Python Programming for Beginners with Python Coding Examples

Learn Python's basic syntax, including indentation, colons, and blocks; use comments, strings, and variables correctly; and understand reserved words and common keywords for clear, maintainable code.

Discover how Python variables store data, use the assignment operator, and manipulate types with arithmetic, comparison, logical, membership, and identity operations.

Explore Python data types such as integers, floats, strings, booleans, lists, tuples, sets, dictionaries, and None, and learn how to convert between them with built-in typecasting and mutable-immutable behavior.

Learn to set up and use Google Colab to write and run Python code in a browser, mount Google Drive, access GPU resources, and share notebooks.

Explore capturing user input with Python’s input function and displaying output via print, using strings, variables, formatting, and type conversions to int, float, bool, complex, list, tuple, and set.

Explore Python control structures, focusing on if else statements, elif, and logical operators, and learn how for and while loops manage iteration with conditional decisions.

Learn how to use for loops in Python to iterate over lists, tuples, dictionaries, and strings, then apply range, enumerate, zip, and reverse for practical data processing.

Learn python while loops using simple syntax and conditions. Use count-controlled, event-controlled, and infinite loops with break and continue, illustrated with i as a counter and user input.

Explore how data structures organize and store data in memory for efficient access and manipulation, focusing on Python's built-in lists, tuples, sets, dictionaries, and strings.

Explore the list data structure in Python, a mutable built-in sequence with square-bracket syntax. Learn indexing, slicing, appending, inserting, removing, concatenating, and list comprehensions to store and manipulate data.

Explore the tuple data structure in Python, an immutable, ordered collection defined with parentheses. Learn indexing, slicing, concatenation, repetition, membership, unpacking, and practical uses like inventory calculations.

Learn set data structures in Python, define sets with curly braces, and store unique elements. Master union, intersection, and difference, plus add, remove, and membership checks.

Explore the Python dictionary data structure, mastering key-value pairs, creation, access, update, deletion, and iteration; apply it to json objects, configuration options, and fast lookups.

Explore strings as a Python data structure and learn common operations from creating literals with quotes, indexing and slicing, formatting, case changes, stripping, to splitting and replacing text.

Define user defined functions in Python with def and optional parameters and return values. Explore recursive functions with base cases like factorial and generator functions using yield for Fibonacci sequences.

Demonstrates built-in Python functions like range, enumerate, zip, map, filter, and reduce, with practical examples on lists, tuples, and strings.

Defines anonymous functions in Python with lambda for one-line, unnamed operations. Shows assigning and calling these functions and sorting dictionaries by age with a lambda key.

Explore Python functions through hands-on coding examples, including return values, parameter types (positional, keyword, default, variable-length), lambdas, generators, and map and filter usage, plus a library book management exercise.

Explore exception handling in Python by using try-except-else-finally, raising custom exceptions, and leveraging with statements to manage resources and provide user-friendly error messages.

Explore file handling in Python by reading and writing text, CSV, and JSON files, and learn to copy, move, and delete files.

Learn how to read sales data from a text file in Python, multiply quantity sold by price to compute revenue per product, and write the results to revenue.txt.

Utilize Python's csv module to read and write csv files with csv.reader, csv.DictReader, csv.DictWriter; update salaries by a percentage and write back the updated data.

Master reading and writing JSON in Python using JSON dumps, JSON loads, JSON dump, and JSON load, with indentation and sort keys, and a real estate properties example.