Fundamentos del Aprendizaje Profundo

Resumen

Fundamentals of Deep Learning is a structured course designed for developers, data professionals, and AI enthusiasts who want to build a strong foundation in neural networks and modern deep learning techniques. This course focuses on core deep learning principles, including how artificial neurons work, forward and backward propagation, gradient descent optimization, activation functions, multi-class classification, Convolutional Neural Networks (CNNs), and transfer learning.

Through a progressive and practical learning path, you will gain hands-on experience training neural networks, evaluating model performance, and applying deep learning techniques to real-world image classification problems. The course bridges theory and implementation, helping you understand not just how models work, but why they work.

Whether you are beginning your journey in artificial intelligence or preparing for advanced machine learning and cloud-based AI roles, this course equips you with the conceptual clarity and practical skills required to confidently build and evaluate deep learning models. This course includes approximately 3:

30–4:

00 hours of video lectures, combining foundational theory with step-by-step demonstrations.

It is divided into focused modules that progressively develop your understanding of neural network architecture and applied deep learning techniques. To reinforce learning, each module includes quizzes and in-video practice questions that test conceptual understanding and practical application. 📘 Module 1:

Foundations of Deep Learning and Neural Networks 🧠 Module 2:

Deep Learning Models, Computer Vision, and Transfer Learning

Programa

• Fundamentos del Aprendizaje Profundo y Redes Neuronales
Bienvenido a la Semana 1 del curso Fundamentos del Aprendizaje Profundo. Esta semana, te introducirás en los conceptos básicos del aprendizaje profundo y establecerás expectativas claras sobre lo que aprenderás a lo largo del curso. Comenzaremos entendiendo qué es el aprendizaje profundo y cómo encaja dentro de los campos más amplios de la inteligencia artificial y el aprendizaje automático.
• Modelos de Aprendizaje Profundo, Visión por Computadora y Aprendizaje por Transferencia
Bienvenido a la Semana 2 del curso Fundamentos del Aprendizaje Profundo. Esta semana se centra en la aplicación práctica de técnicas de aprendizaje profundo a problemas del mundo real, con un énfasis en el entrenamiento de modelos, la evaluación y las arquitecturas modernas de redes neuronales.

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Impartido por

Whizlabs Instructor

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Materias

Computer Science