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David A. Rosenblueth
and
Stalin Muñoz Gutiérrez
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).
Read more
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).
Read more
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).
Algunas tareas requieren programación básica en Python: El alumno deberá completar código al que se le ha eliminado una parte.
Register for this course and see more details by visiting:
OpenCourser.com/course/ezarj5/razonamiento
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Syllabus
Lógica proposicional
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.
Read more
Syllabus
Lógica proposicional
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.
Read more
Lógica proposicional parte 2
Lógica temporal y Lógica de predicados
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.
Teoría de la probabilidad
En este módulo de razonamiento probabilístico estarás familiarizado con dos modelos gráficos probabilísticos: las redes bayesianas y las cadenas de Markov.
Teoría de la probabilidad (parte 2)
En este módulo de razonamiento probabilístico estarás familiarizado con un modelo gráfico probabilístico: los procesos de decisión de Markov.
Teoría de la probabilidad (parte 3)
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Combines deductive and probabilistic reasoning, which broadens learners' perspective of formal reasoning
Introduces three distinct logics, providing a rounded understanding of logical reasoning and problem-solving
Provides a solid foundation in both logic and probability theory, making it suitable for learners interested in artificial intelligence
Requires basic programming skills in Python, which may be a barrier for some learners
Covers a wide range of topics within logic and probability, ensuring a comprehensive understanding of these fundamental concepts
Save this course
Save Razonamiento artificial to your list so you can find it easily later:
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Reviews summary
Razonamiento artificial: complejo pero gratificante
El curso "Razonamiento Artificial" brinda una sólida introducción tanto a la lógica como a la teoría de la probabilidad. Recibe elogios por su contenido informativo y bien explicado, pero también críticas por su complejidad y tareas de programación poco claras. Los estudiantes valoran los desafíos prácticos, pero recomiendan tener una base en matemáticas y programación antes de comenzar.
El curso puede ser complejo, pero ofrece una experiencia de aprendizaje gratificante y mejora las habilidades de lógica y probabilidad.
"Excelente el contenido, me obligó a consultar en otras fuentes y aprendí mucho."
"Excelente curso! el segundo mejor de esta especialización solo después del curso de algoritmos de búsqueda"
"Muy buen curso, es un excelente reto"
Los moderadores rara vez se involucran en los foros, lo que genera frustración cuando los estudiantes buscan ayuda.
"Falla mucho la parte del mantenimiento del curso ya que, casi no se ven los moderadores en los foros"
"En las tareas de programación las instrucciones del formato que se debe subir no es claro del todo y no existe interacción alguna por los moderadores"
Las tareas de programación pueden ser confusas y carecen de instrucciones claras, lo que lleva a la frustración.
"Para la tarea de programación en redes bayesianas deberían dar más hints sobre cómo obtener los resultados."
"Como recomendación deberían especificar mejor lo que quieren en el archivo de los laboratorios"
"Las tareas pueden ser un poco confusas para algunas personas"
Los primeros módulos del curso pueden ser muy complejos y difíciles de entender, especialmente para los principiantes.
"Muy complejo de entender, especialmente las dos primeras semanas. No es para publico general."
"En las entregas de las tareas de programación necesitan ser más específicos en el formato. Creo que la información es buena y los vídeos están muy bien hechos; sin embargo, hizo falta más énfasis en algunos temas."
"El curso tiene buenos temas y son muy importantes, sin embargo en los primeros pasos las explicaciones son algo cripticas y los video no se acoplan a una sola terminología lo que lleva un poco a confusiones."
El curso requiere una sólida base en matemáticas y programación para tener éxito.
"Buen Curso. Sin embargo, es necesario tener conocimientos técnicos y de programación."
"Es muy interesante en ocasiones complejo. En el ejercicio del modulo 6 no se especifica como debe ser la salida lo que hace que uno pierda tiempo sin necesidad."
"El curso es interesante y práctico, solo que se requiere de conocimientos de programación para acreditar las actividades."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Razonamiento artificial with these
activities:
Revisit logic basics
Show steps
Prepare yourself for more advanced logic topics by brushing up on your basics.
Browse courses on
Logic
Show steps
-
Review your notes or textbooks on propositional logic.
-
Go over practice problems and exercises to test your understanding.
Revise the basics of probability theory
Show steps
Reviewing basic probability theory will strengthen your foundation for the more advanced concepts covered in this course.
Browse courses on
Probability Theory
Show steps
-
Review the concepts of sample space, events, and probability.
-
Practice calculating probabilities using conditional probability and the multiplication rule.
-
Solve problems involving independent events.
Read 'Introduction to Logic' by Irving Copi
Show steps
This book provides a comprehensive overview of logic, including both propositional and predicate logic. It will supplement the course material and enhance your understanding of the subject.
View
Introducción a la lógica
on Amazon
Show steps
-
Read the chapters on propositional logic and predicate logic.
-
Work through the exercises at the end of each chapter.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Organize and review your course notes
Show steps
Taking the time to organize and review your course notes will help you solidify your understanding of the material and identify areas that need further attention.
Show steps
-
Gather all of your course notes, including lecture notes, slides, and handouts.
-
Organize your notes by topic or module.
-
Review your notes regularly, especially before exams.
Share your knowledge by mentoring a peer
Show steps
Deepen your understanding of the course material by helping others learn.
Show steps
-
Reach out to a peer who is struggling with the material or who would like additional support.
-
Review the course material together and answer any questions your peer may have.
-
Provide encouragement and support to your peer as they work through the course.
Solve practice problems on propositional logic
Show steps
Solving practice problems on propositional logic will reinforce your understanding of logical reasoning and improve your problem-solving skills.
Browse courses on
Propositional Logic
Show steps
-
Find a collection of practice problems on propositional logic.
-
Work through the problems step-by-step, using truth tables or other techniques to evaluate logical expressions.
-
Review your solutions and identify areas where you need improvement.
Solve probability problems
Show steps
Sharpen your probability skills by working through a variety of problems.
Browse courses on
Probability
Show steps
-
Find practice problems online or in textbooks.
-
Work through the problems step-by-step, checking your answers against the provided solutions.
Follow tutorials on Markov chains
Show steps
Tutorials on Markov chains will provide hands-on experience and deepen your understanding of their properties and applications.
Browse courses on
Markov Chains
Show steps
-
Find tutorials that cover the basics of Markov chains, such as state transitions and transition probabilities.
-
Work through examples to practice applying Markov chain concepts.
-
Explore more advanced tutorials on topics such as hidden Markov models.
Participate in a study group for temporal logic
Show steps
Collaborating with peers in a study group will provide opportunities to discuss concepts, solve problems, and reinforce your understanding of temporal logic.
Show steps
-
Find a study group or create one with classmates.
-
Meet regularly to discuss the course material, work on assignments, and prepare for exams.
-
Take turns presenting concepts and leading discussions.
Design a logical circuit using propositional logic
Show steps
Designing a logical circuit using propositional logic will demonstrate your understanding of how logical concepts can be applied in practical settings.
Browse courses on
Propositional Logic
Show steps
-
Choose a simple logical function to implement, such as an AND gate or an OR gate.
-
Design the circuit using logic gates and wires.
-
Simulate the circuit to verify its functionality.
Explore advanced logic concepts
Show steps
Expand your knowledge of logic by exploring more advanced concepts.
Show steps
-
Search for online tutorials on temporal logic, predicate logic, or modal logic.
-
Follow the tutorials, taking notes and completing any practice exercises.
Build a logic-based decision-making system
Show steps
Apply your knowledge of logic to create a practical decision-making system.
Show steps
-
Define the problem you want to solve and the decisions that need to be made.
-
Design a logic-based model to represent the problem and the possible outcomes.
-
Implement your model using a logic programming language or a general-purpose programming language with logic libraries.
-
Test and evaluate your system to ensure its accuracy and efficiency.
Develop a probabilistic model for a real-world scenario
Show steps
Demonstrate your understanding of probabilistic models by applying them to a real-world problem.
Browse courses on
Probabilistic Graphical Models
Show steps
-
Identify a real-world scenario that can be modeled probabilistically.
-
Formulate a probabilistic model to represent the scenario, including the relevant variables and their relationships.
-
Collect data and use it to estimate the parameters of your model.
-
Validate your model by testing its predictions against real-world observations.
-
Document your model and its results in a technical report or presentation.
Revisit logic basics
Show steps
Prepare yourself for more advanced logic topics by brushing up on your basics.
Browse courses on
Logic
Show steps
Show steps
Show steps
- Review your notes or textbooks on propositional logic.
- Go over practice problems and exercises to test your understanding.
Revise the basics of probability theory
Show steps
Reviewing basic probability theory will strengthen your foundation for the more advanced concepts covered in this course.
Browse courses on
Probability Theory
Show steps
Show steps
Show steps
- Review the concepts of sample space, events, and probability.
- Practice calculating probabilities using conditional probability and the multiplication rule.
- Solve problems involving independent events.
Read 'Introduction to Logic' by Irving Copi
Show steps
This book provides a comprehensive overview of logic, including both propositional and predicate logic. It will supplement the course material and enhance your understanding of the subject.
View
Introducción a la lógica
on Amazon
Show steps
Show steps
Show steps
- Read the chapters on propositional logic and predicate logic.
- Work through the exercises at the end of each chapter.
Ten other activities
Expand to see all activities and additional details
Show all 13 activities
Organize and review your course notes
Show steps
Taking the time to organize and review your course notes will help you solidify your understanding of the material and identify areas that need further attention.
Show steps
Show steps
Show steps
- Gather all of your course notes, including lecture notes, slides, and handouts.
- Organize your notes by topic or module.
- Review your notes regularly, especially before exams.
Share your knowledge by mentoring a peer
Show steps
Deepen your understanding of the course material by helping others learn.
Show steps
Show steps
Show steps
- Reach out to a peer who is struggling with the material or who would like additional support.
- Review the course material together and answer any questions your peer may have.
- Provide encouragement and support to your peer as they work through the course.
Solve practice problems on propositional logic
Show steps
Solving practice problems on propositional logic will reinforce your understanding of logical reasoning and improve your problem-solving skills.
Browse courses on
Propositional Logic
Show steps
Show steps
Show steps
- Find a collection of practice problems on propositional logic.
- Work through the problems step-by-step, using truth tables or other techniques to evaluate logical expressions.
- Review your solutions and identify areas where you need improvement.
Solve probability problems
Show steps
Sharpen your probability skills by working through a variety of problems.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Find practice problems online or in textbooks.
- Work through the problems step-by-step, checking your answers against the provided solutions.
Follow tutorials on Markov chains
Show steps
Tutorials on Markov chains will provide hands-on experience and deepen your understanding of their properties and applications.
Browse courses on
Markov Chains
Show steps
Show steps
Show steps
- Find tutorials that cover the basics of Markov chains, such as state transitions and transition probabilities.
- Work through examples to practice applying Markov chain concepts.
- Explore more advanced tutorials on topics such as hidden Markov models.
Participate in a study group for temporal logic
Show steps
Collaborating with peers in a study group will provide opportunities to discuss concepts, solve problems, and reinforce your understanding of temporal logic.
Show steps
Show steps
Show steps
- Find a study group or create one with classmates.
- Meet regularly to discuss the course material, work on assignments, and prepare for exams.
- Take turns presenting concepts and leading discussions.
Design a logical circuit using propositional logic
Show steps
Designing a logical circuit using propositional logic will demonstrate your understanding of how logical concepts can be applied in practical settings.
Browse courses on
Propositional Logic
Show steps
Show steps
Show steps
- Choose a simple logical function to implement, such as an AND gate or an OR gate.
- Design the circuit using logic gates and wires.
- Simulate the circuit to verify its functionality.
Explore advanced logic concepts
Show steps
Expand your knowledge of logic by exploring more advanced concepts.
Show steps
Show steps
Show steps
- Search for online tutorials on temporal logic, predicate logic, or modal logic.
- Follow the tutorials, taking notes and completing any practice exercises.
Build a logic-based decision-making system
Show steps
Apply your knowledge of logic to create a practical decision-making system.
Show steps
Show steps
Show steps
- Define the problem you want to solve and the decisions that need to be made.
- Design a logic-based model to represent the problem and the possible outcomes.
- Implement your model using a logic programming language or a general-purpose programming language with logic libraries.
- Test and evaluate your system to ensure its accuracy and efficiency.
Develop a probabilistic model for a real-world scenario
Show steps
Demonstrate your understanding of probabilistic models by applying them to a real-world problem.
Browse courses on
Probabilistic Graphical Models
Show steps
Show steps
Show steps
- Identify a real-world scenario that can be modeled probabilistically.
- Formulate a probabilistic model to represent the scenario, including the relevant variables and their relationships.
- Collect data and use it to estimate the parameters of your model.
- Validate your model by testing its predictions against real-world observations.
- Document your model and its results in a technical report or presentation.
Career center
Learners who complete Razonamiento artificial will develop knowledge and skills
that may be useful to these careers:
Artificial Intelligence Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer designs, builds, and deploys artificial intelligence solutions. This course may help build a foundation in artificial intelligence by developing skills in logic and probability. These skills are foundational in artificial intelligence. This course may be especially helpful for those who wish to specialize in logical or probabilistic artificial intelligence.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, builds, and deploys machine learning models. This course may be helpful in developing skills in logic and probability, which are foundational in machine learning. This course may be especially helpful for those who wish to specialize in logical or probabilistic machine learning.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical methods to solve complex problems in business and industry. This course may be helpful in developing skills in logic and probability, which are used in operations research. This course may be especially helpful for those who wish to specialize in logical or probabilistic operations research.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data to extract meaningful insights. This course may be helpful in developing skills in logic and probability, which are used in statistics. This course may be especially helpful for those who wish to specialize in logical or probabilistic statistics.
Financial Analyst
Financial Analyst
A Financial Analyst uses data and analytical methods to help businesses make better financial decisions. This course may be helpful in developing skills in logic and probability, which are used in financial analysis. This course may be especially helpful for those who wish to specialize in logical or probabilistic financial analysis.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses data and analytical methods to help businesses make better investment decisions. This course may be helpful in developing skills in logic and probability, which are used in quantitative analysis. This course may be especially helpful for those who wish to specialize in logical or probabilistic quantitative analysis.
Actuary
Actuary
An Actuary uses mathematical and statistical methods to assess risk and uncertainty. This course may be helpful in developing skills in logic and probability, which are used in actuarial science. This course may be especially helpful for those who wish to specialize in logical or probabilistic actuarial science.
Psychologist
Psychologist
A Psychologist studies the human mind and behavior. This course may be helpful in developing skills in logic and probability, which are used in psychology. This course may be especially helpful for those who wish to specialize in logical or probabilistic psychology.
Economist
Economist
An Economist uses data and analytical methods to study the economy and make predictions about its future performance. This course may be helpful in developing skills in logic and probability, which are used in economics. This course may be especially helpful for those who wish to specialize in logical or probabilistic economics.
Political Scientist
Political Scientist
A Political Scientist studies politics and government. This course may be helpful in developing skills in logic and probability, which are used in political science. This course may be especially helpful for those who wish to specialize in logical or probabilistic political science.
Business Analyst
Business Analyst
A Business Analyst uses data and analytical methods to help businesses make better decisions. This course may be helpful in developing skills in logic and probability, which are used in business analysis. This course may be especially helpful for those who wish to specialize in logical or probabilistic business analysis.
Data Scientist
Data Scientist
A Data Scientist collects, analyzes, and interprets data to extract meaningful insights. This course may be helpful in developing skills in logic and probability, which are used in data analysis and interpretation. This course may be especially helpful for those who wish to specialize in probabilistic data science.
Neuroscientist
Neuroscientist
A Neuroscientist studies the brain and nervous system. This course may be helpful in developing skills in logic and probability, which are used in neuroscience. This course may be especially helpful for those who wish to specialize in logical or probabilistic neuroscience.
Sociologist
Sociologist
A Sociologist studies human society and social behavior. This course may be helpful in developing skills in logic and probability, which are used in sociology. This course may be especially helpful for those who wish to specialize in logical or probabilistic sociology.
Software Engineer
Software Engineer
A Software Engineer designs, builds, and deploys software applications. This course may be helpful in developing skills in logic and probability, which are used in software design and development. This course may be especially helpful for those who wish to specialize in logical or probabilistic software engineering.
For more career information including salaries, visit:
OpenCourser.com/course/ezarj5/razonamiento
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Razonamiento artificial.
Provides a comprehensive overview of artificial intelligence, including both logical and probabilistic reasoning. It valuable reference for students and practitioners alike.
Este libro proporciona una visión general completa de la inteligencia artificial, incluidos el razonamiento lógico y probabilístico. Es una valiosa referencia para estudiantes y profesionales.
Este libro proporciona una visión general completa de la inteligencia artificial, con un enfoque en métodos modernos. Es una valiosa referencia para estudiantes y profesionales interesados en el desarrollo de sistemas inteligentes.
Ofrece una visión general integral del campo de la inteligencia artificial, incluyendo técnicas de razonamiento lógico y probabilístico tratadas en el curso.
Este libro proporciona una introducción a la probabilidad y la estadística, con un enfoque en aplicaciones en ingeniería y ciencias. Es una buena opción para estudiantes que desean aprender los conceptos básicos de probabilidad y estadística.
Este libro proporciona una introducción a la probabilidad y la estadística, con un enfoque en aplicaciones en ingeniería y ciencias. Es una buena opción para estudiantes que desean aprender los conceptos básicos de probabilidad y estadística.
Este libro proporciona una introducción a la teoría de la probabilidad y la estadística, con un enfoque en aplicaciones en ingeniería y ciencias. Es una buena opción para estudiantes que desean aprender los conceptos básicos de teoría de la probabilidad y estadística.
Este libro proporciona una introducción a la teoría de la decisión, con un enfoque en aplicaciones en ingeniería y ciencias. Es una buena opción para estudiantes que desean aprender los conceptos básicos de teoría de la decisión.
Provides a clear and concise introduction to logic, with a focus on applications in computer science. It good choice for students who want to learn the basics of logic.
Provides a comprehensive introduction to probability and statistics, with a focus on applications in computer science. It valuable resource for students who want to learn the basics of probability and statistics.
Provides a comprehensive introduction to Bayesian reasoning and machine learning. It valuable resource for students who want to learn the basics of Bayesian reasoning and machine learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ezarj5/razonamiento
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Effort
6 semanas de estudio, 3 a 5 horas por semana.
Level
Intermediate
Via
Coursera
Institution
Universidad Nacional Autónoma de México
Instructors
David A. Rosenblueth
Stalin Muñoz Gutiérrez
Language
Español
Good to know
Combines deductive and probabilistic reasoning, which broadens learners' perspective of formal reasoning
Introduces three distinct logics, providing a rounded understanding of logical reasoning and problem-solving
Provides a solid foundation in both logic and probability theory, making it suitable for learners interested in artificial intelligence
Requires basic programming skills in Python, which may be a barrier for some learners
Covers a wide range of topics within logic and probability, ensuring a comprehensive understanding of these fundamental concepts
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