The Complete Python 3 Masterclass - From Beginner To Pro

Explore Python basics, including numbers, variables, and lists, and learn to convert data types while visualizing concepts with graphics and hands-on coding.

Learn to work with numbers in Python by printing integers and decimals, performing basic arithmetic like 5+4, and evaluating expressions such as 5/4.

Learn how to use variables in Python within a Jupyter notebook, including assignment, printing, and simple calculations, then compute averages with multiple variables.

Explore strings in Python by creating string literals, concatenating them with variables, resolving type errors when mixing strings and integers, and converting numbers to strings.

Evaluate a four-question Python quiz to distinguish string and number types, including casting numbers to strings and proper concatenation. Learn through step-by-step explanations to identify the correct working code.

Explore lists in Python by building and manipulating student records, accessing items with zero-based indices, and using len and append to manage and average marks.

Learn how to work with lists in Python: define lists with square brackets and commas, access the third element using zero-based indexing, and use append to add items.

Master how the pop function removes the last list item, returns it, and how to store and print the popped value to illustrate last-in, first-out behavior.

Learn data conversion in Python by turning strings into integers with int() and floats with float(), fix concatenation versus addition, handle user input, and convert numbers to strings with str().

Master data conversion with lists by turning lists into strings and strings into lists using join and split, with comma and space separators and length checks.

Explore how Python comments work using hash symbols. Predict which lines print when mixed with commented and uncommented print statements in a short quiz.

Explore Python basics through a hands-on trick, performing arithmetic operations, converting results to integers, and printing formatted outputs. Build a simple email-based name extractor with split, join, and list operations.

Master Python if statements and else blocks by writing conditions, indent blocks, and handle multiple cases with elif and else, using comparison operators.

Explore how Python's comparison operators evaluate booleans, using examples like less than, greater than, equal, and not equal, with booleans and string content comparisons guiding if statements.

Explore Python boolean logic with and/or operators and the in operator, evaluate conditions, and practice quizzes on print statements and age checks for contracts.

learn how the not operator negates conditions and how not in checks handle list membership, using age less than 30 and Moe not in names.

Use elif to replace nested else-if chains when checking currencies like dollar, yen, euro, and Thai baht, printing the match and improving readability; only the first true branch executes.

Master how the while loop repeats code while a condition stays true, updates a counter to avoid infinite loops, and uses indentation to define the loop body.

Learn how to use python for loops with ranges and lists, iterating values such as 0–9 and 5, 8, 10, and decide when to use for loops versus while loops.

Master Python basics through quiz tasks on list membership with the in operator, the elif form, and counting a for loop with range 1 to 9, and while loop termination.

Explore Python loops with for range 0 to 10 and learn break and continue, including how continue skips iterations and break exits the loop, illustrated by a weight-check elevator example.

Learn how to handle errors by diagnosing origins such as version, browser, or environment, debug effectively, search Stack Overflow, and apply quick fixes like casting types or restarting.

Build a Python random Trump tweet bot by composing four phrase parts with lists and the random module, join the parts into one line, and extend it in upcoming lessons.

Explore how functions combine code for efficiency, readability, and reusability, enabling you to split programs into logical blocks and reuse functionality across projects.

Learn to define and call Python functions with def, pass parameters, and pass arguments, enabling reusable code for tasks like printing messages and handling simple errors.

Explore functions with multiple parameters and return values, including calling one function from another, and using return to output the greater of two values with practical examples.

Explore objects in Python by creating lists, printing them, and appending items. Understand how variables act as objects, how classes define behavior, and how strings are split.

Open, read, and write files in Python to persist data across sessions, using CSV for tabular data like attendance lists.

Open a file in read mode in a jupiter notebook, read each line, print them, and use strip to remove trailing line breaks.

Learn to write files in Python by opening a file in write mode, writing text, closing the file, using line breaks, and appending or writing lists with a for loop.

Learn how the with keyword in Python simplifies file handling by opening files as a context manager, ensuring automatic closure and preventing unclosed files while improving safety and resources.

Learn to open and read CSV files in Python, handle semicolon-separated values and line breaks, extract city names and populations, and present data in a clean tabular format.

Draw graphics in Python by importing a plotting library, configuring inline plots in Jupyter, and plotting x and y coordinates to visualize data such as birth statistics from CSV input.

Open a jupiter notebook, load the birth names dataset, parse lines into name, year, state, and gender, then build x and y values to graph birth statistics with Matplotlib.

Practice counting how many mxs were given as male first names in California from 1950 through 2000 using Python, handling string to int conversion and header rows.

Read and parse a data file in Python, split lines by comma, and filter by year 1950–2000, male gender, and California to count occurrences of the name Max.

Learn how to modify a Python list in place by iterating over indices, and understand why '==' compares and '=' assigns when changing list elements.

Learn to work with lists in Python by creating lists, using pop to remove the last item, append to add elements, del to delete by index, and remove by value.

Master list slicing in Python by using negative and positive indices to extract sublists and strings, learn about exclusive end, and apply to examples like hello world.

Explore Python slicing for strings and lists, using negative indices and single-character access with brackets, and learn to predict outputs for sample quiz problems.

Explore list comprehension in Python to transform lists, generating new lists like y by multiplying x by itself, and visualize results with Matplotlib.

Explore tuples and dictionaries in Python to group data and return multiple values, and compare them with lists to map names to phone numbers effectively.

Learn how to pack and unpack tuples in Python, return tuples from functions, and iterate over lists of tuples to access names, ages, and subjects.

Count how often each first name occurs by reading data into a dictionary, then analyze to find the most common name using loops and dictionaries.

Explore how to use dictionaries and loops in Python to count word occurrences, track frequencies, and identify the most common name in a list.

Learn to build and update a names dictionary from a file using loops and splits, skip the header, count occurrences, and find the most frequent name.

Learn to nest lists in Python, create lists within lists to model data like cities, access elements with indices, and use dictionaries with immutable keys to organize students by subject.

Explore the basics of object oriented programming and why a class serves as a blueprint to organize data and functions. Build your first class and objects to model a student.

Implement constructors in Python using __init__ to ensure every student object has a first name and last name. Add an increase_term method to manage semesters.

Explore how visibility of methods and variables controls access in programming, using a supermarket analogy to show private attributes and encapsulation.

Learn how private properties and methods enforce access control in object-oriented Python, using single and double underscores, and exposing values via getters.

Explore encapsulation to protect data by keeping phone book entries private and exposing add and get methods, enabling stable usage even when storage changes.

Implement and override Python's special methods—__str__, __repr__, and __len__—to customize a phonebook object's string display, detailed repr, and length.

Learn inheritance in Python by building a student and a working student, using super to share initialization, overriding methods, and applying polymorphism to manage mixed class instances.

Practice inheritance and object orientation by building a file reader that reads lines into a list, then extend to a csv reader returning a multidimensional list via overridden lines.

Practice inheritance and object-oriented design by extending a file reader to read a csv-like file into a multi-dimensional list, using constructors, super calls, line stripping, and comma-based splitting.

Learn to check variable types in Python with type and isinstance using student and working student classes, and see how inheritance affects type checks.

Explore how Python treats everything as an object, inspect int and float types with type, and see how operations rely on object methods like __add__ and __len__.

This video explains Python naming conventions, using Pascal case for classes, sneek case for functions, methods, and variables, and keeping multi-word names to three words for readability.

Explore static variables in Python, bind them to the class rather than instances, and see how changing a static price affects all car objects, unlike instance-level attributes.

Learn to split a single-file code into modules for scalable Python projects, load and reuse modules, and import module files, including a Python module named C as V.

Create a module file named hello.py, import it, and reuse code across your project; use from hello import world and Mars to call functions.

Learn how to create modules in a folder, mark it with __init__.py, and choose between importing a single module, importing all from the package, or importing individual files.

This lecture reviews Python module imports and function access, covering import, from import, pandas usage, and aliasing modules to call functions like read_csv efficiently.

Explores using the Python module index to select versions, imports the csv module, and demonstrates reading csv files with delimiters and quote character handling, with practical examples.

Learn how HTML structures a web page using opening and closing tags, including p, head, and body. Explore creating an index.html file, viewing source, and applying CSS or meta information.

Fetch web pages with the python requests module using get, inspect status codes, headers, and html text, and learn to extract and reformat data for display.

Learn to use Beautiful Soup to parse HTML, extract paragraph text with find_all, and inspect tag attributes to filter content.

Explore CSS selectors by building and styling a simple page, using classes and IDs to target elements, apply colors, and differentiate specific paragraphs.

Explore how div containers group elements, apply class selectors like part 1 and part 2, and use style tags and dot notation to bold specific text.

Learn how to convert relative image links to absolute URLs in Python by using urllib.parse.urljoin, and apply it to fetch and store complete image URLs.

Practice crawling multiple pages by scripting a paginated fetch with time.sleep to avoid overloading servers, using urljoin and navigation class anchors to follow next-page links until no button remains.

Master crawling multiple pages by locating the next page link through the navigation button, extracting the href, looping until no next button, and collecting article data.

Export articles to CSV using a CSV writer, save the file in the notebook, and use a semicolon separator with double quotes for Excel compatibility.

Export article data to a csv file using a csv writer with a semicolon delimiter and quote characters, writing rows for emoji, title, image, and content, viewable in Excel.

Discover how generators in Python yield values on the fly, avoiding full list creation and enabling a crawler to display only the first few articles as needed.

Use generators with a crawler to yield articles as they are crawled, avoiding fetching all pages. This approach improves efficiency by stopping after a number of entries and reducing traffic.

install PyCharm community edition, set up a Python project with an Anaconda interpreter, and create a crawler project, configuring themes, plugins, and package indexing for a functional program.

Migrate a crawler from Jupiter notebooks to Python in PyCharm and build a Python package with article fetcher.