Artificial Intelligence (AI)
date_range Начало21 сентября 2020 г.
event_note Завершение 21 декабря 2020 г.
list 12 последовательности
assignment Уровень : Продвинутый
chat_bubble_outline Язык: английский
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Важная информация

credit_card Обучение платное
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timer 96 час(ы) курса

Резюме

What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common?

They are all complex real world problems being solved with applications of intelligence (AI).

This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.

You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.

Hands on experience will be gained by building a basic search agent. Adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.

  • Introduction to Artificial Intelligence and intelligent agents, history of Artificial Intelligence
  • Building intelligent agents (search, games, logic, constraint satisfaction problems)
  • Machine Learning algorithms
  • Applications of AI (Natural Language Processing, Robotics/Vision)
  • Solving real AI problems through programming with Python

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Специальные требования

Students are required to have some basic of Python programming and an understanding of probability. Homework assignments will have a programming component in Python. The course offers an excellent opportunity for students to dive into Python while solving AI problems and learning its applications.

  • Linear algebra (vectors, matrices, derivatives)
  • Calculus
  • Basic probability theory
  • Python programming

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Программа

Week 1: Introduction to AI, history of AI, course logistics
Week 2: Intelligent agents, uninformed search
Week 3: Heuristic search, A algorithm
__Week 4:
Adversarial search, games
__Week 5:
Constraint Satisfaction Problems
__Week 6:
Machine Learning: Basic concepts, linear models, perceptron, K nearest neighbors
__Week 7:
Machine Learning: advanced models, neural networks, SVMs, decision trees and unsupervised learning
__Week 8:
Markov decision processes and reinforcement learning
__Week 9:
Logical Agent, propositional logic and first order logic
__Week 10:
AI applications (NLP)
__Week 11:
AI applications (Vision/Robotics)
__Week 12:
* Review and Conclusion

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Пользователи

Ansaf Salleb-Aouissi
Department of Computer Science
Columbia University

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Разработчик

Columbia University
For more than 250 years, Columbia has been a leader in higher education in the nation and around the world. At the core of our wide range of academic inquiry is the commitment to attract and engage the best minds in pursuit of greater human understanding, pioneering new discoveries and service to society.
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Платформа

Edx

EdX est une plateforme d'apprentissage en ligne (dite FLOT ou MOOC). Elle héberge et met gratuitement à disposition des cours en ligne de niveau universitaire à travers le monde entier. Elle mène également des recherches sur l'apprentissage en ligne et la façon dont les utilisateurs utilisent celle-ci. Elle est à but non lucratif et la plateforme utilise un logiciel open source.

EdX a été fondée par le Massachusetts Institute of Technology et par l'université Harvard en mai 2012. En 2014, environ 50 écoles, associations et organisations internationales offrent ou projettent d'offrir des cours sur EdX. En juillet 2014, elle avait plus de 2,5 millions d'utilisateurs suivant plus de 200 cours en ligne.

Les deux universités américaines qui financent la plateforme ont investi 60 millions USD dans son développement. La plateforme France Université Numérique utilise la technologie openedX, supportée par Google.

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