Master in Artificial Intelligence
Online Master in Artificial Intelligence
The Master in Artificial Intelligence is born as a result of the union between the extensive experience in training and research, in the field of technology, which characterizes the UPC, backed by the recognition and accreditations it has, both nationally and internationally; and, the experience in online training, with a technological and business focus, from OBS .
The Master in Artificial Intelligence allows students to know the concepts and necessary elements of AI from a theoretical-practical point of view to successfully carry out projects in this area.
In the Master, students will delve into five large blocks:
Block I. Fundamentals: the key concepts related to AI will be provided, as well as those related to all technologies encompassed under this term.
Block II Development of Machine Learning and Neural Networks models: the models based on Machine Learning and Neural Networks and their practical use will be deepened. This includes optimization and subsequent evaluation of the models.
Block III Main AI architectures: the main existing frameworks in the market for the development of AI models will be deepened.
Block IV Implementation of AI projects: the development and management phases of projects linked to AI technologies will be addressed, as well as their implementation process.
Block V. Business applications of the AI and its business impact: the main business applications of the AI will be introduced, as well as the impact they have, both from a business and technological point of view.
It is important to highlight that the eminently practical nature of the program allows the student to immediately apply the knowledge acquired during the master's degree.
Once the program is finished, students will be able to occupy positions such as:
Head of ID Development Group in different sectors.
Business consultant specialized in AI.
Technological consultant specialized in AI.
Responsible for IA projects.
Expert in development of AI systems.
What is AI and what are its different applications? What cutting-edge technologies and capabilities are necessary to generate competitive advantages from AI? What is its potential impact on companies and society? What risks exist in machine learning based learning models? What is the relationship between AI and Big Data? What key elements should be considered to lead AI projects in an Organization?
The Master in Artificial Intelligence will help you answer all these questions, through the combination of the concepts related to the most important technologies, and the application of these at the business level. The analysis of different real cases and the development of your own project, will allow you to specify the reality of AI technologies, as well as their application to support business needs.
The Master in Artificial Intelligence has as main objective to bring the fundamentals of AI to all those professionals who see how the applications of Machine Learning, in their sectors, are changing the way of managing business models. Through this program, students will acquire the necessary technical knowledge to lead AI projects.
The curriculum of the Master in Artificial Intelligence is designed to achieve the following specific objectives:
Deepen the fundamentals and key concepts of AI, as well as the methods and techniques used to solve business problems.
Know the main algorithms and tools related to Machine Learning, to be able to implement them in solving problems without having previous programming knowledge.
Develop AI models using the main work frameworks existing in the market.
Develop practical AI applications such as virtual assistants and chatbots. Being able to lead AI projects, not only from a technical point of view but also from management, developing multidisciplinary profiles that know how to relate and connect different business areas and technological practices.
Understand the strategic impact of AI by developing a business vision to maximize your ROI.
Understand the applications of AI in different Industries and deepen the use cases with the greatest business impact.
Block I. Fundamentals of AI
IA leveling course
In parallel to module 1, students start the Artificial Intelligence program with this leveling course that provides the knowledge bases of programming, algorithms and mathematics. In this course, students will find material resources that will allow them to delve into different topics necessary for the follow-up of the course. In this course, they will perform test-type exams that will serve as a guide for the evaluation of their knowledge and will be evaluated at the end of it. The topics to be addressed are:
Basics of AI.
Introduction to programming.
Introduction to algorithms in AI.
Module 1. AI: fundamentals and main technologies
In this module the student will be introduced to the world of AI and its application in business, addressing issues such as:
Key concepts of AI.
Main AI technologies.
The "data-driven" organization.
Bases for the execution of AI projects and their difference with traditional IT execution.
Module 2. Socio-economic impact of AI
In this module, the student will acquire an integrated vision of the concept of AI in the current socio-economic context. In this one, the student will see topics such as:
Economic impact of AI and industry 4.0.
Impact of AI on people: ethical, social and legal considerations.
AI adoption and maturity model in organizations. IA Maturity Models as a positioning tool for organizations.
Block II Design and development of Machine Learning Models and Neural Networks
Module 3. Introduction to Machine Learning: data and algorithms
This module will introduce the student to Machine Learning, providing those key concepts for their correct understanding. In this you will see topics such as:
Key machine learning concepts.
The importance of the data.
Data quality and governance.
Machine Learning algorithms: risks and limitations.
Module 4. Machine Learning models: optimization and applications
This module will provide the keys to optimize the result of Machine Learning models, while addressing the process linked to minimizing risks in the generation of AI-based applications. The topics that will be worked on are:
Optimization of the models.
Data quality for robust analytics.
Generation of applications based on Machine Learning.
Module 5. Neural Networks
Throughout this fifth module, the student will enter the world of Neural Networks and will see topics such as:
Deep reinforced learning.
Training of a Neural Network: TensorFlow Playground.
Block III Main AI architectures
Module 6. AI Frameworks
In this module the student will see the main AI frameworks that currently exist in the market. Among them are:
Frameworks Open Source.
Google IA Framework.
Microsoft Cognitive Services Framework.
Amazon IA Services Framework.
IBM Watson Framework
Block IV Implementation of AI projects
Module 7. Implementation of AI projects (I): methodology
In this first part of block 4, the student will see the methodological aspects of the direction and implementation of AI projects. The topics that will be addressed are:
ML methodology: CRISP-DM.
Content life cycle.
Feedback and maintenance.
Reuse and retraining.
Cases and practical examples.
Module 8. Implementation of AI (II) projects: material and human resources
In this second part of the block, the student will focus on the direction and implementation of AI projects from the point of view of material and human resources. In this sense, some of the points that will be addressed in the module are:
Human Resources. Specific profiles, and impact on traditional profiles.
Block V. Business applications of AI and its business impact
Module 9. Business applications of AI and its business impact
This module will introduce the student to the main business applications of AI. Some of the topics that will be addressed are:
Intelligent interaction: optimization of the customer experience, through hyper-personalization, conversational interfaces and real-time data exploitation.
Smart products and services: the capabilities that AI provides and the search for new business models and markets.
Intelligent operations: combination of AI with automation solutions, to enable self-learning.
Intelligent corporate support functions (security, HR, technology, etc.): the use of AI to increase human intelligence and improve decision making.
Module 10. Client-based AI models
In this last module of the program, the applications of AI to customer relationship processes will be deepened. Some of the points of the module are the following:
Attraction: Social Networks and Paid Media.
Experience: Content customization and customer journey.
Sale: Upselling and cross selling.
Service: chatbots and smart assistants.
Master's final project
During the Final Master Project (PFM), the student will work hand in hand with a real company in the development of a project. This will have the option to do it for your own company or choose between the options proposed by the school.
During the Master in Artificial Intelligence, the student will have the opportunity to conduct 2 practical workshops, divided into a technological workshop and a business workshop.
Technological Workshop Python language application
This workshop raises the basic knowledge about Python introduced in the leveling course, advancing in the knowledge about the application of this programming language. Throughout this workshop, students will acquire a practical vision on the application of the most commonly used programming language in the field of Artificial Intelligence and Machine Learning: Python.
Python is a reference programming language in Artificial Intelligence environments for its ease of use, versatility and the large number of libraries available. The growth in the use of this language is being spectacular thanks, fundamentally, to the new technologies of Data Science and Machine Learning.
Note: In order to carry out this workshop, it is essential to have knowledge in programming.
Business Workshop Empowerment of Big Data projects through Machine Learning
Machine Learning needs large amounts of data to be able to function and train the algorithms it uses. In this workshop, students will see the different uses of Machine Learning in the Big Data environment. In addition, this workshop will allow students to master how AI relates to Big Data. How do we apply Machine Learning in Big Data? How can we discover patterns in the data through the use of Machine Learning? What applications do you have at the business level?
As it is a practical workshop, students will work, by way of example, with a use case of digital marketing. Specifically, you will see how the programmatic purchase of digital media is done today and how it can be optimized using Machine Learning techniques combined with Big Data environments. In this way, you will see the business benefit that this combination of technologies brings and how to extrapolate it to other processes.
Throughout the program students will use, among others, the following tools:
Software that allows programming in Python language. It is one of the most commonly used programming languages. It is a multiparadigma language.
Programming software integrated by different tools, expandable through the download of different packages, libraries or own samples. It is open source.
Free software library that is used to perform numerical calculations using flowcharts.
Python package designed to perform numerical calculations using tension programming.
CNTK (Microsoft Cognitive Toolkit)
Library for Deep Learning based on deep neural networks. This is based on the computational network construct, which is a unified framework to describe different types of learning machines, such as deep neural networks, convolutional neural networks, recurrent neural networks, etc.
APIS services (Amazon)
AWS service that allows you to create, publish, maintain, monitor and protect the REST and WebSocket APIs at any scale.
Student profile and admission requirements
The master's modules are designed with those professionals, from different sectors, who aspire to accelerate the development of their professional career and understand the role that AI is acquiring, in the business environment. The requirements to access the Master of Artificial Intelligence of OBS are the following:
Graduates and graduates in technical engineering, ADE and science (medicine, mathematics, physics or chemistry).
Executives who want an immersion in the business impact and the new possibilities that these technologies open, identifying the necessary elements to be able to apply them in real productive environments.
Project managers and managers who want to expand their management capacity to undertake projects related to AI.
People with experience or vocation in the area of AI who wish to strengthen their academic training.
Consultants and specialists in the AI sector who want to prepare, update and complete their profile, thus forging their competitive position in the market.
Upon completion of the program, students will obtain:
A title of Three Points.
An own degree accredited by the UPC, if the requirements of the University are fulfilled at the end of the program.