Become one of the most in-demand professionals of today. Specialize with thi complete professional master’s degree in Artificial Intelligence and Knowledge Engineering"

Developments based on Artificial Intelligence have reached numerous applications within the field of engineering. From the automation of numerous procedures in Industry and companies, to process control itself. This means that engineering professionals need to know and master the operation of these complex techniques.

This essential knowledge also becomes the first step to gain access to the development capacity of this type of technology.

Throughout this program, a real working scenario is offered in order to be able to evaluate the convenience of its application in your own project, assessing its real indications, its way of development and the expectations you may have regarding the results.

Through experience you will learn how to develop the necessary knowledge to advance in this field of work. This program, which necessarily requires experience, is reconciled through distance learning and practical teaching, offering a unique option to give your CV the boost you are looking for...

Join the elite with this highly effective instructional program and open new avenues for your professional advancement"

This professional master’s degree in Artificial Intelligence and Knowledge Engineering, contains the most complete and up-to-date program on the market. Its most notable features are: 

• The latest technology in online teaching software
• A highly visual teaching system, supported by graphic and schematic contents that are easy to assimilate and understand 
• Practical cases presented by practising experts
• State-of-the-art interactive video systems
• Teaching supported by telepractice 
• Continuous updating and recycling systems
• Autonomous learning: full compatibility with other occupations
• Practical exercises for self-evaluation and learning verification
• Support groups and educational synergies: questions to the expert, debate and knowledge forums
• Communication with the teacher and individual reflection work
• Availability of content from any fixed or portable device with internet connection
• Supplementary documentation databases are permanently available, even after the program

A professional master’s degree that will enable you to work in all areas of Artificial Intelligence and Knowledge Engineering with the solvency of a high-level professional"

Our teaching staff is made up of professionals from different fields related to this specialty. In this way, the intended objective of instructional updating is achieved. A multidisciplinary faculty of trained and experienced professionals in different environments, who will develop the theoretical knowledge efficiently, but above all, will put at your service the practical knowledge derived from their own experience: one of the differential qualities of this program.

he efficiency of the methodological design of this professional master’s degree, enhances the student's understanding of the subject. Developed by a multidisciplinary team of e-learning experts, the Method integrates the latest advances in educational technology. In this way, you will be able to study with a range of comfortable and versatile multimedia tools that will give you the operability you need in your training.

The design of this program is based on Problem-Based Learning, an approach that views learning as a highly practical process. To achieve this remotely TECH will use telepractice. with the help of an innovative interactive video system and Learning from an Expert you will be able to acquire the knowledge as if you were facing the scenario about which you are currently learning. A concept that will make it possible to integrate and fix learning in a more realistic and permanent way.

With a methodological design based on teaching techniques proven for their effectiveness, this innovative professional master’s degree in Artificial Intelligence and Knowledge Engineering will take you through different teaching approaches to allow you to learn in a dynamic and effective way"

Our innovative telepractice concept will give you the opportunity to learn through an immersive experience, which will provide you with a faster integration and a much more realistic view of the contents: “learning from an expert"

The objective is to specialize highly qualified professionals for work experience. An objective that is complemented in a global manner by promoting human development that lays the foundations for a better society. This objective is achieved by helping professionals to access a much higher level of competence and control. A goal that, in just a few months, can be achieved with high intensity and precision program.

If your objective is to broaden your skills set to include new paths of success and development: this is the program for you: a training that aspires to excellence"

General Objectives

• Train scientifically and technologically for the practice of computer engineering 
• Obtain comprehensive knowledge in the field of computer science 
• Obtain broad knowledge in the field of computer structure 
• Acquire the necessary knowledge in software engineering 
• Review the mathematical, statistical and physical bases essential for this subject 

Specific Objectives  

Module 1. Programming Fundamentals

• Understand the basic structure of a computer, software and general purpose programming languages 
• Learn how to design and interpret algorithms, which are the necessary basis for developing computer programs 
• Understand the essential elements of a computer program, such as the different data types, operators, expressions, statements, I/O and control statements 
• Understand the different data structures available in general purpose programming languages, both static and dynamic, and to acquire the essential knowledge for file handling
• Learn the different testing techniques in computer programs and the importance of generating good documentation together with good source code 
• Learn the basic concepts of the C++ programming language, one of the most widely used languages in the world 

Module 2. Data Structure

• Learn the fundamentals of programming in the C++ language, including classes, variables, conditional expressions and objects 
• Understand abstract data types, linear data structure types, simple and complex hierarchical data structures and their implementation in C++ 
• Understand the operation of advanced data structures other than the usual ones 
• Know the theory and practice related to the use of priority heaps and priority queues 
• Learn the operation of hash tables, such as abstract data types and functions 
• Understand graph theory, as well as advanced graph algorithms and concepts 

Module 3. Algorithm and Complexity

• Learn the main algorithm design strategies, as well as the different methods and measures for algorithm computation 
• Know the main sorting algorithms used in software development 
• Understand the operation of the different algorithms with trees, heaps and graphs 
• Understand how greedy algorithms work, their strategy and examples of their use in the main known problems We will also learn the use of greedy algorithms on graphs 
• Learn the main strategies of minimum path search, with the approach of essential problems of the field and algorithms for their resolution 
• Understand the backtracking technique and its main uses, as well as other alternative techniques

Module 4. Advanced Algorithms Design

• Learn more about the advanced design of algorithms, analyzing recursive and divide and conquer algorithms, as well as performing amortized analysis
• Understand the concepts of dynamic programming and algorithms for NP problems 
• Understand the operation of combinatorial optimization, as well as the different randomization algorithms and parallel algorithms 
• Know and understand the operation of different local and candidate search methods 
• Learn the mechanisms of formal program verification and iterative program verification, including first-order logic and Hoare's formal system 
• Learn the operation of some of the main numerical methods such as the bisection method, the Newton Raphson method and the secant method 

Module 5. Computational Logic

• Learn the fundamentals of computational logic, what it is used for and its justification of use
• Know the different strategies of formalization and deduction in propositional logic, including natural reasoning, axiomatic and natural deduction, as well as the primitive rules of propositional calculus 
• Acquire advanced knowledge in propositional logic, going into the semantics of this logic and the main applications of this logic such as logical circuits 
• Understand predicate logic both for the calculation of natural deduction of predicates and for the formalization and deduction strategies for predicate logic 
• Understand the basics of natural language and its deductive mechanism 
• Introduce logic programming using the PROLOG language 

Module 6. Artificial Intelligence and Knowledge Engineering

• Lay the foundations of Artificial Intelligence and Knowledge Engineering, making a brief tour through the history of Artificial Intelligence up to the present day 
• Understand the essential concepts of search in Artificial Intelligence, both informed and uninformed search 
• Understand how Artificial Intelligence works in games 
• Learn the fundamental concepts of neural networks and the use of genetic algorithms 
• Acquire the appropriate mechanisms to represent knowledge, especially taking into account the semantic web 
• Understand the functioning of expert systems and decision support systems 

Module 7. Intelligent Systems

• Learn all the concepts related to agent theory and agent architecture and its reasoning process
• Assimilate the theory and practice behind the concepts of information and knowledge, as well as the different ways of representing knowledge 
• Understand the theory related to ontologies, as well as learn ontology languages and software for ontology creation 
• Learn different models of knowledge representation, such as vocabularies, taxonomies, thesauri and mind maps, among others 
• Understand the functioning of semantic reasoners, knowledge-based systems and expert systems
• Know how the semantic web works, its current and future state, as well as semantic web-based applications

Module 8. Machine Learning and Data Mining

• Introduce knowledge discovery processes and basic concepts of machine learning 
• Learn data exploration and pre-processing methods, as well as different algorithms based on decision trees 
• Understand the operation of Bayesian methods and regression and continuous response methods
• Understand the different classification rules and the evaluation of classifiers by learning how to use confusion matrices and numerical evaluation, the Kappa statistic and the ROC curve
• Acquire essential knowledge related to text mining and natural language processing (NLP) and clustering 
• Expand your knowledge of neural networks, from simple neural networks to recursive neural networks 

Module 9. Multiagent Systems and Computational Perception

• Understand the basic and advanced concepts related to agents and multi-agent systems 
• Study the FIPA agent standard, considering agent communication, agent management and architecture, among other issues 
• Deepen the learning of the JADE (Java Agent Development Framework) platform by learning to program in it both basic and advanced concepts, including topics of communication and agent discovery
• Lay the foundations of natural language processing, such as automatic speech recognition and computational linguistics 
• Gain an in-depth understanding of computer vision, digital image analysis, transformation and segmentation of digital images 

Module 10. Bio-Inspired Computing

• Introduce the concept of bio-inspired computing, as well as to understand the functioning of the different types of social adaptation algorithms and genetic algorithms 
• Deepen the study of the different models of evolutionary computation, knowing their strategies, programming, algorithms and models based on estimation of distributions 
• Understand the main space exploration-exploitation strategies for genetic algorithms 
• Understand the operation of evolutionary programming applied to learning problems and multi-objective problems 
• Learn the essential concepts related to neural networks and understand the operation of real use cases applied to areas as diverse as medical research, economics and computer vision

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