A university degree that will allow you to design a robotic agent controlled by Artificial Intelligence"

Thirty years ago Artificial Intelligence was reserved for science fiction, however, today it is a reality and more and more different economic sectors are benefiting from its technological advances. Progress that also contributes to society. All this would not be possible without the work of professional engineers who have succeeded in creating systems capable of learning from the environment, finding a solution or adapting to a changing environment.

This Postgraduate certificate provides students with advanced knowledge in complex AI algorithms, fundamental to understanding the mathematical and conceptual basis that this technology is built upon. A program that will allow the engineering professional to delve into the logical and mathematical foundations of reasoning and learning that have allowed the development of algorithms for route finding, computer vision, language processing or robot control. 

A program with an advanced theoretical framework, but with an eminently practical approach that will allow students to directly apply all the learning acquired to practical use cases. This is all possible thanks to the specialized team that lead this Postgraduate certificate. 

An excellent opportunity for the engineering professional who aspires to improve their professional career with fully online program. A flexible teaching method allows you to take this program whilst juggling work and/or other personal responsibilities. All of this, plus multimedia content that you can access from day one, whenever and wherever you want. All you need is an electronic device with an Internet connection to connect to the virtual platform and start making progress in a booming sector.

Access a university program that brings you the most up-to-date multimedia content in the field of AI and Intelligent Agents”

The Postgraduate certificate in Intelligent Agents and Artificial Intelligence contains the most complete and up-to-date program on the market. The most important features include:

• Case studies presented by experts in robotic engineering
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where self-assessment can be used to improve learning
• Its special emphasis on innovative methodologies 
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection work
• Content that is accessible from any fixed or portable device with an Internet connection

An education that will allow you to master the key professional tools for the development of the intelligent agent"

The program’s teaching staff includes professionals from the sector who contribute their work experience to this educational program, as well as renowned specialists from leading societies and prestigious universities. 

Its 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 an immersive education programmed to learn in real situations. 

The design of this program focuses on Problem-Based Learning, by means of which the professional must try to solve the different professional practice situations that are presented throughout the academic course. For this purpose, the student will be assisted by an innovative interactive video system created by renowned experts.

Dominate Deep Learning with this Postgraduate certificate. You are just one click away from improving your professional career. Enroll now"

This Postgraduate certificate allows you to delve deeper into supervised, unsupervised and automatic learning"

The syllabus of this Postgraduate certificate is designed to provide students with the most comprehensive knowledge on intelligent robots and agents. With teaching that will delve into the foundation behind this technology, and during 6 weeks of this program that’ll also cover the brain-algorithm connection and its applications, machine learning, before finally leading the engineering professional to develop Developing a Robotic Intelligent Agent. The video summaries of each topic, the specialized readings and the real cases provided by the teaching team will facilitate learning and practical application in the professional's day-to-day work. 

Advance your career and immerse yourself in Intelligence and its application in robots and softbots"

Module 1. Intelligent Agents. Applying Artificial Intelligence to Robots and Softbots

1.1. Intelligent Agents and Artificial Intelligence

1.1.1. Intelligent Robots. Artificial Intelligence
1.1.2. Intelligent Agents

1.1.2.1. Hardware Agents. Robots
1.1.2.2. Software Agents. Softbots

1.2. Brain-Algorithm Connection

1.2.1. Biological Inspiration of Artificial Intelligence 
1.2.2. Reasoning Implemented in Algorithms. Typology
1.2.3. Explainability of Results in Artificial Intelligence Algorithms
1.2.4. Evolution of Algorithms up to Deep Learning

1.3. Search Algorithms in the Solution Space

1.3.1. Elements in Solution Space Searches
1.3.2. Solution Space Search Algorithms in Artificial Intelligence Problems
1.3.3. Applications of Search and Optimization Algorithms
1.3.4. Search Algorithms Applied to Machine Learning

1.4. Machine Learning 

1.4.1. Machine Learning
1.4.2. Supervised Learning Algorithms
1.4.3. Unsupervised Learning Algorithms
1.4.4. Reinforcement Learning Algorithms

1.5. Supervised Learning

1.5.1. Supervised Learning Methods 
1.5.2. Decision Trees for Classification
1.5.3. Support Vector Machines
1.5.4. Artificial Neural Networks
1.5.5. Applications of Supervised Learning

1.6. Unsupervised Learning 

1.6.1. Unsupervised Learning
1.6.2. Kohonen Networks
1.6.3. Self-Organizing Maps
1.6.4. K-Means Algorithm

1.7. Reinforcement Learning 

1.7.1. Reinforcement Learning
1.7.2. Agents Based on Markov Processes
1.7.3. Reinforcement Learning Algorithms
1.6.4. Reinforcement Learning Applied to Robotics

1.8. Artificial Neural Networks and Deep Learning 

1.8.1. Artificial Neural Networks. Typology
1.8.2. Applications of Neural Networks
1.8.3. The Transformation from Machine Learning to Deep Learning
1.8.4. Applications of Deep Learning

1.9. Probabilistic Inference

1.9.1. Probabilistic Inference
1.9.2. Types of Inference and Method Definition
1.9.3. Bayesian Inference as a Case Study
1.9.4. Nonparametric Inference Techniques
1.9.5. Gaussian Filters

1.10. From Theory to Practice: Developing a Robotic Intelligent Agent 

1.10.1. Inclusion of Supervised Learning Modules in a Robotic Agent
1.10.2. Inclusion of Reinforcement Learning Modules in a Robotic Agent
1.10.3. Architecture of a Robotic Agent Controlled by Artificial Intelligence
1.10.4. Professional Tools for the Implementation of the Intelligent Agent
1.10.5. Phases of the Implementation of AI Algorithms in Robotic Agents

Enroll now and apply the latest algorithmic advances in Artificial Intelligence projects"