Python Programming for Beginners

About Course

Learn Python programming from basics with practical examples and hands-on exercises. This course covers Python fundamentals, variables, data types, operators, conditional statements, loops, functions and more. Designed for beginners who want to build a strong foundation in Python programming.

Understand Python programming from basics to advanced concepts
Write clean and efficient Python programs
Work with variables, data types, operators and control statements
Use functions, modules and packages effectively
Master strings, lists, tuples, sets and dictionaries
Understand Object-Oriented Programming in Python
Handle files, exceptions and errors
Work with regular expressions and useful Python libraries
Solve practical programming problems and coding exercises
Build real-world Python projects
Prepare for Python programming interviews and assessments

Course Content

Module 1: Introduction to Python
Learn the fundamentals of Python programming, its features, applications, installation process, and how to write your first Python program.

Lesson 1: What is Python?

00:10
Lesson 2: Features of Python

00:10
Lesson 3: Installing Python & VS Code

00:10
Lesson 4: Your First Python Program

00:10
Lesson 5: Python Syntax, Comments & Indentation

Module 2: Variables & Data Types
Learn how Python stores and manages data using variables, identifiers, built-in data types, dynamic typing, type checking, and practical examples.

Module 3: Python Operators
Learn the different types of operators in Python including arithmetic, assignment, comparison, logical, identity, membership, and bitwise operators with practical examples.

Module 4: Input, Output & Type Conversion
Learn how to accept user input, display formatted output, convert data between different types, and work with Python's built-in input, output, and type conversion functions.

Module 5: Conditional Statements
Learn how to control the flow of Python programs using conditional statements such as if, if-else, if-elif-else, nested conditions, and conditional expressions with practical programs.

Module 6: Loops in Python
Learn how to repeat tasks efficiently in Python using while and for loops, range(), nested loops, loop control statements, and practical looping programs.

Lesson 32: Introduction to Loops
Lesson 33: The while Loop
Lesson 34: The for Loop
Lesson 35: The range() Function
Lesson 36: Nested Loops
Lesson 37: break Statement
Lesson 38: continue and pass Statements
Lesson 39: else with Loops
Lesson 40: Loops – Practical Programs and Patterns

Module 7: Strings in Python
Learn how to create, access, manipulate, format, search, and process text data in Python using string indexing, slicing, operators, methods, escape sequences, and practical programs.

Lesson 41: Introduction to Strings
Lesson 42: String Indexing
Lesson 43: String Slicing
Lesson 44: String Operators
Lesson 45: Important String Methods
Lesson 46: Searching and Replacing in Strings
Lesson 47: Splitting and Joining Strings
Lesson 48: String Testing and Validation Methods
Lesson 49: Escape Sequences and String Formatting
Lesson 50: String Practical and Interview Programs

Module 8: Lists in Python
Learn how to create, access, modify, organize, and process collections of data using Python lists, including indexing, slicing, list methods, nested lists, comprehensions, and practical programs.

Lesson 51: Introduction to Lists
Lesson 52: Accessing List Elements – Indexing
Lesson 53: List Slicing
Lesson 54: Adding Elements to a List
Lesson 55: Updating and Removing List Elements
Lesson 56: Important List Methods and Operations
Lesson 57: Sorting and Reversing Lists
Lesson 58: Nested Lists and Two-Dimensional Data
Lesson 59: List Comprehension
Lesson 60: List Practical and Interview Programs

Module 9: Tuples in Python
Learn how to create, access, manipulate, and work with tuples in Python. This module covers tuple operations, methods, packing, unpacking, and practical applications.

Module 10: Sets in Python
Learn how to create and work with sets in Python. This module covers set properties, operations, methods, and practical applications for handling unique and unordered data.

Module 11: Dictionaries in Python
Learn how to create, access, modify, and manage dictionaries in Python. This module covers key-value pairs, dictionary methods, operations, and practical applications for storing and processing structured data.

Module 12: Functions in Python
Learn how to create and use functions in Python to organize code, improve reusability, and simplify complex programs. This module covers function creation, parameters, arguments, return values, and different types of arguments.

Module 13: Advanced Functions and Lambda Expressions
Explore advanced function concepts in Python including lambda expressions, recursion, scope of variables, and functional programming tools used for efficient data processing.

Module 14: Modules and Packages in Python
Learn how to organize Python programs using modules and packages. This module covers built-in modules, user-defined modules, importing techniques, and creating reusable Python packages.

Module 15: Object-Oriented Programming – Introduction
Learn the fundamentals of Object-Oriented Programming (OOP) in Python. This module introduces classes, objects, constructors, instance variables, methods, and the foundation required for advanced OOP concepts.

Module 16: Object-Oriented Programming – Advanced Concepts
Explore advanced Object-Oriented Programming concepts in Python. This module covers inheritance, method overriding, polymorphism, encapsulation, and abstraction to build structured and reusable applications.

Module 17: Exception Handling in Python
Learn how to identify and handle runtime errors using Python's exception handling mechanism. This module covers try-except blocks, multiple exceptions, finally, raise, and user-defined exceptions.

Module 18: File Handling in Python
Learn how to create, read, write, append, and manage files using Python. This module covers file modes, text file operations, the with statement, and practical file-processing applications.

Module 19: Regular Expressions in Python
Learn how to search, match, extract, and validate text using Regular Expressions. This module introduces patterns, special characters, Python's re module, and real-world data validation.

Module 20: Date, Time and Math Operations in Python
Learn how to work with dates, times, mathematical operations, and random values using Python's built-in modules. This module focuses on practical utilities frequently required in real-world applications.

Module 21: Comprehensions in Python
Learn how to write concise and efficient Python code using comprehensions. This module covers list, dictionary, and set comprehensions along with conditions and practical data-processing examples.

Module 22: Iterators and Generators in Python
Understand Python's iterator and generator concepts for efficient data processing. This module covers iterable objects, iterators, iter(), next(), generator functions, and the yield keyword.

Module 23: Decorators in Python
Learn how decorators enhance the functionality of functions and methods without modifying their original code. This module covers nested functions, function arguments, decorators, and practical applications.

Module 24: Multithreading in Python
Learn the fundamentals of multithreading and concurrent execution in Python. This module covers thread creation, the threading module, synchronization, and practical applications.

Module 25: Database Programming with Python and MySQL
Learn how to connect Python applications with MySQL databases. This module covers database connectivity, SQL execution, CRUD operations, transactions, and building simple database-driven applications.

Module 26: Working with CSV and JSON Files
Learn how to work with CSV and JSON data formats in Python. This module covers reading, writing, updating, and processing structured data commonly used in real-world applications.

Module 27: NumPy Fundamentals
Learn the fundamentals of NumPy, one of the most important Python libraries for numerical computing. This module covers arrays, indexing, mathematical operations, and multidimensional data.

Module 28: Pandas Fundamentals
Learn how to analyze and manipulate structured data using the Pandas library. This module introduces Series, DataFrames, data selection, filtering, and basic data analysis.

Module 29: Data Visualization with Matplotlib
Learn how to visually represent data using Matplotlib. This module covers different chart types, customization, labels, legends, and practical data visualization techniques.

Module 30: GUI Application Development with Tkinter
Learn how to build desktop applications using Python's Tkinter library. This module covers windows, widgets, layouts, events, forms, and database-connected GUI applications.

Module 31: Advanced Pandas and Data Analysis
Explore advanced data analysis techniques using Pandas. This module covers data cleaning, missing values, grouping, aggregation, merging, and practical analysis of real-world datasets.

Module 32: Python Database Application Development
Apply Python and MySQL concepts to develop database-driven applications. This module focuses on application structure, CRUD operations, validation, search functionality, and project development.

Module 33: Introduction to APIs and REST APIs
Understand how modern applications communicate through APIs. This module introduces APIs, REST architecture, HTTP methods, endpoints, status codes, and JSON-based communication.

Module 34: Working with APIs Using Python
Learn how to connect Python applications with REST APIs, send HTTP requests, process JSON responses, use parameters, and handle API errors.

Module 35: Web Scraping with Python
Learn how Python can extract publicly accessible information from web pages for legitimate data collection and analysis. This module covers HTML basics, Requests, Beautiful Soup, and structured data extraction.

Module 36: Introduction to Flask
Learn the fundamentals of Flask, a lightweight Python web framework. This module introduces web applications, routes, templates, forms, and the basic Flask project structure.

Module 37: Flask Web Application Development
Build database-driven web applications using Flask. This module covers forms, templates, database integration, CRUD operations, authentication concepts, and practical project development.

Module 38: Python Automation and Real-World Scripts
Learn how Python can automate repetitive tasks and improve productivity. This module covers file automation, Excel automation, email concepts, and practical automation scripts.

Module 39: Python Major Project
Apply the concepts learned throughout the course to design and develop a complete Python application. Students will learn project planning, development, testing, debugging, documentation, and presentation.

Module 40: Python Interview Preparation and Final Assessment
Prepare for Python technical interviews and evaluate the knowledge gained throughout the course. This module covers interview questions, coding challenges, project explanation, mock interviews, and final assessment.

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About Course

What Will You Learn?

Course Content

Module 1: Introduction to Python Learn the fundamentals of Python programming, its features, applications, installation process, and how to write your first Python program.

Lesson 1: What is Python?

Lesson 2: Features of Python

Lesson 3: Installing Python & VS Code

Lesson 4: Your First Python Program

Lesson 5: Python Syntax, Comments & Indentation

Module 2: Variables & Data Types Learn how Python stores and manages data using variables, identifiers, built-in data types, dynamic typing, type checking, and practical examples.

Lesson 6: Introduction to Variables

Lesson 7: Rules for Naming Variables

Lesson 8: Multiple Assignment

Lesson 9: Python Data Types

Lesson 10: Checking Data Types with type()

Lesson 11: Dynamic Typing in Python

Module 3: Python Operators Learn the different types of operators in Python including arithmetic, assignment, comparison, logical, identity, membership, and bitwise operators with practical examples.

Lesson 12: Arithmetic Operators

Lesson 13: Assignment Operators

Lesson 14: Comparison Operators

Lesson 15: Logical Operators

Lesson 16: Identity and Membership Operators

Lesson 17: Bitwise Operators

Lesson 18: Operator Precedence and Associativity

Module 4: Input, Output & Type Conversion Learn how to accept user input, display formatted output, convert data between different types, and work with Python's built-in input, output, and type conversion functions.

Lesson 19: Taking User Input with input()

Lesson 20: Displaying Output with print()

Lesson 21: Type Conversion and Type Casting

Lesson 22: Formatted Output Using f-Strings

Lesson 23: String Formatting with format()

Lesson 24: Practical Programs Using Input and Output

Module 5: Conditional Statements Learn how to control the flow of Python programs using conditional statements such as if, if-else, if-elif-else, nested conditions, and conditional expressions with practical programs.

Lesson 25: Introduction to Conditional Statements

Lesson 26: The if Statement

Lesson 27: The if-else Statement

Lesson 28: The if-elif-else Statement

Lesson 29: Nested if Statements

Lesson 30: Conditional Expressions – Ternary Operator

Lesson 31: Conditional Statements – Practical Programs

Module 6: Loops in Python Learn how to repeat tasks efficiently in Python using while and for loops, range(), nested loops, loop control statements, and practical looping programs.

Lesson 32: Introduction to Loops

Lesson 33: The while Loop

Lesson 34: The for Loop

Lesson 35: The range() Function

Lesson 36: Nested Loops

Lesson 37: break Statement

Lesson 38: continue and pass Statements

Lesson 39: else with Loops

Lesson 40: Loops – Practical Programs and Patterns

Module 7: Strings in Python Learn how to create, access, manipulate, format, search, and process text data in Python using string indexing, slicing, operators, methods, escape sequences, and practical programs.

Lesson 41: Introduction to Strings

Lesson 42: String Indexing

Lesson 43: String Slicing

Lesson 44: String Operators

Lesson 45: Important String Methods

Lesson 46: Searching and Replacing in Strings

Lesson 47: Splitting and Joining Strings

Lesson 48: String Testing and Validation Methods

Lesson 49: Escape Sequences and String Formatting

Lesson 50: String Practical and Interview Programs

Module 8: Lists in Python Learn how to create, access, modify, organize, and process collections of data using Python lists, including indexing, slicing, list methods, nested lists, comprehensions, and practical programs.

Lesson 51: Introduction to Lists

Lesson 52: Accessing List Elements – Indexing

Lesson 53: List Slicing

Lesson 54: Adding Elements to a List

Lesson 55: Updating and Removing List Elements

Lesson 56: Important List Methods and Operations

Lesson 57: Sorting and Reversing Lists

Lesson 58: Nested Lists and Two-Dimensional Data

Lesson 59: List Comprehension

Lesson 60: List Practical and Interview Programs

Module 9: Tuples in Python Learn how to create, access, manipulate, and work with tuples in Python. This module covers tuple operations, methods, packing, unpacking, and practical applications.

Lesson 1: Introduction to Tuples

Lesson 2: Creating and Accessing Tuples

Lesson 3: Tuple Operations and Methods

Lesson 4: Tuple Packing and Unpacking

Lesson 5: Practical Programs Using Tuples

Module 10: Sets in Python Learn how to create and work with sets in Python. This module covers set properties, operations, methods, and practical applications for handling unique and unordered data.

Lesson 1: Introduction to Sets

Lesson 2: Creating and Accessing Sets