Python for Complete Beginners

Install Python with the free individual Anaconda distribution to get Python and Jupyter Notebook in a beginner-friendly development environment across Windows, macOS, and Linux.

We provide a quick overview of Python data types, including integers, floating point numbers, strings, lists, tuples, dictionaries, sets, and booleans, with notes on short keywords like int and str.

Explore Python variable naming rules: no leading numbers, no spaces, underscores allowed, and avoid keywords, lowercase. See dynamic typing, reassignment across types, and using type() to inspect integers and floats.

Explore Python strings as ordered sequences of characters, using single or double quotes, zero-based and negative indexing, slicing, printing, escape sequences, and measuring length with len.

In this lecture, students learn string indexing and slicing in Python, using a text variable to demonstrate positive and negative indexing, slicing with start, stop, and step, and reverse indexing.

Explore string concatenation and formatting in Python, learn string methods like upper, lower, and split, understand immutability, and master f-strings for variable interpolation.

Explore Python lists as mutable, ordered sequences that hold diverse objects, with indexing, slicing, and concatenation. Learn append, pop, reverse, sort, and length using len.

Learn what tuples are in Python, that they are immutable unlike lists, and how to create, index, slice, and use count and index methods.

Explore booleans, how true and false determine code execution, and how comparison operators return boolean values. Then dive into sets as unordered collections of unique elements with add operations.

Master Python comparison operators to test equality, inequality, and order for numbers and strings, noting case sensitivity. Understand chaining with and, or, and not to handle booleans across types.

Master Python control flow with if, elif, and else statements, using conditions, indentation, and multiple branches to decide printed outputs like charging, food orders, and cat names.

Explore Python list comprehension, a concise one-line alternative to for loops and append, with examples from strings, ranges, nested loops, and a note on readability.

Master the Python function basics: define with def, name in lowercase with underscores, call with parentheses, pass parameters, and use return to produce values rather than print.

Explore how to combine logic statements with functions in Python, build an is_even checker, filter even numbers from lists, and return and unpack multiple values with tuple unpacking.

Develop a cups game by combining Python functions to shuffle a four-cup list, obtain a user guess of an index, and check if the $100 is revealed.

Learn to define functions with *args and **kwargs to accept arbitrary positional and keyword inputs. See how *args yields a tuple and **kwargs yields dictionary, with positional before keyword arguments.

Explore map and filter functions in Python by applying a percentage function to a value list, mapping results, and filtering even numbers to demonstrate practical use.

Explore lambda expressions as anonymous functions used with map and filter to transform data, including a 30 percent discount example, and learn when to prefer lambdas over named functions.

Explore Python's variable scope by tracing local, enclosing, global, and built-in scopes through examples of global variables, nested functions, and safe reassignment via returning values.

Learn to define a user-defined class in Python, create instances, and use a constructor to set attributes such as brand, color, and price.

Explore how methods operate inside classes, how to call them with parentheses, and how to pass parameters like a serial number, using examples from a car and BMI class.

Learn inheritance and polymorphism in Python by deriving car and truck from a machine. Reuse and override methods like drive and machine type, and use abstract classes to enforce implementation.

Discover how special methods in Python integrate custom objects with built-in operations, using __init__, __str__, __del__, and __len__ to manage creation, string representation, deletion, and length for a software class.