Introducción a la Inteligencia Artificial: Principales Algoritmos

Description

In this course, you will learn:

• The Basic Foundations of Artificial Intelligence
• Differentiating between the various topics related to Artificial Intelligence
• What problems does a specific algorithm solve?
• The several algorithms you have available to address a specific problem
• Application of search algorithms
• Supervised application of learning algorithms
• Application of unsupervised learning algorithms
• Reinforced learning algorithms are used in this application.
• In Python, artificial intelligence libraries are used.

Syllabus:

1. Introduction

• Description of Artificial Intelligence
• History of Artificial Intelligence
• Distinction between issues surrounding Artificial Intelligence
• Applications
• Initiation to Artificial Intelligence libraries

2. Traditional Artificial Intelligence algorithms

• Knowledge-based Artificial Intelligence
• Search algorithms
• Algorithms for playing games

3. Machine learning: Supervised learning

• Introduction to supervised learning
• Prediction
• Classification
• Introduction to neural networks

4. Machine learning: unsupervised and reinforced learning

a) Unsupervised learning

• Clustering algorithms
• Dimensionality reduction

b) Reinforced

• Markov decision processes with finite state spaces
• Monte Carlo methods
• Temporary differences apprenticeships

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