Python,Flask Framework And Django Course For Beginners

Explore Python's high-level, object-oriented design, easy syntax, and cross-platform reach, then master immediate, script, and integrated development environment coding modes with tools like Jupyter and Spyder, including Django and Flask.

Learn Python variables and constants, defined as named memory locations, with dynamic typing, automatic initialization, and flexible assignment. Explore valid names, camelCase conventions, and multi-value assignments in one line.

Explore Python class and objects through an example of a complex number class, its constructor, attributes, methods, instantiation, and object deletion.

Explore Python lists as flexible arrays by learning core operations: append, extend, insert, remove, pop, and copy, while indexing, slicing, and sorting elements, including multidimensional lists.

Explore Python file methods, from open and close to detach, fileno and flush; learn read, readline, readlines, seek, tell, truncate, and how readable, writable, and seekable properties control access.

Explore python keywords and identifiers, and learn reserved words, rules for valid identifiers, and examples such as true, false, none, plus common keywords like break, class, def, lambda, and more.

Learn how python tuples offer immutable, heterogeneous collections that differ from lists and can serve as dictionary keys. Explore creating, indexing, slicing, concatenating, and common tuple operations.

Explore Python sets as unordered collections of unique items, perform union, intersection, difference, symmetric difference, and update operations, and use mutability features including add, remove, discard, and frozenset behavior.

Explore python modules and packages, learn how importing enables code reuse, use aliases and dot notation to access functions and classes, and compare import styles: import, from, and star.

Explore Python directory and file management by creating, listing, renaming, and deleting directories and files, using current working directory navigation, listing contents, and basic path operations.

Explore Python dictionaries as unordered key-value stores, learn to create, access, and modify them using methods like get, keys, items, pop, clear, and fromkeys, plus dict comprehension and membership tests.

Explore Python strings from definitions and encoding to indexing, immutability, and concatenation; learn string formatting with format, escaping quotes, and using in, enumerate, and find.

Explore Python data type conversion by showcasing implicit and explicit type casting, converting strings to integers or floats, and handling type errors during mixed operations.

Explore Python's number types, including integers, floats, and complex numbers, and learn type checks with type and isinstance, prefixes for binary, octal, and hexadecimal, and decimal conversions.

Gain insight into Python namespaces and scope, including local, global, and built-in namespaces, the memory address via id, the global keyword, and how nested functions share and modify variables.

Explore global, local, and non-local variables by examining their scope in Python, including global and nonlocal keywords and nested function interactions.

Apply the Python global keyword to read and modify a global variable from inside a function, illustrating local versus global scope and updating the global value.

Explore how Python iterators work, implement the iterator protocol with __iter__ and __next__, and create custom iterators that raise StopIteration when exhausted.

Explore Python for loops to iterate over sequences, use the range function with start, stop, and step, and master else and break blocks, including nested loops.

Learn how inheritance creates derived classes from a base class in Python, covering single, multiple, hierarchical, multilevel, and hybrid forms, with examples of constructors and polymorphism.

Discover how Python supports multiple inheritance by deriving a class from several base classes and combining their features. The lecture demonstrates base and derived classes with practical method demonstrations.

Explore how Python handles function arguments, including optional and default values, fixed versus variable arguments, and *args, with practical demonstrations like a max finder and a sum of arbitrary inputs.

Learn to write Python functions using def, parameters, and return values to create modular, reusable code, including docstrings and a menu-driven calculator for basic operations.

Learn how the Python break statement terminates a loop and transfers control to the next statement. See lowercase syntax, nested loop behavior, and a practical demonstration with continue for contrast.

Explore the Python continue statement, learn how it skips the rest of the loop body for the current iteration, and see an example printing only even numbers.

Explore Python syntax and semantic errors, and learn to handle exceptions using try, except, and finally with assertion, end-of-file, import, index, division by zero, and type errors.

Learn how Python handles exceptions with try, except, and finally blocks and how programs generate error messages when division by zero or invalid data types occur.

Explore Python user defined exceptions with a voters eligibility example, showing custom exception creation, raising, try-except, else, and finally blocks, including type errors and non-numeric ages.

Explore object oriented programming in Python by defining classes and objects with constructors and self, using attributes and methods, and applying inheritance, encapsulation, and polymorphism for reusable, dry code.

Explore Python nested dictionary implementation, accessing and printing values, adding and deleting entries, and iterating through outer and inner dictionaries in a nested structure.

Explore Python statements and comments, including assignment, if and while statements, multi-line statements with backslash continuation, and indentation-driven blocks, plus # comments, multi-line comments and docstrings.

Learn how the pass statement in Python acts as a placeholder with no execution effect, unlike a comment, and how it can reserve future functionality inside loops.

Discover Python generators as simple iterators, distinguishing generator functions from normal ones, and learn to use next and for loops to access values one at a time.

Explore Python decorators and metaprogramming by transforming existing functions with wrapper logic. See practical demonstrations of defining decorators, inner functions, and the @decorator syntax that modify function behavior.

Master the Python while loop, its condition-driven execution, and the break and else flow. Apply these ideas to pattern printing tasks such as dressing-table patterns.

Explore Python conditional logic using if, elif, and else blocks, with emphasis on indentation and nesting, and see age-based examples demonstrating how conditions control program flow.

Explore Biton metrics implementation in Python by building dynamic two-dimensional matrices with lists, using loops, applying indexing including negative indexing, and understanding shallow versus deep copy.

Master Python regular expressions with practical examples that search, match, and replace strings, use wildcards and character classes, and validate formats like emails and phone numbers.

Demonstrate Python list comprehension by converting a string to a list with a for loop, using lambda and conditions. Show transposing a matrix via list comprehension to form new rows.

Master Python recursion concepts, including direct and indirect calls, with Biton support, and explore advantages, disadvantages, and a factorial demonstration.

Learn Python input and output basics with input and print, including int casting, string vs integer operations, and formatting with placeholders, sep and end; import math for power calculations.

Learn how to work with data files in Python by opening in text or binary modes, reading and writing, appending, or using exclusive creation, and always closing to free resources.

Learn Python looping techniques: top, middle, and bottom condition loops; use while with break and simulate do-while. Prompt input, cast to int, and check even or odd.

Explore Python copying concepts by contrasting shallow copy and deep copy with the copy module, showing that = shares references, while shallow copies nest references and deep copies recreate objects.

Learn to define anonymous functions with lambda in Python, and compare def and lambda, then use map and filter to double values and select even numbers in lists.

Explore how assertions use boolean expressions to enforce conditions, such as nonzero divisors, halt the program with an assertion error when false, and serve as a debugging tool with examples.

Explore Python's @property to encapsulate attributes with getter and setter logic, illustrated by a temperature Celsius class that validates against absolute zero and converts to Fahrenheit.

Explore Python closures by defining nested functions, accessing non-local variables in enclosing scopes, and returning inner functions with practical examples.