Core Python for Everyone

Learn to write your first Python program by assigning numbers to variables, adding them with the plus operator, and displaying the sum, while using # for comments.

Explore the Python development environment by tracing how a Python program moves from source code to execution, detailing the roles of compilers and interpreters and machine language.

Explore common programming errors in Python, including syntax, runtime, and logical mistakes, plus indentation and correct operators. Learn how proper variables and function names ensure code runs reliably.

Discover Python data types by learning how variables store values like numbers and strings, and explore booleans and dictionaries, with keywords like true and false.

Explore sequential control flow in Python, using input and type conversion to compute averages of physics, chemistry, and mathematics within structured programming, including selection and loops.

Explore pseudocode and flowcharts as tools to describe algorithms, break tasks, and design programs using flowchart symbols for initialization, assignment, input, and decisions.

Explore operator precedence in Python, showing how multiplication and division share priority and how left-to-right associativity determines the program output, with examples to avoid confusion.

Explore Python's logical operators and, or, and not, and their truth values. Learn how Python evaluates conditions and uses these operators to test divisibility by three or five.

Master iteration control flow by generating a sequence with a fixed difference, using the assignment operator, and writing reusable code to avoid copying instructions in large programs.

Master how to use Python for loops and the range function to generate sequences, control iteration, and compute sums with practical examples.

Learn how to use nested loops in Python to generate star patterns, control line breaks with print end, and build multi-line outputs through outer and inner loop coordination.

Explore counter controlled and sentinel controlled loops in Python by building a program that computes the average marks for physics, chemistry, and mathematics based on user input.

Define and use functions to find the highest of three numbers, covering input and formal parameters, return values, and code reuse.

Learn how nested functions work in Python, including inner function scope, local vs global variables, and the use of nonlocal and global keywords to access or modify values.

Learn to divide a software project among team members, assign independent programs, and integrate them to compute the maximum of three numbers, demonstrating collaborative development and leadership.

Explore the advantages and disadvantages of using functions, highlighting code reusability and stack memory implications for parameters and local variables.

Learn how Python lists store multiple values of different types and are indexed from zero, with access by indices and negative indices. Build skills to slice, modify, and extend lists.

Explore arrays and lists in Python, practice creating and editing lists, inserting values at the next position, and removing elements to see the modified results.

Learn how tuples differ from lists, emphasizing immutability, indexing, and how data types are organized in Python collections.

Master numpy for scientific computing with multidimensional arrays, matrices, and core operations like arithmetic, sorting, and basic statistics. Learn to perform matrix multiplication and array manipulations using numpy functions.

discover how to define strings in Python, store words and sentences, and work with Unicode characters and multi-line strings.

Explore string immutability in python: once defined, a string cannot be modified or deleted, and memory can be saved by avoiding unnecessary string duplication across unicode strings.

Learn how to create and manage multiple objects in Python, using constructors and methods to compare attributes, volumes, and costs, and to model object interactions.

Explore how a nested class serves as a data member of another class by embedding related objects like an address within an identity card, reducing identifiers and boosting maintenance.

Explore Python classes by building a practical example with two classes, attributes, and a driver function to demonstrate data handling, calculations, and basic object interactions.

Explore access specifiers and encapsulation in Python classes, learning how private attributes are protected, how public access works outside the class, and how copying yields independent objects.