Python for Absolute Beginners to Advanced

About Course

Unlock the power of Python from scratch to mastery with our Python for Absolute Beginners to Advanced online training. This comprehensive course is designed to transform you into a confident Python programmer, whether you are completely new to coding or looking to advance your Python skills for data science, web development, automation, or career growth.

The training starts with Python basics like syntax, variables, data types, and control structures, gradually moving to advanced concepts including object-oriented programming, file handling, modules, libraries, and real-world project development. You will gain practical hands-on experience through coding exercises, quizzes, and mini-projects, ensuring you understand not just the “how” but also the “why” behind each concept.

By the end of this course, you will be equipped with the skills needed to build Python applications, automate daily tasks, prepare for technical interviews, and confidently step into roles requiring Python programming

How to set up Python and write your first programs confidently
Understanding Python syntax, variables, data types, and operators
Using conditional statements and loops for program flow control
Writing reusable code with functions and handling exceptions
Working with lists, tuples, sets, and dictionaries in Python
Reading and writing files including text, CSV, and JSON formats
Applying object-oriented programming concepts in Python
Performing data analysis with Pandas and basic data visualization with Matplotlib
Web scraping fundamentals using Python for real-world data extraction
Automating repetitive tasks using Python scripting
Interacting with APIs and parsing JSON data for projects
Building small real-world projects to strengthen your skills
Following Python best practices and writing clean, readable code
Gaining exposure to advanced topics like GUI basics, web development frameworks, and an introduction to machine learning with Python

Course Content

Module 1: Introduction to Python
What is Python? History and Use Cases Installing Python and IDEs (Anaconda, VS Code, PyCharm) Writing your first Python program Using the Python interpreter and scripts

Module 2: Python Basics
Variables, Data Types, and Type Conversion Operators (Arithmetic, Logical, Comparison) User Input and Output Basic string manipulation and formatting

Module 3: Control Structures
Conditional Statements: if, elif, else Loops: while, for, nested loops Loop control statements: break, continue, pass List and dictionary comprehensions

Module 4: Functions in Python
Defining and calling functions Arguments, keyword arguments, and return values Lambda functions Built-in functions vs. user-defined functions Scope and lifetime of variables

Module 5: Data Structures
Lists: creation, methods, slicing Tuples and Sets Dictionaries: creation, methods, iteration Working with nested data structures

Module 6: File Handling
Reading and writing files (text, CSV, JSON) Handling file exceptions Practical file handling mini-projects

Module 7: Error and Exception Handling
Types of errors Try, Except, Else, Finally blocks Raising exceptions Custom exception handling

Module 8: Object-Oriented Programming in Python
Classes and Objects Constructors and destructors Instance and class variables Inheritance and polymorphism Encapsulation and abstraction

Module 9: Python Libraries for Data Handling
Introduction to NumPy Introduction to Pandas Basic data analysis with Pandas Data visualization with Matplotlib (basic plotting)

Module 10: Web Scraping with Python
Introduction to web scraping Using requests and BeautifulSoup Extracting and parsing web data Practical scraping mini-project

Module 11: Automation with Python
Automating repetitive tasks Using Python for Excel and PDF handling Sending automated emails with Python

Module 12: Working with APIs
Understanding APIs and JSON Making API requests with Python Handling API responses Building a simple project using a public API

Module 13: Real-World Mini Projects
Building a weather app with API Basic CRUD app using file handling Automation script (file renamer or email sender) Data analysis mini-project with Pandas

Module 14: Advanced Topics (Optional Add-On)
Introduction to GUI with Tkinter Introduction to Django/Flask for web development Introduction to machine learning with scikit-learn

Module 15: Best Practices and Next Steps
Writing clean, readable Python code (PEP 8) Virtual environments and package management (pip, conda) Version control with Git basics Career paths with Python (Web Dev, Data Science, Automation) Final Q&A and certificate issuance

Python for Absolute Beginners to Advanced

About Course

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What Will You Learn?

Course Content

Module 1: Introduction to Python
What is Python? History and Use Cases Installing Python and IDEs (Anaconda, VS Code, PyCharm) Writing your first Python program Using the Python interpreter and scripts

Module 2: Python Basics
Variables, Data Types, and Type Conversion Operators (Arithmetic, Logical, Comparison) User Input and Output Basic string manipulation and formatting

Module 3: Control Structures
Conditional Statements: if, elif, else Loops: while, for, nested loops Loop control statements: break, continue, pass List and dictionary comprehensions

Module 4: Functions in Python
Defining and calling functions Arguments, keyword arguments, and return values Lambda functions Built-in functions vs. user-defined functions Scope and lifetime of variables

Module 5: Data Structures
Lists: creation, methods, slicing Tuples and Sets Dictionaries: creation, methods, iteration Working with nested data structures

Module 6: File Handling
Reading and writing files (text, CSV, JSON) Handling file exceptions Practical file handling mini-projects

Module 7: Error and Exception Handling
Types of errors Try, Except, Else, Finally blocks Raising exceptions Custom exception handling

Module 8: Object-Oriented Programming in Python
Classes and Objects Constructors and destructors Instance and class variables Inheritance and polymorphism Encapsulation and abstraction

Module 9: Python Libraries for Data Handling
Introduction to NumPy Introduction to Pandas Basic data analysis with Pandas Data visualization with Matplotlib (basic plotting)

Module 10: Web Scraping with Python
Introduction to web scraping Using requests and BeautifulSoup Extracting and parsing web data Practical scraping mini-project

Module 11: Automation with Python
Automating repetitive tasks Using Python for Excel and PDF handling Sending automated emails with Python

Module 12: Working with APIs
Understanding APIs and JSON Making API requests with Python Handling API responses Building a simple project using a public API

Module 13: Real-World Mini Projects
Building a weather app with API Basic CRUD app using file handling Automation script (file renamer or email sender) Data analysis mini-project with Pandas

Module 14: Advanced Topics (Optional Add-On)
Introduction to GUI with Tkinter Introduction to Django/Flask for web development Introduction to machine learning with scikit-learn

Module 15: Best Practices and Next Steps
Writing clean, readable Python code (PEP 8) Virtual environments and package management (pip, conda) Version control with Git basics Career paths with Python (Web Dev, Data Science, Automation) Final Q&A and certificate issuance

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What Will You Learn?

Course Content

Module 1: Introduction to Python What is Python? History and Use Cases Installing Python and IDEs (Anaconda, VS Code, PyCharm) Writing your first Python program Using the Python interpreter and scripts

Module 2: Python Basics Variables, Data Types, and Type Conversion Operators (Arithmetic, Logical, Comparison) User Input and Output Basic string manipulation and formatting

Module 3: Control Structures Conditional Statements: if, elif, else Loops: while, for, nested loops Loop control statements: break, continue, pass List and dictionary comprehensions

Module 4: Functions in Python Defining and calling functions Arguments, keyword arguments, and return values Lambda functions Built-in functions vs. user-defined functions Scope and lifetime of variables

Module 5: Data Structures Lists: creation, methods, slicing Tuples and Sets Dictionaries: creation, methods, iteration Working with nested data structures

Module 6: File Handling Reading and writing files (text, CSV, JSON) Handling file exceptions Practical file handling mini-projects

Module 7: Error and Exception Handling Types of errors Try, Except, Else, Finally blocks Raising exceptions Custom exception handling

Module 8: Object-Oriented Programming in Python Classes and Objects Constructors and destructors Instance and class variables Inheritance and polymorphism Encapsulation and abstraction

Module 9: Python Libraries for Data Handling Introduction to NumPy Introduction to Pandas Basic data analysis with Pandas Data visualization with Matplotlib (basic plotting)

Module 10: Web Scraping with Python Introduction to web scraping Using requests and BeautifulSoup Extracting and parsing web data Practical scraping mini-project

Module 11: Automation with Python Automating repetitive tasks Using Python for Excel and PDF handling Sending automated emails with Python

Module 12: Working with APIs Understanding APIs and JSON Making API requests with Python Handling API responses Building a simple project using a public API

Module 13: Real-World Mini Projects Building a weather app with API Basic CRUD app using file handling Automation script (file renamer or email sender) Data analysis mini-project with Pandas

Module 14: Advanced Topics (Optional Add-On) Introduction to GUI with Tkinter Introduction to Django/Flask for web development Introduction to machine learning with scikit-learn

Module 15: Best Practices and Next Steps Writing clean, readable Python code (PEP 8) Virtual environments and package management (pip, conda) Version control with Git basics Career paths with Python (Web Dev, Data Science, Automation) Final Q&A and certificate issuance

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Categories

Module 1: Introduction to Python
What is Python? History and Use Cases Installing Python and IDEs (Anaconda, VS Code, PyCharm) Writing your first Python program Using the Python interpreter and scripts

Module 2: Python Basics
Variables, Data Types, and Type Conversion Operators (Arithmetic, Logical, Comparison) User Input and Output Basic string manipulation and formatting

Module 3: Control Structures
Conditional Statements: if, elif, else Loops: while, for, nested loops Loop control statements: break, continue, pass List and dictionary comprehensions

Module 4: Functions in Python
Defining and calling functions Arguments, keyword arguments, and return values Lambda functions Built-in functions vs. user-defined functions Scope and lifetime of variables

Module 5: Data Structures
Lists: creation, methods, slicing Tuples and Sets Dictionaries: creation, methods, iteration Working with nested data structures

Module 6: File Handling
Reading and writing files (text, CSV, JSON) Handling file exceptions Practical file handling mini-projects

Module 7: Error and Exception Handling
Types of errors Try, Except, Else, Finally blocks Raising exceptions Custom exception handling

Module 8: Object-Oriented Programming in Python
Classes and Objects Constructors and destructors Instance and class variables Inheritance and polymorphism Encapsulation and abstraction

Module 9: Python Libraries for Data Handling
Introduction to NumPy Introduction to Pandas Basic data analysis with Pandas Data visualization with Matplotlib (basic plotting)

Module 10: Web Scraping with Python
Introduction to web scraping Using requests and BeautifulSoup Extracting and parsing web data Practical scraping mini-project

Module 11: Automation with Python
Automating repetitive tasks Using Python for Excel and PDF handling Sending automated emails with Python

Module 12: Working with APIs
Understanding APIs and JSON Making API requests with Python Handling API responses Building a simple project using a public API

Module 13: Real-World Mini Projects
Building a weather app with API Basic CRUD app using file handling Automation script (file renamer or email sender) Data analysis mini-project with Pandas

Module 14: Advanced Topics (Optional Add-On)
Introduction to GUI with Tkinter Introduction to Django/Flask for web development Introduction to machine learning with scikit-learn

Module 15: Best Practices and Next Steps
Writing clean, readable Python code (PEP 8) Virtual environments and package management (pip, conda) Version control with Git basics Career paths with Python (Web Dev, Data Science, Automation) Final Q&A and certificate issuance