CS50

CS50x en Español - Clase 5 - Estructuras de Datos

CS50x en Español - Clase 3 - Algoritmos

CS50x en Español - Clase 4 - Memoria

CS50x en Español - Clase 1 - C

CS50x en Español - Clase 2 - Arreglos

CS50x en Español - Clase 0 - Scratch

Behind the Scenes: Introduction to Artificial Intelligence with Brian Yu - Chapter 7 - Moving

AI navigation in physical environments relies on path planning algorithms that balance efficiency with real-world constraints. Depth-First Search and Breadth-First Search provide foundational methods for traversing grids, while Dijkstra’s algorithm and A search optimize for cost and speed by incorporating heuristics. M...

Behind the Scenes: Introduction to Artificial Intelligence with Brian Yu - Chapter 6 - Generating

Generative AI functions as a predictive system that produces new content by determining the most likely next element in a sequence. For text, models utilize tokenization and neural networks to predict subsequent words, with "temperature" parameters balancing creativity against statistical likelihood. Techniques such as...

Behind the Scenes: Introduction to Artificial Intelligence with Brian Yu - Chapter 5 - Communicating

Natural language processing enables AI to interpret, communicate, and generate human language, a task complicated by inherent linguistic ambiguity. Effective processing begins with tokenization, breaking text into manageable units like words or sub-words, which are then analyzed using n-grams to identify common sequenc...

Behind the Scenes: Introduction to Artificial Intelligence with Brian Yu - Chapter 4 - Sensing

Artificial intelligence systems interpret sensory data by converting complex inputs into numerical formats that neural networks can analyze. Images are represented as grids of pixel values, where convolutional layers identify hierarchical patterns—from simple edges to complex shapes—while pooling layers reduce data dim...

Introduction to Artificial Intelligence with Brian Yu - Chapter 3 - Analyzing (live, unedited)

Unsupervised learning enables AI to derive insights from raw, unlabeled data through various analytical strategies. Clustering algorithms, such as k-means and DBSCAN, group related items—like photos or music playlists—by identifying inherent patterns rather than relying on predefined categories. Dimensionality reductio...

Introduction to Artificial Intelligence with Brian Yu - Chapter 2 - Predicting (live, unedited)

Artificial intelligence increasingly relies on predictive modeling to handle non-deterministic tasks, moving beyond traditional calculation and storage. Regression problems focus on predicting continuous numeric values, such as device charging times or plant growth, by identifying relationships between input variables ...

Introduction to Artificial Intelligence with Brian Yu - Chapter 1 - Playing (live, unedited)

Artificial intelligence utilizes diverse strategies to simulate human intelligence, with game-playing serving as a foundational research domain. Systems solve problems like Tic-Tac-Toe, Chess, and Go by translating outcomes into numerical values, employing algorithms like Minimax to determine optimal moves. As complexi...

Behind the Scenes - Introduction to Artificial Intelligence with Brian Yu - Chapter 1 - Playing

Artificial intelligence involves building systems that simulate human intelligence by acquiring knowledge, solving problems, and making decisions. Game-playing serves as a foundational environment for testing these capabilities, utilizing algorithms like Minimax to explore decision trees and determine optimal moves. As...

CS50 2D - Lecture 7 - Pokémon

Pokémon-style RPGs rely on a state stack architecture to manage complex transitions between field exploration, menu navigation, and turn-based combat. Unlike traditional state machines that restrict the game to a single active state, a state stack allows for layered rendering, enabling menus or dialogue boxes to appear...

CS50 2D - Lecture 6 - Angry Birds

Box2D provides a robust framework for implementing realistic physics in 2D game development, moving beyond manual velocity and collision calculations. By utilizing rigid bodies—categorized as static, dynamic, or kinematic—developers can simulate complex interactions like gravity, friction, and rotation with minimal mat...

CS50 2D - Lecture 5 - Legend of Zelda

Top-down 2D game development requires specific architectural shifts from traditional side-scrolling platformers, particularly regarding movement, collision detection, and world structure. Implementing a Zelda-inspired engine involves managing bird's-eye view navigation across X and Y axes and utilizing data-driven desi...

CS50 2D - Lecture 4 - Super Mario Bros.

Modeling 2D virtual worlds requires integrating tile maps, camera translation, and state-driven entity behavior. Super Mario Bros. serves as a foundational model for these systems, illustrating how to represent game space through grid-based tile maps and simulate movement using love.graphics.translate. Character animat...

CS50 2D - Lecture 3 - Match 3

Match-3 game development centers on managing tile-based grids through efficient data structures and time-based animations. Implementing fluid movement requires moving beyond simple velocity-based physics toward tweening and timers, which allow for smooth interpolation of tile positions and opacity. A robust Match-3 eng...

CS50 2D - Lecture 2 - Breakout

Breakout development requires a robust state machine to manage complex transitions between menus, gameplay, and victory conditions. Efficient graphic rendering relies on sprite sheets, where texture atlases are partitioned into quads to handle diverse assets like paddles and bricks without overwhelming memory. Collisio...