This 100% online Postgraduate diploma will allow you to code real-world problems through advanced algorithms and computer systems"

Intelligent Systems are undergoing a constant evolution, which opens a wide range of possibilities for society in general terms. For example, the implementation of Artificial Intelligence provides solutions in the field of medicine. These range from patient monitoring to assisting in clinical decision-making and the development of new drugs. This reflects the importance of professionals having a thorough knowledge of this subject in order to improve people's quality of life. Moreover, in order to carry out successful innovation processes, they need to be aware of the latest trends in this area of expertise and incorporate them into their practice.

For this reason, TECH launches a revolutionary program that will provide students with an integral prism that merges Machine Learning with Knowledge Engineering. To this end, the academic itinerary will delve into both Agent Theory and Neuron Networks. In this way, students will learn the most effective methods for the integration of knowledge representations, starting from the relationship between the different types of logic. On the other hand, this program will focus on Computational Perception so that graduates will be able to handle programming languages adequately.

To consolidate all these contents, TECH is based on the innovative  Relearning system. This teaching method is based on the repetition of key contents, to guarantee a progressive and natural learning process.  In addition, the only thing graduates will need is a device with Internet access to access the study materials remotely, at the time or place of their choice. In addition, the Virtual Campus will be available at all times and will allow users to download the contents so that they can consult them whenever they wis h.  

Master the software agents according to JADE in the best digital university in the world according to Forbes"  

This Postgraduate diploma in Intelligent Systems contains the most complete and up-to-date program on the market. The most important features include:

• Development of 100 simulated scenarios presented by experts in Intelligent Systems Science
• The graphic, schematic and practical contents with which they are conceived provide scientific and practical information on Intelligent Systems.
• News on the latest developments in Intelligent Systems.
• It contains practical exercises where the self-assessment process can be carried out to improve learning
• Interactive learning system based on the case method and its application to real practice.
• All of this will be complemented by theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments.
• Content that is accessible from any fixed or portable device with an Internet connection

You will master the Protégé software to efficiently create, edit and visualize ontologies"

The program includes in its teaching staff, professionals from the sector who pour into this program the experience of their work, in addition to recognized specialists from prestigious reference societies and universities. 

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations. 

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year For this purpose, the students will be assisted by an innovative interactive video system created by renowned and experienced experts.  

Elevate your professional potential within the world of Knowledge Engineering thanks to the innovative resources provided by this program"

With the innovative Relearning methodology, you will assimilate all the knowledge to obtain the results you are looking for and make a leap in your professional career"

This program is designed by a teaching staff composed of experts in Computer Engineering, which will provide students with a holistic view of Intelligent Systems. The academic itinerary will analyze in detail the agents of Artificial Intelligence. The syllabus will provide students with the most advanced software for the creation of ontologies, among which RDF Triplets stand out. Likewise, the training will delve into Knowledge Engineering so that graduates can develop systems that simulate and apply human knowledge effectively. In addition, the program will focus on image segmentation with Fourier Transforms.

A comprehensive and current curriculum configured as a high quality training tool of exceptional quality" 

Module 1. Intelligent Systems

1.1. Agents Theory

1.1.1. Concept History
1.1.2. Agent Definition
1.1.3. Agents in Artificial Intelligence
1.1.4. Agents in Software Engineering

1.2. Agent Architectures

1.2.1. The Reasoning Process of an Agent
1.2.2. Reactive Agents
1.2.3. Deductive Agents
1.2.4. Hybrid Agents
1.2.5. Comparison

1.3. Information and Knowledge

1.3.1. Difference between Data, Information and Knowledge
1.3.2. Data Quality Assessment
1.3.3. Data Collection Methods
1.3.4. Information Acquisition Methods
1.3.5. Knowledge Acquisition Methods

1.4. Knowledge Representation

1.4.1. The Importance of Knowledge Representation
1.4.2. Definition of Knowledge Representation According to Roles
1.4.3. Knowledge Representation Features

1.5. Ontologies

1.5.1. Introduction to Metadata
1.5.2. Philosophical Concept of Ontology
1.5.3. Computing Concept of Ontology
1.5.4. Domain Ontologies and Higher-Level Ontologies
1.5.5. Building an Ontology

1.6. Ontology Languages and Ontology Creation Software

1.6.1. Triple RDF, Turtle and N3
1.6.2. RDF Schema
1.6.3. OWL
1.6.4. SPARQL
1.6.5. Introduction to Ontology Creation Tools
1.6.6. Installing and Using Protégé

1.7. Semantic Web

1.7.1. Current and Future Status of the Semantic Web
1.7.2. Semantic Web Applications

1.8. Other Knowledge Representation Models

1.8.1. Vocabulary
1.8.2. Global Vision
1.8.3. Taxonomy
1.8.4. Thesauri
1.8.5. Folksonomy
1.8.6. Comparison
1.8.7. Mind Maps

1.9. Knowledge Representation Assessment and Integration

1.9.1. Zero-Order Logic
1.9.2. First-Order Logic
1.9.3. Descriptive Logic
1.9.4. Relationship between Different Types of Logic
1.9.5. Prolog: Programming Based on First-Order Logic

1.10. Semantic Reasoners, Knowledge-Based Systems and Expert Systems

1.10.1. Concept of Reasoner
1.10.2. Reasoner Applications
1.10.3. Knowledge-Based Systems
1.10.4. MYCIN: History of Expert Systems
1.10.5. Expert Systems Elements and Architecture
1.10.6. Creating Expert Systems

Module 2. Artificial Intelligence and Knowledge Engineering

2.1. Introduction to Artificial Intelligence and Knowledge Engineering

2.1.1. Brief History of Artificial Intelligence
2.1.2. Artificial Intelligence Today
2.1.3. Knowledge Engineering

2.2. Searching

2.2.1. Common Search Concepts
2.2.2. Uninformed Search
2.2.3. Informed Search

2.3. Boolean Satisfiability, Constraint Satisfiability and Automatic Planning

2.3.1. Boolean Satisfiability
2.3.2. Constraint Satisfiability Problems
2.3.3. Automatic Planning and PDDL
2.3.4. Planning as Heuristic Search
2.3.5. Planning with SAT

2.4. Artificial Intelligence in Games

2.4.1. Game Theory
2.4.2. Minimax and Alpha-Beta Pruning
2.4.3. Simulation: Monte Carlo

2.5. Supervised and Unsupervised Learning

2.5.1. Introduction to Machine Learning
2.5.2. Classification
2.5.3. Regression
2.5.4. Validation of Results
2.5.5. Clustering

2.6. Neural Networks

2.6.1. Biological Fundamentals
2.6.2. Computational Model
2.6.3. Supervised and Unsupervised Neuron Networks
2.6.4. Simple Perceptron
2.6.5. Multilayer Perceptron

2.7. Genetic Algorithms

2.7.1. History
2.7.2. Biological Basis
2.7.3. Problem Coding
2.7.4. Generation of the Initial Population
2.7.5. Main Algorithm and Genetic Operators
2.7.6. Evaluation of Individuals: Fitness

2.8. Thesauri, Vocabularies, Taxonomies

2.8.1. Vocabulary
2.8.2. Taxonomy
2.8.3. Thesauri
2.8.4. Ontologies

2.9. Knowledge Representation Semantic Web

2.9.1. Semantic Web
2.9.2. Specifications RDF, RDFS and OWL
2.9.3. Inference/ Reasoning
2.9.4. Linked Data

2.10. Expert systems and DSS

2.10.1. Expert Systems
2.10.2. Decision Support Systems

Module 3. Multiagent Systems and Computational Perception

3.1. Agents and Multiagent Systems

3.1.1. Concept of Agent
3.1.2. Architecture
3.1.3. Communication and Coordination
3.1.4. Programming Languages and Tools
3.1.5. Applications of the Agents
3.1.6. The FIPA

3.2. The Standard for Agents: FIPA

3.2.1. Communication between Agents
3.2.2. Agent Management
3.2.3. Abstract Architecture
3.2.4. Other Specifications

3.3. The JADE Platform

3.3.1. Software Agents According to JADE
3.3.2. Architecture
3.3.3. Installation and Execution
3.3.4. JADE Packages

3.4. Basic Programming with JADE

3.4.1. The Management Console
3.4.2. Basic Creation of Agents

3.5. Advanced Programming with JADE

3.5.1. Advanced Creation of Agents
3.5.2. Communication between Agents
3.5.3. Discovering Agents

3.6. Computer Vision

3.6.1. Processing and Digital Analysis of Images
3.6.2. Image Analysis and Artificial Vision
3.6.3. Image Processing and Human Vision
3.6.4. Image Capturing System
3.6.5. Image Formation and Perception

3.7. Digital Image Analysis

3.7.1. Stages of the Image Analysis Process
3.7.2. Pre-Processing
3.7.3. Basic Operations
3.7.4. Spatial Filtering

3.8. Digital Image Transformation and Image Segmentation

3.8.1. Fourier Transform
3.8.2. Frequency Filtering
3.8.3. Basic Concepts
3.8.4. Thresholding
3.8.5. Contour Detection

3.9. Shape Recognition

3.9.1. Feature Extraction
3.9.2. Classification Algorithms

3.10. Natural Language Processing

3.10.1. Automatic Speech Recognition
3.10.2. Computational Linguistics

You will have at your disposal the most modern educational resources, with free access to the virtual campus 24 hours a day"