AI Infrastructure Cloud Tpus Es Course Syllabus

Este curso especializado ofrece una visión integral de la infraestructura de IA con enfoque en las Unidades de Procesamiento de Tensor en la nube (Cloud TPUs), desarrollado por Google. A lo largo de aproximadamente 15-20 horas, los estudiantes explorarán los fundamentos del cómputo de alto rendimiento, redes neuronales, diseño de sistemas de IA, procesamiento del lenguaje natural, visión por computadora y despliegue en entornos de producción. El curso combina teoría, ejercicios prácticos y proyectos guiados con retroalimentación del instructor, ideal para profesionales técnicos que buscan dominar la infraestructura de IA a escala.

Module 1: Foundations of Computing & Algorithms

Estimated time: 2 hours

• Introduction to key concepts in foundations of computing & algorithms
• Review of tools and frameworks commonly used in practice
• Hands-on exercises applying foundations of computing & algorithms techniques
• Guided project work with instructor feedback

Module 2: Neural Networks & Deep Learning

Estimated time: 2.5 hours

• Hands-on exercises applying neural networks & deep learning techniques
• Interactive lab: Building practical solutions
• Discussion of best practices and industry standards
• Review of tools and frameworks commonly used in practice

Module 3: AI System Design & Architecture

Estimated time: 1.5 hours

• Introduction to key concepts in ai system design & architecture
• Hands-on exercises applying ai system design & architecture techniques
• Discussion of best practices and industry standards
• Review of tools and frameworks commonly used in practice

Module 4: Natural Language Processing

Estimated time: 3 hours

• Introduction to key concepts in natural language processing
• Hands-on exercises applying natural language processing techniques
• Case study analysis with real-world examples
• Guided project work with instructor feedback

Module 5: Computer Vision & Pattern Recognition

Estimated time: 4 hours

• Introduction to key concepts in computer vision & pattern recognition
• Interactive lab: Building practical solutions
• Guided project work with instructor feedback
• Discussion of best practices and industry standards

Module 6: Deployment & Production Systems

Estimated time: 3.5 hours

• Introduction to key concepts in deployment & production systems
• Case study analysis with real-world examples
• Assessment: Quiz and peer-reviewed assignment

Prerequisites

• Conocimientos previos en computación en la nube
• Fundamentos de inteligencia artificial y aprendizaje automático
• Experiencia técnica en programación y sistemas

What You'll Be Able to Do After

• Evaluate model performance using appropriate metrics and benchmarks
• Apply computational thinking to solve complex engineering problems
• Implement intelligent systems using modern frameworks and libraries
• Design algorithms that scale efficiently with increasing data
• Understand core AI concepts including neural networks and deep learning