Master Python - From beginner to professional

Install Python with Anaconda and Jupyter Notebook, set up a code editor, and learn to download Windows, Mac, and Linux installers while choosing Visual Studio Code or PyCharm.

Explore the command line and the command line interface (cli); learn cross-platform navigation with cd, pwd, dir, and ls, and prepare to run Python scripts in the terminal.

Learn to install, open, and use Jupyter Notebook to write live Python code, visualize output, add equations and narrative text, and share notebooks with your audience.

Master Jupyter notebook basics by creating and running code and markdown cells, using command mode shortcuts, managing kernels, and exporting notebooks for Python learning.

Learn to write comments that the computer ignores using a hash symbol, and use the control and forward slash shortcut to comment or uncomment multiple lines.

Master the print function in Python to observe the computer's output. Use quotes and parentheses to display messages and prepare for dynamic output with variables.

Learn how to store and reference data with variables in python, using the equal sign to assign values like first_name, and practice changing variable values to see dynamic code behavior.

Learn how to use constants in Python, storing fixed values like pi and gravity, and naming them in uppercase. Discover using libraries for common constants rather than defining them.

Master Python covers Python keywords, which are reserved words you cannot use for variables or functions; 36 keywords exist in Python 3.9, case sensitive, always available without import.

Explore python's built-in data types and variables, including numbers, strings, booleans, lists, tuples, dictionaries, and sets, to build a strong foundation for future projects.

Explore using numbers in Python with integers and floating point numbers, check types with the type function, perform calculations, and apply the order of operations while using variables in expressions.

update variables efficiently using plus equals and other assignment operators, as shown with footsteps, and perform exponentiation with the double star syntax while converting numbers between int and float.

Explore how Python's floating point numbers rely on binary fractions, causing precision issues with numbers like 1.1 + 2.2, and learn how the decimal module enables high-precision calculations.

Explore the Python math module to access pi and perform factorial calculations, using import math and dot notation, and preview modules and packages for numeric tasks.

Explore strings as sequences of Unicode characters, learn encoding and decoding, and master string creation with single, double, and triple quotes, including escaping with backslashes, printing, and indexing.

Access string indexing and slicing to retrieve individual characters and ranges from strings, using len for length, zero-based and negative indexing, and common errors like out-of-range and type errors.

Master Python string slicing to access ranges using start and end indices (end not included) with an optional step, including negative indexing and reversing strings.

Strings are immutable; you cannot change individual characters or delete parts of a string. You can overwrite the variable with a new string or delete the variable with del.

Learn how to perform string concatenation in Python using the plus operator, literals, and line breaks, combine variables, and repeat strings with the star operator to build single, coherent outputs.

Master string membership in Python using the in and not in operators to test for characters or substrings within strings. Understand case sensitivity, booleans, and variables.

Explore string methods via dot notation on a string object, applying capitalize, count, find, and more. Compare index versus find behavior, and cleanse data with strip, lstrip, rstrip, and title.

Explore the Python format() method, using curly brace placeholders with positional and keyword arguments to format strings and reorder content. Learn to handle index errors, format numbers, and align output.

Explore how Python lists organize data with square brackets, supporting strings, numbers, booleans, and nested structures through practical examples like shopping lists and tic tac toe.

Access list elements with square bracket indexing, starting at zero, for simple and nested lists. Use negative indexing for from-the-end items and avoid out-of-range, non-integer errors.

Learn to slice lists in Python using start, end, and optional step values. Discover negative indexing and how to obtain sublists with clear, efficient code.

Explore list methods in Python, learn about mutable lists versus immutable strings, and practice adding, removing, and sorting list items using dot notation and method calls.

Sort lists with the sort method to modify the original list in place in ascending or descending order, or use the built-in sorted function to return a new sorted list.

Explore how to modify mutable lists in Python using the assignment operator, change a single element by index (the first item), or replace multiple items with slicing.

Master adding elements to lists in Python using plus concatenation, plus equals, append, extend, and insert, demonstrated with a shopping list and Tim's food.

Remove elements from a list using remove and pop in Python, targeting first occurrence or a specific index, while handling returns and potential index errors.

Learn how to delete items from a Python list using the del statement, by index or slice, and how to delete the whole list or clear it.

Explore practical list operations in python, including len for length, range for sequences, zip for pairing data, and index and count for search and tally.

Use the in operator to check if a value exists in a list, tuple, or string, and use not in for inverse checks in conditional logic.

Learn how to convert strings to lists and back in Python using split and join, including splitting on commas and spaces, and unpacking results into variables.

Master Python lists by applying powerful techniques to store data efficiently, access it in multiple ways, and use a range of list methods before moving to the next data structure.

explains how a Python dictionary stores data as key-value pairs, with keys as words and values as definitions or prices, and shows creating dictionaries with curly braces.

Define dictionaries with curly braces and key-value pairs, using immutable and unique keys. Create dictionaries from lists with zip and dict, and mix values like strings, numbers, and lists.

Learn how to access dictionary values using keys with square brackets and the get method. Explore handling missing keys with key errors versus None returns.

Discover how dictionaries are mutable and how to update existing keys or add new key-value pairs with the assignment operator, illustrated by bread and new items.

Remove items from dictionaries using pop, pop item, clear, and del; learn how values or tuples are returned, handle missing keys with a default, and preserve the dictionary for use.

Learn how to use dictionary methods to obtain all keys, all values, or all items from a dictionary, convert results to lists, and iterate over them.

Learn dictionary membership using in and not in to test keys, and explore built in functions like len, sorted, all, and any to analyze dictionary data.

Discover tuples in Python, an immutable data structure distinct from lists, and learn how to create an empty tuple, assign with parentheses, and check its type with type().

Create tuples by placing elements inside parentheses, separated by commas, mixing data types, and note that parentheses are optional for packing, with a trailing comma needed for single-element tuples.

master python's tuple handling by refreshing indexing and slicing: access elements with square brackets, use nested and negative indexing, and slice with start:end to extract ranges.

Explore how tuples are immutable yet can contain mutable lists, modify nested lists with indexing and the append method, and use concatenation and multiplication to create new tuples through reassignment.

Use del to delete the entire tuple; you cannot delete specific elements, and deleting the tuple makes the name undefined.

Explore immutable tuples and their two methods. See examples counting ones and finding first index, starting the search from a given position, and using in and not in for membership.

Learn to pack values into a Python tuple and unpack them into individual variables, handling matching element counts and unpacking errors to build flexible data handling.

Choose tuples for heterogeneous, immutable data to enable faster iteration and use as dictionary keys; prefer lists for homogeneous, mutable data to allow changes.

Discover what a set is: an unordered, unique collection of immutable elements; the set itself is mutable and supports adding, removing, and operations like union, intersection, and symmetric difference.

Learn how to create sets in Python with curly braces or the set() function. Understand that sets contain immutable items, avoid duplicates, and can include mixed data types.

Learn how sets differ from lists: they are mutable and unordered, with no indexing or slicing. Use add for a single element and update for multiple elements, duplicates removed.

Remove elements from a set using discard and remove, compare their error behavior, and use pop, clear, and del to manage and delete sets.

Learn set union in Python using the pipe operator or the union method to combine A (1 to 5) and B (4 to 8) into 1 to 8 without duplicates.

Learn set intersection in Python by using the ampersand operator or the intersection method to obtain shared elements, like 4 and 5 from sets A and B.

Explore the set difference operation in Python to get items unique to one set relative to another, using minus operator and the difference method for A or B.

Explore symmetric difference, returning items in either set a or b but not shared values, using the carrot operator or symmetric_difference method; results are the same regardless of order.

Explore built-in functions for sets, such as len, max, min, sorted, and sum, and perform membership tests with in and not in.

Explore frozen sets, counterparts to sets with unique values that cannot change elements; they can be dictionary keys and support union, intersection, difference, and symmetric difference, with order affecting results.

Explore Python control flow by using boolean expressions and relational operators to guide program decisions, evaluating conditions from top to bottom and executing corresponding code.

Learn how boolean values work in Python, including the bool type, true and false as reserved keywords, and creating boolean variables by assignment and evaluating boolean expressions.

Compare values using operators such as equals, not equals, greater than, less than, and their inclusive forms; observe how types and case sensitivity affect boolean results and conditional code.

Learn how to use Python if statements with boolean expressions and variables, apply and, or, not operators, and build conditional logic for real-world scenarios.

Learn why indentation matters in Python, where leading whitespace defines code blocks and guides control flow, with best practices like four spaces and no mixed tabs.

Learn to implement conditional statements in Python using if, elif, and else, with real examples like awarding scores and updating lists with append.