1
Introduction to Python
Get started with Python programming. Learn about Python history, features, installation, and write your first Python program.
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Learning objectives:
• Understand Python features and advantages
• Install and configure Python development environment
• Write and run your first Python program
• Understand Python syntax and indentation rules
2
Python Fundamentals: Variables, Data Types, and Operators
Master the building blocks of Python programming. Learn about data types, variables, type conversion, and various operators.
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Learning objectives:
• Understand Python data types (int, float, str, bool)
• Declare and use variables
• Perform type conversion and casting
• Use arithmetic, comparison, logical, and assignment operators
3
Data Structures: Lists, Tuples, Sets, and Dictionaries
Work with Python built-in data structures. Learn list, tuple, set, and dictionary operations and methods.
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Learning objectives:
• Create and manipulate lists, tuples, sets, and dictionaries
• Understand mutability and immutability
• Use built-in methods for data structures
• Perform common operations on collections
4
Control Flow: Conditionals and Loops
Learn to control program flow using conditional statements and loops. Master if-elif-else, for loops, while loops, and loop control statements.
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Learning objectives:
• Use if-elif-else statements for decision making
• Implement for and while loops
• Understand break, continue, and pass statements
• Handle nested control structures
5
Functions and Modules
Learn to create reusable code with functions and modules. Understand function definition, parameters, return values, and module organization.
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Learning objectives:
• Define and call functions
• Understand function parameters and arguments
• Use default arguments, *args, and **kwargs
• Create and import modules
• Understand scope and namespace
6
Object-Oriented Programming in Python
Dive into object-oriented programming in Python. Learn to create classes, instantiate objects, understand constructors, methods, and inheritance.
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Learning objectives:
• Create classes and objects
• Understand __init__ method and constructors
• Use instance methods, class methods, and static methods
• Implement inheritance and method overriding
7
Advanced OOP: Magic Methods, Properties, and Decorators
Explore advanced object-oriented concepts including magic methods, properties, and decorators.
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Learning objectives:
• Understand magic methods (__str__, __repr__, etc.)
• Use properties and property decorators
• Create and use decorators
• Understand method resolution order
8
Exception Handling and File I/O
Master exception handling and file operations in Python. Learn try-except blocks, custom exceptions, and file reading/writing.
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Learning objectives:
• Handle exceptions using try-except-finally
• Raise and create custom exceptions
• Read from and write to files
• Work with different file modes
9
Working with Strings and Regular Expressions
Master string manipulation and pattern matching using regular expressions in Python.
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Learning objectives:
• Perform string operations and formatting
• Use string methods effectively
• Understand and use regular expressions
• Match and search patterns in text
10
Advanced Topics: Generators, Iterators, and Comprehensions
Explore advanced Python features including generators, iterators, list comprehensions, and generator expressions.
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Learning objectives:
• Understand iterators and iterables
• Create generators using yield
• Use list, dictionary, and set comprehensions
• Understand generator expressions
11
Python Mini Project Studio
Learn how to translate fresh concepts into tightly scoped Python mini projects for fast validation.
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Learning objectives:
• Break a concept into a project brief with Python-first constraints
• Select the right tooling (virtualenv, pytest, formatting) for quick builds
• Capture insights and feedback loops at each milestone
12
Python End-to-End Delivery Blueprint
Design, implement, and ship production-ready Python systems that span API, background work, and deployment.
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Learning objectives:
• Model services with FastAPI/Django plus async workers (Celery/RQ)
• Package code with type checking, linting, and layered testing
• Automate delivery using CI/CD, container images, and observability hooks
13
Python Interview Readiness Lab
Master Python-focused interview loops covering algorithms, system design, and behavioral storytelling.
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Learning objectives:
• Create reusable approaches for DSA prompts using Python idioms
• Discuss system designs referencing async, scaling, and packaging choices
• Tell outcome-driven stories that highlight collaboration and impact