Introduction to Programming: Python

Explains python enhancement proposals and the zen of python, highlighting docstring conventions, naming, whitespace, line length, pep8 style, and namespaces for readable code.

Explore boolean expressions, true or false results, and how conditional statements use them. Learn Python's comparison operators, if, elif, and else, plus simple compound conditions with and, or, not.

Learn to chain and nest conditional statements in Python using and and or logic operators. See age-based examples and focus on readability, with if, elif, else and nested conditions.

Explore loops in Python by using while and for constructs, learn range behavior and the in keyword, and master break and continue to control iteration, including step sizes.

Explore functions in Python from simple f(x)=3x to printing hello world, defaults, and keyword arguments. Learn recursion with factorial and summation, using loops, math library, and recursive definitions.

Explore Python's standard library and pip, learn to use math, os, urllib, and turtle modules, and install plotting libraries like matplotlib and NumPy with pip.

Learn how Python handles built-in lists, indexing from zero, and common operations like len, range, list construction, and methods such as append, insert, pop, sort, and copy.

Explore slicing lists, build two-dimensional matrices with lists of lists, and print and traverse them, using start, stop, step indices and negative indexing, with numpy for readability.

Explore Python's built-in dictionaries, a key-value data structure, and learn to create maps, access values by keys, and use methods like keys, values, items, get, and pop.

Explore how Python tuples bundle multiple values and support unpacking into variables, including returning multiple values from functions and using an asterisk to handle extra items.

Explore the itertools library for iterator algebra, including count, cycle, product, permutations, and combinations, with practical examples of finite and infinite iterators.

Discover how Python sets remove duplicates, perform unions and intersections, and apply set concepts to strings and range-based sets for data science.

Explore Python's random number generation and data science tools, including random between bounds, random choice, and seeds; apply NumPy, SciPy, and SymPy to calculus, fast Fourier transform, integration, and optimization.

Explore how Python handles errors by introducing exceptions, raising and catching them, and using common types like type errors, value errors, and syntax errors to enforce input validity.

Learn how Python's try-except-finally constructs catch errors, handle name errors and other exceptions, and use else and finally to keep apps stable.

Explore how assertions provide sanity checks and unit testing to ensure code returns the intended results. See practical examples and error handling, including how graders use assertions to verify programs.

Explore python file I/O by opening files in read, write, append, and read/write modes; learn to seek, read, readline, readlines, and safely close files.

Explore list comprehensions and the ternary operator in Python, using colors as examples and showing how to create, filter, and apply data frames in Pandas in one line.

Explore character matching with Python's regular expressions using the Alice in Wonderland text, learning case sensitivity, anchors, and quantifiers like dot, star, and plus.

Learn data extraction with regular expressions in Python, combining searching and extracting to pull emails from an email conversation file using find all and search.

Explore the escape character in regular expressions, use the backslash to match special characters like the dollar sign, and simulate grep to search files with Python.

Explore object oriented programming with classes, constructors, and instantiation to model points and rectangles, and compute area, perimeter, and volume.

Learn how to define public and private class properties, use the property function to manage access, and import modules and classes for reuse in Python.

Learn data hiding with private attributes and double underscores, and use dunder methods to overload operators, customize string output, and understand object lifecycle and garbage collection.

Explore inheritance in object oriented programming by building parent and child classes, using super, overriding methods, and distinguishing abstract classes and interfaces to structure reusable code.

Discover how class methods bind to the class, not the object, and how static methods bind to the class; class methods access class state, while static methods do not.

Learn to build a basic Python GUI with Tkinter, create a simple area and perimeter calculator, and explore widgets, grid layout, and event-driven updates.

Explore the core ideas of functional programming in Python, including recursion, first-class and higher-order functions, and immutability. See how functions can be passed, stored, and returned.

Explore anonymous functions and lambda expressions in Python, learn one-line function definitions, purity vs impure behavior, and how map and filter leverage these concepts.

Explore iterators, generators, and decorators in Python, using yield and next to control data flow, create custom iterables, and apply decorators that wrap functions for added behavior.

Explore higher-order functions in Python by applying functions to lists with map, filter, and lambdas. See how map transforms elements and how filter selects items.

Master Python's reduce to collapse a list into a single value using lambda or named functions, with sum and product examples and an optional initial value.

Learn how to pass a variable number of arguments in Python with *args and **kwargs, using sums, for loops, and keyword dictionaries to handle non keyword and keyword arguments.