El razonamiento formal juega un papel importante en la inteligencia artificial. Hay dos maneras principales de formalizar razonamiento: una que enfatiza la deducción (lógica), y otra que enfatiza la incertidumbre (teoría de la probabilidad). En este curso vamos a cubrir una introducción tanto a la lógica (vamos a cubrir tres lógicas) como a la teoría de la probabilidad (vamos a cubrir tres modelos gráficos probabilísticos).
Razonamiento artificial
Razonamiento artificial
This course is part of Introducción a la inteligencia artificial Specialization
Instructors: David A. Rosenblueth
Sponsored by EdgePoint Software
8,549 already enrolled
Gain insight into a topic and learn the fundamentals.
4.1
(104 reviews)
Intermediate level
Some related experience required
20 hours to complete
3 weeks at 6 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
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Assessments
7 assignments
Taught in Spanish
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This course is part of the Introducción a la inteligencia artificial Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 6 modules in this course
En este módulo de razonamiento lógico podrás familiarizarte con la lógica proposicional. Verás una primera manera de formalizar razonamiento y los problemas NP-completos, que son arquetípicos en inteligencia artificial.
What's included
4 videos1 reading1 assignment
En este módulo de razonamiento lógico podrás familiarizarte con la lógica proposicional. Verás una primera manera de formalizar razonamiento y los problemas NP-completos, que son arquetípicos en inteligencia artificial.
What's included
3 videos1 assignment1 programming assignment1 ungraded lab
En este módulo de razonamiento lógico podrás familiarizarte con la lógica temporal para entender los conceptos básicos de los "verificadores de modelos" y con la lógica de predicados para sentar las bases de varias técnicas de inteligencia artificial.
What's included
6 videos2 assignments
En este módulo de razonamiento probabilístico estarás familiarizado con dos modelos gráficos probabilísticos: las redes bayesianas y las cadenas de Markov.
What's included
2 videos1 assignment1 programming assignment1 ungraded lab
En este módulo de razonamiento probabilístico estarás familiarizado con un modelo gráfico probabilístico: los procesos de decisión de Markov.
What's included
2 videos1 assignment1 programming assignment1 ungraded lab
En este módulo de razonamiento probabilístico estarás familiarizado con un modelo gráfico probabilístico: los procesos de decisión de Markov.
What's included
3 videos1 assignment1 programming assignment1 ungraded lab
Instructors
Instructor ratings
4.4 (32 ratings)Offered by
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4.1
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Showing 3 of 104
AG
4
Reviewed on Apr 19, 2021
Está interesante el curso pero debes de saber un poco sobre programación y de matemáticas o te darás de topes.
EB
5
Reviewed on Oct 5, 2020
Es un curso espectacular muy didáctico , se aprenden técnicas y conceptos de gran utilidad. Felicitaciones a la UNAM
AL
5
Reviewed on Dec 20, 2020
Buen curso. Sin embargo, es necesario tener conocimientos técnicos y de programación.
Recommended if you're interested in Computer Science
Universidad Nacional Autónoma de México
Universidad Nacional Autónoma de México
Tecnológico de Monterrey
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