Python & Django Framework for Beginners - 2025

Explore Python's high-level, object-oriented design with easy syntax and dynamic typing. Learn immediate, script, and IDE coding modes, core concepts like modules, packages, and the Django framework.

Install and configure Anaconda on Windows, selecting Python 3.6 64-bit, agreeing to the license, choosing the destination folder, and optionally installing VS Code to prepare for Python program execution.

Understand how Python uses variables as named memory locations with dynamic typing and automatic assignment, and recognize constants that cannot change, along with camel case naming and uppercase constants.

Demonstrate Python's object oriented model by defining a complex number class as a blueprint, using a constructor and instance attributes, creating objects, printing values, and managing attributes.

Explore Python array concepts through list-based implementations, covering append, extend, insert, remove, pop, index, count, sort, reverse, and copy, with notes on numpy arrays for real arrays.

Explore Python file methods and how input variations affect behavior, including close, open, detach, file info, file descriptor, flush, read, seek, tell, truncate, and writable checks for interactive streams.

Learn how Python keywords are reserved words that define syntax and cannot be used as identifiers. Identify how Python identifiers name classes, functions, and variables, with case sensitivity.

Explore Python tuples, their immutability, heterogeneous data handling, and how they differ from lists. Create, index, slice, unpack, concatenate, and apply built-in tuple functions for efficient, dictionary-key friendly data.

Explore Python sets, an unordered collection of unique items, where elements are immutable but the set is mutable, and perform union, intersection, difference, and symmetric difference with common methods.

Learn how Python modules expose classes, functions, and variables, and how packages create namespaces. Practice importing with aliases and from imports, including numpy and pi.

Explore Python directory and file management using the OS module to create, rename, list, and remove directories and files, and manage current and changing working directories.

Explore Python dictionaries, their key-value structure, and how to define them. Learn common operations such as access, update, delete, clear, copy, get, items, keys, values, and dictionary comprehensions.

Explore python strings as sequences of characters, including encoding and decoding with ascii and unicode. Define, index, slice, and concatenate; apply formatting, lower and upper, and find and replace.

Learn how Python handles data type conversion, including implicit and explicit type conversion, with demonstrations converting integers, floats, and strings, and avoiding type errors in operations.

Explore Python number types—integers, floats, and complex numbers—and learn type checking with type and isinstance, number representations in binary, octal, and hexadecimal, and precision handling with decimal.

Explore python namespace and scope, including built-in, global, and local namespaces, across modules, functions, and classes. See how id reveals memory addresses and how global and nested functions shape scope.

Explore global, local, and non-local variables in Python, showing how scope governs access inside and outside functions, and how global and non-local keywords affect values in nested functions.

Learn how the Python global keyword lets a function read and write a global variable and distinguish between local and global scope through a practical demonstration.

Explore Python iterators and the iterator protocol, showing how iter and next enable iteration over lists, for loops, and generators, with examples of stop iteration and custom iterators.

Master Python for loops by learning syntax, iterating over lists, tuples, strings, and other iterables, using range for number sequences, and applying else and break logic.

Explore Python inheritance and polymorphism by defining base and derived classes, covering single, multiple, hierarchical, multi level, and hybrid inheritance, with practical demonstrations.

Explore how Python implements multiple inheritance by deriving a class from several base classes, inheriting their features, methods, and variables, with practical demonstrations.

Explore how Python handles function arguments, including default, keyword, and arbitrary arguments. See practical demonstrations of max finding, optional inputs, and summing variable inputs.

Learn how Python functions organize code with def, parameters, and return values, and distinguish built-in and user-defined functions through practical examples and docstrings.

Learn how the break statement terminates loops, including in nested cases, with a practical example using while true and a random number to exit.

Explore Python errors and exceptions, including syntax errors, runtime and semantic errors, and common exceptions like assertion error, import error, and index error, then learn try, except, and finally usage.

Explore Python exception handling with try, except, and finally, learn how errors propagate, and see practical demonstrations of zero division, value errors, and name errors.

Define a user defined exception in Python by creating a voter eligibility class that inherits from Exception and uses super in its constructor, then demonstrate raise, except, else, and finally.

Explore Python's object oriented programming by defining objects and classes, and demonstrate inheritance, encapsulation, and polymorphism with practical examples to reinforce DRY and reusable code.

Explore Python nested dictionary implementation by creating and manipulating dictionaries within dictionaries, accessing elements, adding and deleting entries, and iterating with nested loops to print inner key-value pairs.

Explore Python operator overloading, where the same operator performs different actions for numbers, lists, and strings, and learn through a practical my point class demonstrating __add__ and __lt__ methods.

Learn Python statements and comments, including assignment and control statements, line continuations (backslash and implicit), indentation, and docstrings.

Learn how the Python pass statement acts as a null, no-op placeholder that the interpreter executes without output. Compare it to comments and see how to use it in code.

Learn how Python generators simplify creating iterators by using yield, pausing and resuming with preserved state, avoiding boilerplate __iter__ and __next__ methods, and automatically handling stop iteration.

Explore Python decorators and metaprogramming, learning how to decorate functions with the @ symbol, create inner functions, and handle cases like division by zero.

Learn how the Python while loop iterates while a test condition is true, supports an else block, and can be broken out with break, with practical demonstrations and pattern printing.

Master Python conditional statements by using if, elif, and else with proper indentation and colon, exploring execution flow and nested conditions through practical age examples.

Learn to implement a two-dimensional matrix in Python using nested lists, define and print matrices, index elements, and explore dynamic creation with loops and shallow vs deep copies.

Explore Python regular expressions to locate, validate, and replace strings using the re module, find matches with findall and finditer, and handle patterns with raw strings, character classes, and substitutions.

Discover Python list comprehension through practical examples: converting strings to lists, comparing with lambda function and for loops, filtering with conditions, and transposing a matrix.

Master recursion in Python, including direct and indirect recursion and base cases. See how recursive functions solve problems with factorial and discuss advantages and disadvantages.

Discover how to handle input and output in Python, print values, and perform simple operations. Explore importing modules, typecasting strings to integers, and basic string formatting with placeholders.

Explore read and write operations on data files in Python. Open a file, read or write, and close it using modes r, w, a, and b for text and binary.

Explore Python looping techniques, including top-, middle-, and bottom-condition loops, break-based exits, infinite looping with while true, and do-while simulations using an even-odd input example.

Explore how shallow copy and deep copy differ in Python, using copy module demonstrations to show reference sharing and full object duplication for nested lists.

Learn how Python assert statements use boolean expressions to validate conditions, raising assertion errors when false, and see a practical demo using an avg function and nonempty lists.

Learn how Python's property enables getter and setter methods, demonstrated with a Celsius temperature class and Fahrenheit conversion to simplify object oriented programming.

Explore Python closures, including nested functions and non-local variables, through practical demonstrations of defining, accessing, and returning closure functions.