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

Install Python and set up the development environment with Anakonda and Jupiter notebooks, then learn Python syntax, indentation, line structure, and comments to build a solid foundation.

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 Python line structure, where code is divided into logical lines ended by newline, with comments and blanks ignored, and learn how physical lines map to logical lines using backslash.

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 comments document Python code to improve readability and collaboration, and follow guidance on single-line comments using # and multi-line comments with triple quotes.

Learn how to join long logical lines in Python using backslashes to avoid horizontal scrolling. Follow the official Python style guide's line-length recommendations to keep code readable.

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.

Explore Python's basic data types, including variables, strings, booleans, integers, floats, and complex numbers, then differentiate mutable lists and dictionaries from immutable strings and tuples, with print and type functions.

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.

Explore the boolean data type in Python, with true and false values, proper capitalization, and how booleans evaluate expressions and interact with printing.

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.

Learn how identity operators 'is' and 'is not' differ from equality '==' by memory references in Python, and how small integers (-5 to 256) may share memory.

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.

Learn how list slicing and indexing in Python work with zero-based indexing, using square brackets and colons, and compare lists (mutable and ordered) to strings (immutable) through item assignment examples.

Learn about tuples, the immutable and ordered data type in Python, created with circular brackets, with indexing and slicing like lists.

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

Learn dictionaries as key-value stores with unique keys for indexing, initialized by curly braces and colons, and use get() to safely access values that may be non-unique or nested.

Learn when to use lists, tuples, dictionaries, and sets in Python, based on mutability, ordering, uniqueness, and relationships, with a preview of compound data structures.

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 the Python control flow, including if/else/elif, boolean expressions, for and while loops, and learn how conditional and repetitive execution shapes program logic.

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.

Learn advanced conditional statements in Python, using if with membership tests and and/or logic to combine lists of strings, numbers, and floats.

Explore for loops in Python to iterate over lists, dictionaries, files, and strings, using range for numeric iterations and proper indentation to define the loop body.

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.

Learn how the break statement stops a loop when a condition is met, for and while loops, and how it prevents further iterations while the rest of the code continues.

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.

Learn the zip function in Python, which maps multiple iterables to a single iterator of tuples for parallel iteration in for loops.

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.

Explore functions: inputs and outputs can be optional, and how functions encapsulate logic to reuse code. Learn basic and advanced Python functions in a functional and object oriented paradigm.

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.

Explore variable scope by distinguishing global and local variables and using the global keyword to access and modify shared data across functions.

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.

Explore Python advanced functions, including lambda functions and args and kwargs, plus iterators and generators with yield. See how map and filter apply functions to iterables and return results.

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.

Discover how generators use yield to create iterators, enabling lazy evaluation and memory efficiency. Compare with normal functions and learn to fetch values via next or loops.

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.