Python 2023 Course in Depth: Beginners to Advanced

Learn Python's features such as its simplicity, open source nature, and high-level design. Explore platform independence, dynamic typing, extensible libraries, and modules like NumPy, pandas, and Django.

Discover how Python identifiers name variables, functions, and classes, follow rules for alphabetic first characters, underscores for multiword names, avoid special characters and keywords, and note case sensitivity.

Explore Python keywords as reserved words, including the capitalized forms of true, false, and none, and view the 33 keywords via the keywords module.

Explore Python data types, including fundamental types like int, float, complex, boolean, and string, and collection data types, with core functions type, id, and print explained.

Explore integers as a Python data type, including decimal, binary, octal, and hexadecimal representations, and learn to convert between forms using built-in bin, oct, and hex functions.

Explore the float datatype in Python, a numeric type for numbers with a decimal part. Use exponential forms like 1.2e3 and 4.7e6 to store large values efficiently.

Explore Python's complex data type, representing numbers with real and imaginary parts using j, and access them with .real and .imag while adding or subtracting with other numbers.

Master the boolean datatype in Python, which holds true or false values, and see how 10 > 20 and 10 < 20 yield boolean results mapped to 1 and 0.

Explore python's string datatype as a sequence of characters defined by single, double, or triple quotes, including multi-line strings, with letters, numbers, and symbols.

explore list and tuple data types in Python, uncovering insertion order, duplicates, and heterogeneous elements in lists, and the immutable nature of tuples with indexing and slicing.

Explore the bytes data type and the byte array in Python, covering immutable vs mutable behavior, the 0 to 256 value range, and how to create and use bytes.

Explain none as the last datatype in Python, a keyword that represents no value, similar to null in Java, and show how variables can exist without a value.

Discover how Python sets store unique, heterogeneous items with no insertion order and how to modify them with add and remove; convert a set to a frozen set using frozenset.

Master Python's range object, a sequence of immutable numbers with a begin index inclusive, end index exclusive, and optional step. Use it to build lists like 1 to 100 quickly.

Master Python dictionaries as key-value data types in curly braces. Access by key, keep keys unique while values may duplicate, and add or delete pairs mutably.

Explore Python arithmetic operators, including plus, minus, star, slash, percent, double slash, and double star, with examples showing their results and differences between float division and floor division.

Apply Python relational operators, such as greater than, less than, greater than or equal to, and less than or equal to, through hands-on examples with x and y.

Explore Python equality operators, including double equals and not equals, with true and false results and chaining concepts illustrated through practical comparisons.

Explore Python's logical operators and, or, not, with clear truth tables and practical examples. Learn how booleans convert from numbers, including zero, and from empty strings and lists.

Explore bitwise operators in Python, including and, or, not, and xor, with bit-level operations on binary data and examples using four and five, plus complements and two's complement for negatives.

The lecture explains Python assignment operators, shows how the single equals assigns values, contrasts it with double equals for comparison, and demonstrates compound assignments like +=, *=, /=, //=.

Explains how in Python the ternary operator evaluates a condition to return one of two values in a single line, with maximum and minimum element examples.

Delve into Python's special operators, focusing on identity operators (is, is not) and membership operators (in, not in), with examples showing memory addresses vs. value equality in lists and strings.

explains how to take dynamic input in Python using the input function, converts strings to integers, and sums two numbers while avoiding hard coded inputs.

Learn how to take multiple inputs in one line in Python using the input function, split by commas, convert to integers with a list comprehension, and compute their sum.

Learn how to capture command line arguments in Python using the RGV attribute, treat inputs as strings, and convert them to integers, floats, or booleans as needed.

Learn to use the Python print function to display output with new lines, tabs, repetition, and multiple arguments, including separator and end options and percent-style formatting for lists and tuples.

Explore Python flow control in this introduction, covering conditional, transfer, and iterator statements, including for and while loops, to manage code execution.

Explore the first conditional in Python with an if statement that executes a block when true, including input, integer conversion, and indentation.

Explore how if-else controls Python program flow, evaluating conditions to run if blocks or else blocks, with examples of voting eligibility, largest of two numbers, and palindrome checks.

Explore how Python's if-elif-else chains handle multiple conditions, with syntax overview and examples, including comparing two numbers and checking even or odd by remainder.

Master Python for loop fundamentals by iterating over sequences, using range to print numbers, filtering even values with if conditions, and collecting results in a list.

Explains using the while loop in Python to run code while a condition is true, with examples printing numbers, filtering evens or odds, and summing first n numbers.

Explore the infinite loop concept, showing how a while loop can run indefinitely, printing values, with examples like i < number, while true, and the break concept.

Explore nested loops in Python by nesting one loop inside another, using range-based outer and inner loops, counting total iterations, and generating star patterns across rows.

explore python transfer statements break, continue, and pass that alter loop flow; learn to stop loops with break, including printing 1–10 and ending an infinite loop at 100.

Explore the Python continue statement, which skips an iteration without breaking the loop, and see a range 1 to 10 example that prints only even numbers.

Learn how the Python pass statement lets you declare empty blocks to satisfy syntax in functions, loops, and classes, avoiding syntax errors while coding flow control.

Learn how Python strings work, including declaring with single or double quotes, using type checks, and creating multi-line strings with triple quotes; single characters are also strings in Python.

Learn to access string characters in Python using positive and negative indexing and slicing, with begin inclusive, end exclusive, and step options, including index error handling.

Explore string mathematical operators, including concatenation and repetition, to join and repeat strings. Use the plus sign for concatenation and the star for repetition, noting operand requirements.

Calculate the string length with the len function to count characters in python, then print each character with its positive and negative indexes using a loop.

Discover how Python's membership operators in and not in let you check whether a substring or character exists in a string, returning true or false.

Explore removing spaces from strings in Python with strip, lstrip, and rstrip, which trim both sides, only the left, or only the right, while spaces inside remain untouched.

Learn how to find the index of a substring in Python strings with find and index, including first and last occurrences and the difference when not found (-1 vs error).

Explore counting substrings with the count function, using examples with abc, java, python, and ruby, and learn how begin index and end index influence results.

Learn to replace a substring in Python using the replace function, with practical examples like swapping difficult with easy, letters with B, and Java with Python.

Learn how Python's split and join functions convert strings into lists using separators, then reconstruct strings from lists to format dates, times, and text.

Explore how to change string cases in Python, covering upper, lower, swap case, title, and capitalize functions, with practical examples and the key differences between title and capitalize.

Explore Python's startswith and endswith functions to test if a string begins or ends with a given substring. See practical examples and how these boolean checks validate strings.

Explore how to check string content with Python's isalnum, isalpha, isdigit, islower, isupper, istitle, and isspace, and learn how each returns true or false for different inputs.

Explains three approaches to format Python strings, using the format method, replacement operator, and format function to insert name, age, and salary data.

Explore how Python lists serve as an ordered, dynamic, and mutable data structure with preserved insertion order and allowed duplicates. Understand heterogeneous elements and how lists grow, shrink, and update.

Explores five methods to create lists in Python, including empty lists, literal lists, user input with eval, list conversions from tuples, character lists from strings, and splitting strings.

Learn how to access Python list elements using positive and negative indexing, and extract sublists with slicing, including start indices, end indices, and exclusive end.

The lecture shows that a list is mutable in Python, and demonstrates updating elements with positive indexing (starting at zero) and negative indexing, resulting in visible changes.

Learn to traverse a list in Python by iterating with for and while loops, touching each element, printing values, using range and len, and converting range to a list.

Explore how len, count, and index operate on lists in Python, using examples to show how len returns the number of elements, count tallies occurrences, and index locates first occurrences.

Explore how to add elements to a Python list using append, insert, and extend, compare last position and specific index behavior, and learn to join lists with extend.

Learn how to remove elements from a Python list using remove and pop, including removing specific items, the last element, or by index, with notes on errors and return values.

Learn how the list.clear function in Python deletes all elements, leaving an empty list object, demonstrated with numeric and string examples to show list truncation.

Learn to reverse and sort Python lists using the reverse function and the sort method. Understand ascending and descending order, and restrictions when lists contain both numbers and strings.

Explore how to manipulate lists with the concatenation and repetition operators, using plus to join two lists and hashtag to repeat a list a given number of times in Python.

Explain aliasing and cloning in Python, showing how two lists may share the same memory object and influence each other. Show how the copy function creates independent objects.

Master Python membership operators in and not in by examining how to test list elements such as ten, Java, Python, and 20, with spacing rules and practical examples.

Master nested lists in Python: store heterogeneous data, access elements via indexing and slicing (including negative indices), and print a matrix with nested loops.

Explore list comprehension in Python, a concise, one-line alternative to loops for creating lists. Build lists from ranges, filter evens, compute squares, find common elements, extract initials, and measure lengths.

Explore Python tuples, an immutable, read-only version of lists enclosed in parentheses that preserve insertion order and allow duplicates and heterogeneous data. Use cases include when data must stay constant.

Discover ways to create tuples in Python: empty tuples, multi-value tuples with or without parentheses, single-value tuples with a trailing comma, and converting iterables to tuples using the tuple constructor.

Explore indexing and slicing tuples in Python, using positive and negative indices, begin and end rules, and step values to access elements.

Learn how to apply two mathematical operators to tuples: the concatenation operator (using plus) to join tuples, and the repetition operator to repeat tuple elements a specified number of times.

Explore six important tuple functions—len, count, index, sorted, max, and min—and learn to compute length, count occurrences, find first indices, sort to a list, and identify extrema in tuples.

Master tuple packing and unpacking in Python by consolidating multiple variables into a single tuple and then redistributing its elements to separate variables.

Learn how Python handles tuple comprehension by using a generator and converting it with tuple(), and apply the expression for loop with an optional if to create tuples.

Explore the differences between lists and tuples in Python, including mutability, square brackets vs parentheses, and dictionary keys. Use lists for evolving data and tuples for constant data.

Explore python sets as a data structure of unique elements, where duplicates are not allowed and insertion order is not preserved, with mutability and the frozen set variant.

Learn how to create set objects: use curly braces for content, set() for empty sets, convert sequences with set(), and empty braces create a dict while duplicates are ignored.

Learn how to add elements to a set using the add and update functions, adding one element at a time or multiple elements from lists and ranges.

Remove, discard, pop, and clear remove elements from a set. Remove raises an error if missing; discard does not; pop removes a random element and returns it; clear empties set.

Learn how the copy function clones a set to create an independent object, avoiding shared references. Discover why direct assignment links to the same memory.

Explore Python's membership operators, in and not in, and learn how they return true or false based on element presence in a set.

Explore set theory basics by applying union, intersection, difference, and symmetric difference to data sets, using function names or the pipe and cap symbols to produce nonduplicated outputs.

Master set comprehension in Python: create sets in one line with curly braces, an expression, a for loop, and an optional if condition, with 1–10, evens, odds, squares, and doubles.

Python dictionaries store data as key-value pairs with unique keys; values may be duplicates and can be different types. They are mutable, dynamic, unordered, and accessed by keys, not indexing.

Learn how to add, update, and delete dictionary entries in Python by manipulating key-value pairs. Use examples to add new keys, override values, and remove entries with the del keyword.

Learn how to create empty dictionaries and dictionaries with data in Python, and access values using keys, while handling missing keys.

Explore dictionary functions in Python, including dict(), len(), get(), pop(), popitem(), keys(), values(), items(), copy(), and setdefault to manage key-value pairs.

Learn to build a Python dictionary program that collects student data from user input, stores it as roll numbers to names, and prints the entire dataset.

Learn dictionary comprehension in Python by constructing key-value pairs from ranges and expressions, including squares, doubles, and optional filters, plus counting element occurrences from a list.