이 과정에서는 AI 해석 가능성과 투명성의 개념을 소개합니다. 개발자와 엔지니어에게 AI 투명성이 얼마나 중요한지를 설명합니다. 데이터와 AI 모델 모두에서 해석 가능성과 투명성을 구현하는 데 도움이 되는 실용적인 방법과 도구를 살펴봅니다.
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Responsible AI for Developers: Interpretability & Transparency - Español
What you'll learn
Definir la interpretabilidad y la transparencia en relación con la IA
Describir la importancia de la interpretabilidad y la transparencia en la IA
Explorar las herramientas y técnicas que se utilizan para lograr interpretabilidad y transparencia en la IA
Details to know
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July 2024
1 assignment
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Share it on social media and in your performance review
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There are 4 modules in this course
En este módulo, se presenta la estructura del cursos y sus objetivos.
What's included
1 video
En este módulo, nos centramos en la interpretabilidad y transparencia de la IA. Se proporcionan varias técnicas y herramientas para ayudar a lograr la interpretabilidad y transparencia en los modelos de IA y datos.
What's included
9 videos1 assignment1 app item
En este módulo, se proporciona un resumen de todo el curso que cubre los conceptos, las herramientas y las tecnologías más importantes.
What's included
1 video1 reading
Vínculos a archivos PDF de todos los módulos para estudiantes
What's included
3 readings
Instructor
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Recommended if you're interested in Cloud Computing
Google Cloud
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Frequently asked questions
Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.