A complete hands-on NumPy learning repository covering array creation, indexing, slicing, reshaping, broadcasting, mathematical operations, boolean indexing, aggregation functions, and real-world use cases.

A selection of useful array operations

A structured collection of Jupyter notebooks exploring NumPy from the ground up; covering array creation, manipulation, broadcasting, indexing, and data visualization for scientific computing and data analysis.

🧠 A fast-paced image-matching game built with React.js. Match images by category before time runs out. Test your memory and reflexes—like Fruit Ninja, but with logic! ⏱️🍍🐘🌍

HomeWork 6: A C# program that manipulates arrays by resizing, adding, or removing elements. Demonstrates dynamic array operations and input validation.

A C++-based scripting prototype that supports let, function, mixed-type arrays, dynamic operations like console.log, readline(), and vector-like methods — all made possible through operator overloading and custom abstractions.

Notebook to learn NumPy basics, arrays, and operations for data analysis.

Basic NumPy array creation and arithmetic operations in Python.

A Node.js CLI application for processing test scores, calculating averages, and validating input.

Proyecto 4 - Programación 2

A collection of 100 array-based coding problems in Python, each solved using loops and functions, ideal for learning, practice, and technical interview prep.

A number evaluation script that identifies even, odd, and prime numbers in an array, along with calculating the sum of primes and determining the maximum and minimum values.

The Address Book Project is a console-based application written in C designed to manage personal contacts. It allows users to: Add Contacts: Add a contact with a name, phone numbers, and email addresses. Search Contacts: Search for contacts by name, phone number, or email. Edit Contacts & Modify

menu-driven numpy calculator that performs arithmetic, statistical, and array manipulation operations with execution time tracking.

This comprehensive course covers the fundamental concepts and practical techniques of NumPy, the essential library for numerical computing in Python. Learn to create, manipulate, and analyze arrays efficiently.

🧮 Explore, manipulate, and visualize data with NumPy to enhance your Python skills in scientific computing and data analysis.