Python Developer)

90% Avg
salary hike
4L Avg
Package
Training Features
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Hands-On Practical Labs

Apply theoretical knowledge in practical labs, gaining valuable hands-on experience.

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Benefit from career guidance services to navigate job opportunities after certification.

Expert-Led Instruction

Learn from experienced instructors with industry expertise, providing valuable insights.

24/7 Support

Access round-the-clock support for immediate assistance, ensuring a seamless learning journey.

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