Learn Python Programming From A-Z: Beginner To Expert Course

Discover three ways to install Python on Windows: the official Python website, many kunda, and the Anakonda distribution, with Anakonda recommended and installation verified via the command prompt.

Discover how Anaconda provides a one-stop Python data science toolkit, and explore Jupyter notebooks for interactive coding and documentation, as well as managing environments and libraries.

Explore the Jupiter notebook interface, create and manage notebooks, run code and markdown cells, and save checkpoints while exporting to pdf, python files, or slides.

Explore how Python counts physical and logical lines and how the interpreter processes line breaks. Compare using backslashes and semicolons to join lines for readability.

Learn how to place multiple statements on a single line in Python using semicolons, while prioritizing readability over line count and preparing for indentation, the next essential concept.

Master indentation in Python to define code blocks and flow with consistent spaces, avoid errors, and follow the style guide for nested and hanging lines.

Learn how Python variables act as memory references, how to name them with lowercase underscores, and how to perform simple operations and use the print function.

Explore integers and floats in Python, learn how type inference and the type function reveal data types, and see how arithmetic yields float results.

Learn how strings are sequences of characters in Python, and how to declare them with single, double, or triple quotes, with backslash escapes for quotes, indexing and slicing.

Learn string manipulation in Python: concatenate with +, repeat by integers, and check substrings with in; use built-in functions like len, str, and int.

Index strings with square brackets using zero-based positions to access characters, including the first at index zero and the last with negative indices. Indices beyond the string length throw errors.

Explore string slicing in Python by using start:end indices and default stride of 1, learn zero- and negative-indexing, and apply count and find to locate substrings.

Master advanced printing techniques in Python by using the print function, formatting with placeholders and the format method, printing to files for logging, and debugging data.

In mini project 1, learn to build a Python letter counter by taking a message and a letter, counting occurrences and computing its percentage, then printing the results.

Explore Python operators, including arithmetic, assignment, comparison, logical, identity, membership, and bitwise operators, used to perform operations on variables and values with concrete examples.

Master arithmetic operators in Python, from basic ones like addition, subtraction, multiplication, and division to advanced ones such as modulus, floor division, and exponentiation, with practical examples.

Learn assignment operators in python, including =, +=, -=, *=, /=, and advanced forms like modulus assign and exponent assign; understand why plus equals uses the previous value.

Explore Python's comparison operators, equal, not equal, less than, less than or equal, greater than, greater than or equal, and floating point limitations, with rounding as a practical workaround.

Master Python's logical operators not, or, and to evaluate truthiness and boolean expressions, understand how equality differs from truth value, and learn to use Stack Overflow for solutions.

Master Python membership operators by using in and not in to check if a sequence exists in another, with practical examples on strings and lists.

Explore bitwise operators in Python, including and, or, exclusive or, and bit shifts. Understand binary representation, how these operators process each bit to produce results.

Master sets in Python: store unique, unordered elements; learn to add and remove items with special functions, and why sets cannot be indexed.

Explore compound data types by using dictionaries, lists, and tuples, including dictionaries inside dictionaries and lists inside dictionaries, and learn to index into nested structures.

Explore control flow as the programming power behind Python, building logic with data types and operators to write more interesting, advanced code.

Explore basic conditional statements in Python, using if, else, and colon-driven blocks with indentation to control code execution and ensure the first true condition runs.

Master while loops and their differences from for loops, including when to use them to avoid infinite loops, with sensor readings and accumulation examples.

Master break and continue statements to control loop flow, then use enumerate and zip for readable Python code. Build dictionaries with for loops and explore list comprehensions.

Explore the continue statement role in skipping current iterations within for and while loops, and compare it with break to see practical uses like printing even numbers.

Explore the enumerate function, a zip-like tool that iterates over a single iterable while counting, returning index and value pairs; learn with a practical example.

Discover how list comprehension provides a compact, one-line alternative to building lists with a for loop and append in Python. Compare it to the normal three-step approach.

Explore Python functions, including the help function, and learn how to define your own functions to organize code. Understand local versus global scope and the purpose of docstrings.

Learn how to use the python help function to discover inputs, outputs, and descriptions for built-in functions like print and append, saving time without memorizing details.

Learn to define Python functions with def, specify inputs (including defaults), implement a function body with return, and name functions clearly while avoiding Python keywords and built-ins.

Learn how to document Python functions with doc strings using triple quotes, explaining inputs, outputs, and function behavior, and follow company standards and Python conventions such as BEP 257.

Explore error handling and user input in Python by distinguishing syntax errors from exceptions, and learn how to prompt and process user data in scripts.

Explore error handling fundamentals by distinguishing syntax errors from exceptions, see how a simple function can throw with strings, and practice catching and handling errors like division by zero.

Learn to capture user input with the input function, provide a helpful prompt, cast the input to an integer or float, and handle invalid input with a clear message.

Identify and fix syntax errors in Python by reading the interpreter's filename, line number, and error message, and learn how sequential fixes enable code to run.

Explore Python exceptions as runtime errors, including zero division, name, type, and assertion errors, and learn to handle them with try, except, and raise.

Master handling exceptions using try and accept to prevent code from stopping, see how specific handling avoids crashes like cannot divide by zero, and learn to use assertions strategically.

Learn to handle multiple exceptions in Python using try, except, else, and finally. Understand how zero division errors and assertion errors trigger different paths, and how finally affects return values.

Explore Python advanced functions, including lambda expressions, args and kwargs, iterators, generators with yield, and map and filter, with a focus on memory-efficient iteration.

Lambda functions provide one-line, simple functions in Python, using the lambda keyword and a colon body for quick tasks and higher-order use with map and filter.

Explore Python function input flexibility with *args and **kwargs, learn how to pass positional and keyword arguments, and master the required, optional, and order rules for clean, maintainable code.

Learn how Python iterators wrap a data stream, convert iterables to iterators, and traverse elements using next, with lazy evaluation for large datasets.

Explore the map function as a higher-order tool that applies a function to iterables, using lambda expressions, generators, and unpacking to write concise Python code.

Explore the filter function as a higher-order tool in Python, comparing it to map, returning booleans and generators, and converting results with list or lambdas.