Artificial Intelligence (Hochschule Ravensburg-Weingarten Univ.). Instructor: Professor Wolfgang Ertel.

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September 25, 2023

English

English [CC]

Description

This course provides an overview of the field of Artificial Intelligence (AI) with its current widespread ramifications. Topics covered in this course include: search, game playing, problem solving; reasoning with Bayesian networks; machine learning and data mining; neural networks; reinforcement learning. And some of the topics will be dealt with in more detail.

Course Curriculum

  • Lecture 01 – Introduction Unlimited
  • Lecture 02 – Search, Games and Problem Solving Introduction Unlimited
  • Lecture 03 – Uninformed Search: Breadth-First Search, Depth-First Search Unlimited
  • Lecture 04 – Heuristic Search: Greedy Search, A*-Search, IDA*-Search Unlimited
  • Lecture 05 – Games with Opponents, Heuristic Evaluation Functions Unlimited
  • Lecture 06 – Computing with Probabilities, The Principle of Maximum Entropy Unlimited
  • Lecture 07 – The Maximum Entropy Method Unlimited
  • Lecture 08 – The Maximum Entropy Method, LEXMED Unlimited
  • Lecture 09 – LEXMED, Reasoning with Bayesian Networks Unlimited
  • Lecture 10 – Reasoning with Bayesian Networks Unlimited
  • Lecture 11 – Reasoning with Bayesian Networks, Machine Learning and Data Mining Unlimited
  • Lecture 12 – The Perceptron, The Nearest Neighbour Method Unlimited
  • Lecture 13 – The Nearest Neighbour Method, Decision Tree Learning Unlimited
  • Lecture 14 – Decision Tree Learning Unlimited
  • Lecture 15 – Decision Tree Learning, Learning of Bayesian Networks Unlimited
  • Lecture 16 – The Naive Bayes Classifier, Clustering Unlimited
  • Lecture 17 – Clustering, Data Mining in Practice Unlimited
  • Lecture 18 – Neural Networks: Modeling Learning, Hopfield Networks, Autoassociative Memory Unlimited
  • Lecture 19 – Neural Networks: Autoassociative Memory Unlimited
  • Lecture 20 – Linear Networks with Minimal Errors, The Backpropagation Algorithm Unlimited
  • Lecture 21 – Neural Networks: The Backpropagation Algorithm, Support Vector Machines Unlimited
  • Lecture 22 – Reinforcement Learning: Uninformed Combinatorial Search, Q-Learning Unlimited
  • Lecture 23 – Reinforcement Learning: Q-Learning Unlimited
  • Lecture 24 – Reinforcement Learning: Exploration and Exploitation, Curse of Dimensionality Unlimited
  • Lecture 25 – Recommender Systems: The Link-analysis Algorithm, Nearest Neighbour Filtering Unlimited

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