Master in Artificial Intelligence. Management and Implementation of Models + 60 ECTS Credits Master in Artificial Intelligence. Management and Implementation of Models + 60 ECTS Credits

Online Training

Master in Artificial Intelligence. Management and Implementation of Models + 60 ECTS Credits

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1500 hours

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60 ECTS

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Spanish

This Master in Artificial Intelligence (AI) is designed to respond to the new knowledge and training needs that have arisen in this field given the boom experienced in recent years in models, algorithms and companies that are dedicated to Artificial Intelligence. It is estimated that the AI ​​sector will have a global business volume of about 16 trillion dollars by 2030. Likewise, companies specialized in the search and selection of professional profiles point to AI as one of the knowledge that will be most in demand in the coming years.

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Details to take into account

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Multilingual support

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Digital certificate included

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Assistant Phia

Objectives

The overall objective of the Master is for the student to understand, apply, manage and lead AI initiatives and projects in an organization. This global objective is achieved through the following partial objectives: 1. Really understand what AI is, its limits and its possibilities. 2. Become familiar with the programming languages, tools and platforms most commonly used in AI projects. 3. Know the most used algorithms in Machine Learning and Deep Learning. 4. Analyze other technologies that emerge in the AI ​​environment and that help develop innovative and differential business models. 5. Review the main methodologies for managing AI projects. 6. Understand the implications and applications of AI in different functional areas of the company.

Content

Career opportunities

As AI is a transversal discipline that affects all functional areas of the company, this Master is aimed at any professional with concern for new technologies. It is especially focused on those who want to lead AI projects or lead this initiative at an organizational level. Additionally, this Master is very suitable for any department manager who wants to update their content and not be left behind in relation to this technology that will affect a multitude of sectors and areas of organizations.

What it prepares you for

The Master is designed so that it can be approached by any professional profile, since it will start from the fundamentals of AI and will not require extensive prior knowledge of programming and statistics (although basic knowledge of these disciplines is required). It is structured in two large blocks: a technical block, where we will explore the main models and algorithms of Machine Learning and Deep Learning, and a block applied to business, where we will study the main implications and applications of AI in companies. At the end of the Master's degree, students will have the necessary skills to carry out AI projects, manage them and promote this initiative within an organization.

Addressed to

As AI is a transversal discipline that affects all functional areas of the company, this Master is aimed at any professional with concern for new technologies. It is especially focused on those who want to lead AI projects or lead this initiative at an organizational level. Additionally, this Master is very suitable for any department manager who wants to update their content and not be left behind in relation to this technology that will affect a multitude of sectors and areas of organizations. It is especially suitable for: - Software developers - Systems engineers - Computer engineers - IT professionals - Project managers - Department managers - Entrepreneurs

Methodology

With our online learning methodology, the student begins his journey through a virtual campus designed exclusively to develop the training itinerary with the aim of improving his professional profile. The student must advance autonomously throughout the different teaching units as well as carry out the corresponding activities and self-assessments.
The load of hours of the training action includes the different activities that the student carries out throughout their itinerary. The hours of telelearning carried out on the Virtual Campus are complemented by the student's autonomous work, communication with the teacher, complementary activities and readings, and the research and creation work associated with the projects.
To obtain the degree, the student must pass all self-assessments and exams and view at least 75% of the contents of the platform. The Final Project is carried out after finishing the theoretical-practical content on Campus. Finally, it is necessary to notify the completion of the Master from the platform to begin the issuance of the degree.

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