Python is an interpreted, high-level, general-purpose programming language. It supports multiple programming paradigms, including procedural, object-oriented, and functional programming. Its language constructs and object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects.

• Knowledge of basic mathematics is required

Module 1: Introduction to Python

• What is Python? Key Features and Applications
• Installing Python (Windows, Mac, Linux)
• Setting Up the Development Environment:
  • Python IDEs: PyCharm, VS Code, Jupyter Notebook
  • Using the Python REPL
• Writing Your First Python Program
• Python Syntax and Indentation

Module 2: Python Basics

• Variables and Data Types
  • Integers, Floats, Strings, Booleans
  • Type Conversion and Casting
• Input and Output
• Operators:
  • Arithmetic, Assignment, Comparison, Logical, Bitwise
• Comments and Docstrings

Module 3: Control Structures

• Conditional Statements:
  • if, elif, else
• Loops:
  • for Loops
  • while Loops
• Loop Control Statements:
  • break, continue, pass
• List Comprehensions

Module 4: Data Structures

• Strings:
  • String Methods, Slicing, and Formatting
• Lists:
  • Operations, Methods, Nested Lists
• Tuples:
  • Immutable Sequences and Their Uses
• Sets:
  • Set Operations (Union, Intersection, Difference)
• Dictionaries:
  • Key-Value Pairs, Dictionary Methods, and Iteration

Module 5: Functions and Modules

• Defining Functions:
  • Parameters, Return Values, Default Arguments
• *args and **kwargs
• Lambda Functions
• Scope and global/nonlocal Keywords
• Importing and Using Modules:
  • Built-in Modules (e.g., math, random)
  • Creating and Importing Custom Modules
• Python Standard Library Overview

Module 6: Object-Oriented Programming (OOP)

• Classes and Objects:
  • Defining and Using Classes
  • Attributes and Methods
• Inheritance and Polymorphism
• Encapsulation and Abstraction
• Magic/Dunder Methods (e.g., __init__, __str__, __repr__)
• Static and Class Methods

Module 7: File Handling

• Working with Files:
  • Reading, Writing, and Appending
  • File Modes (r, w, a, rb, wb)
• Handling File Paths
• Using with Statement (Context Managers)
• Working with CSV Files:
  • csv Module
• JSON Data:
  • Reading and Writing JSON (json Module)

Module 8: Error and Exception Handling

• Understanding Errors and Exceptions
• try, except, else, finally
• Raising Exceptions
• Custom Exception Classes

Module 9: Advanced Python Concepts

• Iterators and Generators
• Decorators
• Closures
• Context Managers
• Regular Expressions (re Module)
• Comprehensions:
  • List, Dictionary, Set Comprehensions

Module 10: Working with Libraries and Frameworks

• Popular Libraries:
  • NumPy: Numerical Computations
  • Pandas: Data Manipulation and Analysis
  • Matplotlib/Seaborn: Data Visualization
  • Requests: HTTP Requests
  • BeautifulSoup: Web Scraping
  • Flask/Django: Web Development
  • SQLAlchemy: Database ORM
• Installing Libraries with pip

Module 11: Testing and Debugging

• Debugging Python Programs
• Writing Unit Tests with unittest
• Mocking and Test Coverage
• Using Debugging Tools (e.g., pdb, Debuggers in IDEs)

Module 12: Working with Databases

• Introduction to Databases and SQL
• Connecting to Databases:
  • SQLite (sqlite3 Module)
  • PostgreSQL/MySQL (via Libraries like psycopg2 or mysql-connector)
• Performing CRUD Operations
• ORMs in Python (e.g., SQLAlchemy, Django ORM)

Module 13: Concurrency and Parallelism

• Multithreading:
  • threading Module
• Multiprocessing:
  • multiprocessing Module
• Async Programming:
  • asyncio, await, and async

Module 14: Automation and Scripting

• Automating Tasks with Python
• Working with OS and System Tools (os, shutil, subprocess)
• Email Automation (smtplib)
• Scheduling Scripts (schedule Library)
• Web Automation with Selenium

Module 15: Data Science with Python

• Introduction to Data Science
• Using NumPy for Numerical Data
• Using Pandas for Data Analysis
• Data Visualization:
  • Matplotlib, Seaborn
• Introduction to Machine Learning with scikit-learn

Module 16: Web Development with Python

• Flask Framework:
  • Setting Up Flask Applications
  • Routing and URL Building
  • Templates with Jinja2
  • Handling Forms and Requests
• Django Framework:
  • Setting Up Django Projects
  • Models, Views, and Templates (MVT Pattern)
  • User Authentication
  • Admin Panel and REST API Development

Module 17: Packaging and Distribution

• Creating Python Packages
• Using setuptools and distutils
• Publishing on PyPI

Module 18: Capstone Projects

• Examples:
  • Build a To-Do List App (Flask/Django)
  • Create a Web Scraper for Real-Time Data
  • Develop a Data Analysis Dashboard
  • Automate a Daily Report Generator
  • Build a REST API for an E-Commerce Backend
  • Implement a Machine Learning Model for Predictions

• Flexible Schedules
• Live Online Training

• Training by highly experienced and certified professionals
• No slideshow (PPT) training, fully Hand-on training
• Interactive session with interview QA’s
• Real-time projects scenarios & Certification Help
• 24 X 7 Support