Python PCEP Course - Become Certified Entry-Level Programmer

Explore unary operators with a single operand, such as plus and minus, and master bitwise operators that operate on binary digits, including and, or, xor, right shift, and left shift.

Learn unary operators with single operands, then apply bitwise and, or, and xor on x=10 and y=8 to produce outputs like 8, 10, and 2.

Explore left and right shift operators in Python, showing how left shifts multiply by two and right shifts divide by two, with examples and outputs like 10 and 80.

Explore operator priority and binding in Python, including exponentiation, unary versus binary operators, and left-to-right versus right-to-left associativity, with practical expression examples.

Master relational operators in Python by comparing values and evaluating true or false. Include greater than or equal to and less than or equal to.

Analyze Python operator precedence with a priority chart, from exponent to unary plus/minus, then arithmetic, and finally relational operators, noting equality and inequality have the lowest precedence.

Explore boolean operators like logical and, or, and not, using truth tables with operands X and Y to determine output Z and how true or false conditions guide code execution.

Explore Python boolean expressions using x and y, evaluating and/or/not, with true as 1 and false as 0, demonstrated through print statements and output examples.

Explore boolean expressions, true or false values, and relational operators including equality, less than or equal to, greater than, and not equal to, with practical examples.

Explore identity operators in Python, using is and is not to check if objects share memory locations rather than their values, with lists and practical examples.

Explore Python membership operators, including in and not in, and learn how they test whether elements are in sequences like lists, strings, and tuples through practical examples.

Explain Python's operator precedence from parentheses to boolean operators, highlighting unary, exponent, multiplicative, additive, bitwise, membership, relational, and identity groups and their equal-priority clusters.

master how Python's print outputs arguments with spaces and a trailing newline by default, and how to customize with end and sep, plus rules about positional versus keyword arguments.

Explore Python typecasting by using int, float, and str to convert data types, handle conversion errors, and observe implicit type conversion in arithmetic operations.

Explore Python strings, zero-based indexing with s[0], and how to access characters. Learn that strings are immutable and can raise index out of range errors.

Explains conditional statements and control flow in Python using if, else, and elif with proper indentation and colon syntax, highlighting true and false conditions.

Explore nested if statements by placing multiple conditional statements inside an if, emphasizing indentation to define nesting, optional one-line statements, and age comparisons that illustrate if-elif-else logic.

Explore using and, or, and not in if statements to handle multiple conditions in Python. Learn through examples with an average age comparison, printing results, and else branches.

Use the Python pass statement as a null placeholder in if blocks to avoid errors and reserve space for future implementation, shown with x = 3.

Learn how while loops drive iteration in Python, executing code while a condition holds and handling indentation, indexing variables, and common pitfalls like infinite loops.

Demonstrate how a while loop runs while a condition holds, then executes the else block at the end, demonstrating finalization after three iterations and what happens with break and pass.

Discover how Python's for loop iterates over sequences like lists, tuples, and strings, executing code for each item with a control variable and colon syntax.

Learn how list comprehension creates a new list from an existing list with a one-line for loop to square numbers. See how a generator object appears before returning final values.

Explore the range function in for loops, generating sequences with optional steps, defaults (start at zero, end at n-1), and behavior when end is not greater than start.

Demonstrate using a for loop with the continue statement to skip numbers meeting a condition and print only the odd numbers.

Learn how the pass statement lets you have an empty for loop in Python, preventing errors and allowing future implementation in a range example.

Master the for with else in Python by examining how an else block runs after a for loop ends, even if the loop doesn't execute, and how break affects it.

Learn how to control Python loops using break and continue statements, terminate loops on conditions, and understand how break affects inner versus outer loops in while and for constructs.

Learn how the Python continue statement skips current loop iterations in for and while loops, with practical examples using lists and range, and see how for-else behavior works.

Learn how to create lists in Python, a mutable sequence that stores values, supports indexing and slicing, and can hold different data types with examples like l1, l2, and l3.

Learn zero-based indexing in lists, access first and second elements, handle index out of range errors, and work with nested or multidimensional lists using nested indexing.

Concatenate lists with the plus operator, as shown by joining vowel lists. Use the star operator to repeat a list, and guide sorting with sort or the sorted function.

learn how to access list elements using negative indexing in Python, using -1 for the last item, -2 for the second last, and explore slicing and nested lists.

Learn how to get the length of a list in Python using the alien function, with an example list of five elements that prints the length.

Update list elements with simple indexing and assignment in Python. Learn to change a list item by index and copy values between elements through practical examples.

Master python list slicing with colon syntax to select ranges using start and end indices. Omit start or end to get the whole list, or reverse using a negative end.

Explore how Python list slicing copies list members into a new, separate object. Learn that changes to one list do not affect the other, a key PCEP concept.

Master negative slicing in Python by using negative indices on lists, where start is included, end is excluded, and -1 and -2 refer to the last and second-last elements.

Explore two essential Python functions: the length function for sequences, including nested lists, and the sorted function for sorting iterables with optional key and reverse.

The sort() method sorts a list in ascending or descending order with optional key and reverse, returns None, and mutates the original list, unlike sorted which creates a new list.

Learn Python list operations, including append and for loops to add elements, and insert for targeted adjustments. Compare del, index, copy versus assignment, and count to locate occurrences.

Explore Python list methods such as extend, pop, reverse, remove, and clear, including extending with lists and tuples, popping by index, and error handling for missing elements.

Learn how the del instruction deletes list items and slices in Python, including deleting the whole list, handling name errors, and alternatives like clear and pop.

Iterate a list using a for loop in Python, leveraging range and length to access elements and accumulate a total, demonstrated by summing list values to 75.

Discover list swapping in Python by using multiple assignment in a single line to swap s1 and s2 and then print the before and after states.

Learn how to swap list items in Python with direct indexing and a generic method that swaps symmetric pairs using a for loop and the list length.

Explore how to use in and not in operators to check element presence in lists, with true/false outcomes, and apply list processing to find smallest value with a for loop.

Master list comprehension to generate a new list by squaring each element of an existing list, reproducing the output of a loop and showing 0, 1, 4, 9, 16.

Explore tuples as immutable sequences like lists, learn their syntax with comma-separated elements wrapped in parentheses, and understand advantages such as immutability, security, and faster iteration than lists.

Explore how tuples use parentheses or none, unlike lists with square brackets, and learn that tuples are immutable while lists are mutable, with examples showing printing and type.

Learn to create empty tuples with parentheses, use a trailing comma for single-element tuples, and unpack into variables. Verify types and basic operations on tuples.

Explore mutability vs immutability in Python by contrasting mutable lists with immutable tuples, and learn why tuples cannot be appended, inserted, deleted, or have item assignments.

Learn how tuples, as a sequence type, support indexing, slicing, and nested element access like lists, including negative indexing and iterating with a for loop.

Understand tuple slicing, accessing ranges with start and end indices, omitting start or end, using negative indices, and copying tuples, like you do with lists.

Learn how to update a tuple indirectly by converting it to a list, modifying elements, then converting back to a tuple, and understand deleting a tuple with del.

Explore how tuples remain immutable yet support some list-like methods, such as sorted, index, count, and len, while noting methods that don’t apply to tuples.

Join two tuples with plus operator, print result and its length, and see that a new tuple is created without altering the original; multiply tuples with star operator.

Explore in and not in for membership tests in tuples, with examples like -20 and 20, and learn how tuples appear on both sides of assignment for unpacking.

Explore dictionaries as mutable key-value stores, distinct from lists and tuples, with unique keys and values that may duplicate, accessed by key.

Learn to create and print dictionaries in Python by mapping keys to values, including lists of values, and build dictionaries with dict() using key=value pairs.

Learn to access dictionary values by keys with square bracket notation, retrieve values with get, and handle missing keys with key errors in examples.

Learn how to add items to a dictionary by creating an empty dict, inserting single-value keys like planet and country, and storing multiple values under one key such as vowels.

Explore removing items from a dictionary with pop and pop item, showing how pop returns a key's value and how pop item removes the last inserted key-value pair.

Delete a specific key-value pair or the entire dictionary using the del instruction, and observe the results with print and the resulting undefined name error.

Learn how to merge two dictionaries in Python without the plus operator, using an empty dict and a loop with dict_three.update to create a combined dictionary.

Explore nested dictionaries in Python, with inner dictionaries containing even squares and odd squares, and print values like two is to four and three is to nine.

Loop through the dictionary with a for loop to print each key, then use the keys method to retrieve all keys like planet, continent, and country.

Explore how to access dictionary keys and values in Python by looping over keys, using the values method, and using items to retrieve key-value pairs.

Explore Python dictionary basics by using the in operator to check for keys, and learn to delete items with del and clear a dictionary, including handling key not present.

Copy a dictionary with the copy method to create a separate object with its own memory location, and contrast it with assignment where dicts share the same object.

Learn how to convert between tuples and dictionaries in Python using dict and tuple of pairs, noting that a dictionary to tuple yields only keys.

Explore Python strings, a data type and sequence of characters. Learn that they are immutable yet can be replaced via assignment, and declared with double or single quotes.

Declares strings with single or double quotes and demonstrates that strings are immutable, so you reassign a new string rather than updating characters, as shown by type checks.

Explore string indexing and slicing in Python, including positive and negative indices, and how del removes a string, showing the resulting name errors when accessing after deletion.

Explore how Python uses single or double quotes for single-line strings and triple-quoted strings for multi-line text, including how to print multi-line strings with preserved spaces.

Explore essential string methods and a function for length using the Mississippi example, including count, index, and substring, plus lower, capitalize, and upper for text processing.

Explain the difference between parameters and arguments in Python, show function definition versus call, and illustrate input handling, string results, and simple typecasting to keep age as a string.

Pass a list as an argument to a function, square each element, sum the results, and illustrate parameter scope and naming with LHS, L1, and L2 in Python.

Explore the scope of arguments in Python: use arguments inside a function while parameters stay inaccessible outside, and see how variables defined outside remain accessible inside through a function call.

Learn how deleting an element inside a function affects the original list when passing a list as an argument, using del to modify the outside list.

Learn why a function call must pass the same number of arguments as its parameters; mismatches trigger errors such as missing one required positional argument.

Learn to pass multiple arguments to a function by collecting age, name, and mobile as inputs and displaying them as a formatted output.

Learn why you cannot use Python keywords as arguments or parameters, as attempting to do so yields invalid syntax, while normal arguments like two and three produce the correct result.

Explore how the return statement terminates a function and returns a value, illustrated by a greetings function that yields 'Welcome'. Storing the return value enables printing the result.

Understand return without expression in python, where a return terminates a function immediately and returns control to the caller, as shown in a greetings example with conditional prints.

Test your knowledge by analyzing a Python example with two functions; passing 3 to f2 computes f1(3) + f1(3) with f1(3) = 27, producing 54.

Explore how the Python None value represents an unknown or non value, demonstrate type errors with None and integers, and show that functions without a return implicitly yield None.

Explain that there are three types of arguments, positional, keyword, and mixed, focusing on how positional argument order maps to parameters and changes results with examples.

Learn how keyword argument passing in Python lets you supply values by parameter name, making order irrelevant while preserving correct parameter names; mismatched names raise errors.

Learn the rule that positional arguments must come before keyword arguments in Python, and avoid errors from multiple values or mixed argument orders.

Explore default parameters in Python and how defaults are overridden by arguments, including keyword arguments. Learn that a non-default parameter cannot follow a default, and how multiple defaults operate.

Understand name scope in Python: an outer variable can be read inside a function but cannot be written, illustrated by outer variable used in a function and a welcome message.

explains how a variable outside a function can be read but not written inside, demonstrating name scope, name hiding, and how inside and outside variables remain distinct.

Explore how variables with the same name inside and outside a function use separate memory locations, and how passing arguments creates distinct parameters and IDs.

Demonstrates how lists passed to a function may share memory or create a new list, clarifying how changing the parameter differs from changing the list itself, with IDs shown.

Learn how the global keyword extends a function's variable scope to the global level, letting outside variables reflect updates with clear Python examples.