Python Programming for Beginners with ChatGPT

Create a ChatGPT account or log in with Google or email, starting with the free GPT 3.5, and explore the interface, themes, and chat management.

Discover how the free version of ChatGPT generates text, creates tables, and writes code, including a Python factorial script and practical examples for writers, researchers, and developers.

Explore ChatGPT's paid tools powered by GPT-4, including multimodal image generation with dalle e3, real-time browsing, data analysis in spreadsheets, plugins, translation, and vision to describe uploaded images.

Learn Python with ChatGPT by writing basic code, fixing syntax and logical errors, and debugging through hands-on examples. Explore printing hello world, running scripts, and testing functions to reinforce concepts.

Master fundamental coding principles in Python with ChatGPT, including syntax, data types, control structures, and functions, and practice problem solving with defined inputs, outputs, testing, and debugging.

Discover Python, a high level interpreted language prized for readability and versatility, with libraries like Django and pandas, and learn to write your first hello world program with ChatGPT.

Explore Python modules and how to import and reuse code, and learn to manage dependencies with pip to install libraries like pandas for data frames.

Learn to use Google Colab to write and run Python code for a tic tac toe game with ChatGPT. Discover notebook basics, prompts, and code customization, including a score counter.

Explore comments, escape sequences, and the print statement in Python to annotate code, format output, and interact with users, with practical examples in Google Colab.

Learn how Python operators work, including arithmetic, comparison, and logical operators, with practical exercises and a simple calculator function to perform add, subtract, multiply, and divide.

Explore data handling in Python by examining strings and numbers, using type checks, string operations, and arithmetic with demonstrations of common errors and data type behavior.

Explore Python type casting by converting between integers, floats, and strings with practical examples and see how to apply conversions for user input, data processing, and formatting.

Take user input in Python with the input function, convert strings to int or float, and handle value errors with try and except in Google Colab.

Learn how Python strings work, from creating strings with single, double, or triple quotes to indexing and immutability, with live demonstrations guided by ChatGPT.

Explore string operations in Python, including concatenation and repetition with plus and multiply operators, and learn slicing with start-end indices and negative indexing to extract substrings, all demonstrated with ChatGPT.

Master Python string methods like upper, lower, strip, replace, split, and join to manipulate and analyze text, normalize data, and handle user input with ChatGPT demos.

Explore if-else statements in Python using ChatGPT to understand elif and nested if-else with practical examples and an exercise on height.

Learn python pattern matching with match case statements from python 3.10, using chatgpt to grasp basic syntax and advanced patterns, including if conditions within case blocks.

Automate repetitive tasks by iterating over lists with for loops in Python, printing each item and applying conditional logic. Explore nested loops, numbers, and ai prompts to handle tasks efficiently.

Master while loops in Python by exploring condition-driven repetition through practical examples, user-input prompts, prime-number demos, and handling infinity loops with break and exit conditions.

Master break and continue in python loops with live examples, showing how to exit and skip iterations in for and while loops.

Explore the core concept of Python functions by defining, calling, and encapsulating logic to return results. See how parameters, conditionals, loops, and multiple functions enable reusable, modular code.

Learn to combine text and calculations in Python by concatenating strings with numbers using str and f-strings, format bills with subtotals and discounts, and perform looped calculations.

Learn to build dynamic llms prompts with variables, creating reusable templates that personalize greetings, weather, and recommendations, using conditional logic and multiple inputs.

Explore local and global variables in Python, with definitions, examples, and live demos, learn how the global keyword enables cross-scope modification, and discover best practices for avoiding unintended changes.

Learn to create and manage a Python task list using lists, append, zero indexed, printing, and removal. Automate updates with a for loop.

Prioritize tasks using Python dictionaries to assign priorities. Leverage AI to analyze urgency, importance, and deadlines and automate reminders and daily plans.

Master tuples in Python for beginners by learning creation, indexing, immutability, and operations like concatenation, repetition, and unpacking, plus count and index methods.

Explore sets in python with chatgpt guidance, learn to add and remove items, test membership, and perform union, intersection, and difference, plus disjoint, subset, and superset checks, and frozen sets.

Master data comparison in Python using comparison operators to evaluate numbers, strings, lists, and dictionaries, producing boolean results and combining checks with and, or, not for flow control.

Learn to guide ai decision making using rule-based, machine learning, and reinforcement learning approaches, define constraints and objectives, and evaluate performance for reliable outcomes.

Explore Python recursion with base cases, recursive calls, and examples like factorial and Fibonacci, using ChatGPT to demo concepts, stack frames, and strategies to avoid stack overflow.

Learn to handle errors in Python with try/except/else/finally, create custom exceptions, and implement graceful recovery, debugging and logging through live demos and practical examples.

Learn how the Python enumerate function adds an index to iterables, returning index-value pairs for lists, strings, and more. Use in for loops with adjustable start values and practical examples.

Master Python virtual environments to isolate project dependencies, avoid package conflicts, and ensure reproducible setups, with setup steps, activation, deactivation, and using requirements.txt.

Discover how the import statement brings in modules and packages, using from and as aliases and dot notation, and reveal the internal loading process from sys.path to top-level code execution.

Explore how if __name__ == '__main__' controls code execution in Python scripts, whether run directly or imported as modules, with practical examples using ChatGPT and data processing.

Explore Python's os module to manage files and directories, access and set environment variables, and run system commands, with live demos of listing directories and path operations.

Explore Python lambda functions, anonymous one-expression functions used with map, filter, reduce, and sorting. See practical examples with ChatGPT to create and test short functions in lists.

Learn to read, write, and append data in Python using the built-in open function, and explore text, csvs, JSON, and binary files with safe, concise file handling.

Learn how to read, modify, and save text files with Python, including updating lines, appending data, replacing text, and handling large files efficiently.

Learn how to merge text, CSV, binary, and JSON files with Python, guided by ChatGPT for interactive code and path handling in practical data consolidation.

Learn to streamline Excel processing with Python and ChatGPT by automating tasks, cleaning data, merging files, and generating reports using Pandas and Openpyxl.

Explore what OOP is in Python, including classes, objects, methods, and attributes, and learn how encapsulation, inheritance, and polymorphism boost reusability, scalability, and code organization.

Explore Python classes and objects to master object-oriented programming, using ChatGPT to interactively model blueprints, instances, encapsulation, inheritance, and polymorphism.

Explore Python constructors, use the init method to initialize object attributes, and learn through examples like person and book classes, including defaults, validation, and using ChatGPT to refine code.

Explore decorators in Python to modify function behavior without changing code. Use chatgpt-guided examples to add caching, timing, logging, and access control for cleaner, reusable code.

Explore getters and setters in Python to control access to private attributes, enforce validation, and encapsulate data through examples and ChatGPT-assisted demos.

Explore python inheritance to build modular, reusable code by creating subclasses from a base class, embracing hierarchical relationships, overriding methods, and using super to customize behavior while preserving polymorphism.

Explore how Python uses naming conventions to implement access modifiers: public, protected, and private. See car and bank account demos, plus name mangling and benefits like encapsulation and maintainability.

Explore static methods in Python and their difference from instance methods, with examples of utility functions, factory methods, and real-world scenarios like e-commerce discounts.

Explore the difference between instance variables and class variables in Python with definitions, examples, and live coding demos guided by ChatGPT in Google Colab.

Master class methods as alternative constructors in Python, enabling flexible and readable object creation from dictionaries, CSV strings, and JSON data via factory-inspired patterns.

Explore operator overloading in Python to redefine plus, minus, and other operators for user-defined classes, using dunder methods and practical vector, rational, and complex number examples.

Single inheritance in Python lets a child class inherit from a single base class, reuse code, and extend functionality using super, illustrated with vehicle and car.

Explore multiple and multilevel inheritance in Python, including the MRO, diamond problem, and super-based initialization, with practical hybrid inheritance examples like a vehicle management system.

Explore hybrid and hierarchical inheritance in Python, defining how combining multiple and multi-level inheritance creates flexible class structures, with ChatGPT-guided examples and MRO-driven method resolution in a library system.

Explore map, filter, and reduce in Python to process iterables concisely within functional programming. See examples like squaring numbers, filtering strings, and summing totals in a data processing pipeline.

Learn to work with Python's time module to measure elapsed time, pause execution, format timestamps, and schedule tasks, using functions like time, sleep, perf_counter, and strftime.

Master Python's requests module to send HTTP requests and interact with web APIs. Learn to handle responses, URL parameters, JSON and form data, sessions, errors, and authentication.

Learn how Python generators enable memory-efficient data processing by iterating over data on demand with yield, creating generator functions, and using generator expressions and chaining.

Discover how function caching speeds Python programs by storing expensive call results for repeated inputs, using functools lru_cache, maxsize, and cache management for recursion and fibonacci examples.

Master regular expressions in Python with the re module to search, replace, find all, and split text, using literals, metacharacters, character classes, quantifiers, anchors, and escaping.

Explore asynchronous input/output in Python with ChatGPT, learning about event loops, coroutines, and async/await to run concurrent tasks efficiently in I/O-bound applications.

Explore multithreading and multiprocessing in Python for high-performance apps, comparing shared-memory threads and separate-process parallelism, with io-bound versus cpu-bound use cases and live demos.