Python Beginners to Advance Bootcamp

Explore Python conditional statements with real-world login demos, using if, else, elif, and nested conditions to validate credentials and guide user flow.

Explore Python conditional statements through practical exercises, including finding the minimum of three numbers and building an ATM menu using if, elif, and else.

Explore how Python modules group reusable code, distinguishing built-in and external packages. Import tools like math, random, and date time, and use pip to install external modules.

Learn how to use pip in Python to install and manage external packages from PyPI, including FastAPI, in real projects and environments.

Master while loops in Python: syntax, conditions, and counter updates, compare manual repetition with automated looping, and explore examples like printing names and multiplication tables with for loops.

Build a guessing game in Python using a while loop, a random jackpot number, and user input to guess higher or lower until the guess matches, tracking attempts.

Explore for loops in Python, understand the range function, iterate over numbers, strings, lists, and tuples, and apply a ten-year population projection as a practical exercise.

Master nested for loops in Python, exploring outer and inner loops through category and product examples. Build patterns and unique pairs with loops and stars, reinforcing execution order.

Learn loop control in Python with break, continue, and pass. See practical for loop examples, including breaking at a condition, skipping iterations, and using pass for templates.

Explore strings in Python, covering creation with single, double, and triple quotes, Unicode concepts, and multi-line strings. Learn indexing, slicing, immutability, and reversing strings for practical data processing.

Explore string operations in Python, including concatenation with the plus operator, repetition via multiplication, relational and logical comparisons, looping over strings, and membership tests.

Discover Python string methods, from common functions like len and max to inbuilt string methods such as capitalize, title, upper, lower, and split and join.

Discover how to use f strings in Python to insert variables into strings in one line, offering a simpler alternative to the format function.

Learn how to compute string length without len(), extract usernames from emails via index and slicing, and check palindromes with a loop.

Learn how lists in Python function as dynamic, heterogeneous data structures that store multiple items under one name, with indexing, slicing, and nested lists, plus common operations and methods.

Discover essential list methods in Python, including append, extend, insert, and more, learn mutability, deletion, counting, indexing, and sorting to enhance your programs.

Explore Python list operations, including concatenation and repetition, membership tests with in and not in, and looping over lists, with practical code examples and a lead into list comprehension.

Explore Python list comprehension, a concise way to create lists from iterations, with examples like filtering, vector scaling, squaring, and selecting languages starting with p.

Explore how the Python zip function creates paired tuples by combining elements from multiple lists into a zip object, viewable by converting to a list, and handling unequal lengths.

Practice Python lists with zip mapping car names to quantities, unpacking tuples, and list comprehensions, then find common unique items from two lists and sort them.

Explore Python tuples, an immutable, list-like data type. Learn how to create, index, and slice tuples, and how to convert them to lists to modify data.

Learn to perform tuple operations in Python, including addition (concatenation) and multiplication (repetition) for tuples. Explore membership tests and loop iteration over tuples, with parallels to list operations.

Explore Python tuples, use built-in methods count and index, and perform length, min, max, sum, and sorted operations; convert to a list to apply list methods.

Explore the difference between lists and tuples in Python: lists use square brackets and are mutable, while tuples use parentheses and are immutable, faster, and memory-efficient.

Master tuple and list unpacking in Python, assign values to variables with unpacking, capture extras with the star syntax, and use zip to pair tuples and convert results to lists.

Explore emulating tuple comprehension in Python by wrapping a generator object with tuple(), since there is no built-in tuple comprehension, and apply the idea to list comprehension outputs.

Explore sets in Python as an unordered collection of unique, immutable items; learn how to create, add, and remove elements, and perform union and intersection operations.

learn sets operations in Python, including union, intersection, difference, and semantic difference, with membership and iteration demonstrations using sample sets.

Explore Python set methods, including union, update, intersection, difference, and semantic difference, plus is disjoint, is subset, is superset, and copy, with common functions like length and sort.

Explore frozen set in Python, an immutable version of a set you can use for union and intersection while preventing additions or deletions.

Learn set comprehension in Python using curly braces to create unique sets from list comprehension concepts, with 1 to 10 example filtering numbers greater than five and taking square roots.

Explore Python dictionaries, a mutable key-value data structure, learn about keys and immutability, creating dictionaries, accessing items, nesting with two-dimensional dictionaries, and adding, editing, and removing entries.

Explore dictionary operations in Python, focusing on membership tests for keys (in and not in) and iterating to access keys and their corresponding values.

Explore built-in dictionary methods in Python, such as length, sorted, max, min, items, keys, values, and update, with practical examples on a dictionary of name, age, and gender.

Explore dictionary comprehension in Python by building key-value pairs with range-based numbers and their squares, and filtering with conditions, while mapping data with zip and paralleling lists and sets comprehensions.

Build a restaurant management system in Python using a dictionary to map menu items to prices, handle user input, compute total, and print receipts.

Learn to define and use functions in Python, including built-in and user-defined forms, with def, parameters, and return values. Discover code reusability, abstraction, and decomposition that power scalable software.

Write clear docstrings inside Python functions to document purpose, inputs, and outputs. Boost robustness with input validation and type checks, and expose docs via the doc attribute.

Clarify the difference between parameters and arguments in Python functions, with examples of default, positional, and keyword arguments using a power function.

Explore Python's *args and **kwargs to pass variable-length non-keyword and keyword arguments, using star and double-star syntax, with tuple and dictionary handling and practical examples.

Explore how functions are executed in memory in Python beginners to advance bootcamp, using a Python tutor visualization of function calls and temporary memory blocks.

Explore functions without a return statement in Python, compare the return and print inside a function, and learn that without a return a function returns none by default.

Explains global and local variable scope in Python functions, shows access patterns, and explains why global variables can't be changed directly and how to use the global keyword.

Learn how to use nested functions in Python by defining a function inside another function, calling inner functions, and understanding local scope, recursion risks, and functional hiding.

Explore how Python treats functions as first-class citizens: pass, return, and assign functions, store them in lists, and examine types and ids.

Discover how using functions modularizes code, improves readability, and enables reuse across projects, from simple scripts to larger applications.

Explore lambda functions in Python, a one-line anonymous function that takes parameters, evaluates a single expression, and can work with higher order functions like map, reduce, and filter.

Discover how map, filter, and reduce enable higher-order programming in Python by applying lambdas to lists and dictionaries, producing mapped results, filtered items, and totals.

Learn how the Python enumerate function assigns indices to list items, returns (index, item) tuples, supports unpacking, and a start parameter for custom indexing.

Solve Python function exercises to extract unique items from a list, sort hyphen separated words alphabetically, and use map, filter, or reduce to identify highly skilled employees, with Hackerrank practice.

Learn to create and manage Python virtual environments with conda, isolate project dependencies and Python versions, install specific package versions, and switch between base and project environments.

Learn how to manage Python project dependencies with a requirements.txt file, listing packages like pandas, numpy, and scikit-learn, and install them all via pip install -r requirements.txt.

Learn the fundamentals of file handling in Python, including opening, reading, writing, and closing text and binary files, with examples of write modes, append, read size, and line-by-line reading.

Learn to manage files in Python with a with context manager, performing read, write, and append operations, and using chunking, seek, and tell to control the cursor.

Understand why text mode can't read binary data like images, and learn to use rb/wb for binary files and serialization for non-string data.

Learn to serialize Python data types to JSON, including lists and dictionaries, and deserialize JSON back to Python with the JSON library, writing to and reading from JSON files.

Learn how to save any Python object in a binary format with the pickle module, using dump and load to serialize objects for machine learning models and later prediction.

Master exception handling in Python by distinguishing syntax errors from exceptions, and implement robust try-except blocks to handle file not found and external inputs securely.

Learn to use try-except blocks to handle file not found, name, and index errors in Python. Explore specific exception types, else and traceback concepts to refine error messaging and debugging.

Explore using try, except, and else in Python to handle file operations, including opening a file, reading it in the else block, and catching file not found errors.

Explore try, except, else, and finally in Python with real-world examples. See how finally runs regardless of errors, and how to manage resources like file operations and database connections.

Raise exceptions in Python with the raise keyword to produce custom error messages, including zero division error and NameError, and use try-except to catch and display them.