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Starting October 2021
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The Bachelor's Degree in Engineering Mathematics and Artificial Intelligence (*), taught in the ICAI School of Engineering (Comillas ICAI), is an innovative program that responds to the great need, both at the present time and in the future for professionals who are capable of facing the challenges posed by Smart Industry and the Digital Economy.
This new degree offers a solid education and training in Applied Mathematics, Computer Science and Artificial Intelligence, and is aimed at students who would like to be protagonists of the digital transformation of our times, and who have a strong desire to take on challenging projects or to be leaders in entrepreneurship.
Students of this degree will benefit from the most advanced teaching methodologies and study in laboratories equipped with the latest technology, with emphasis placed heavily on teamwork, practical training oriented to projects and entrepreneurship, and in permanent connection with the Business and Technological ecosystem that is leading digital transformation internationally. All of this is being organized and offered by Comillas ICAI, an institution that has been training committed and responsible Engineers for more than 100 years, capable of addressing the new digital reality and AI applications, always placing individuals, as people, at the center of importance.
This degree has a duration of four years and is taught in Spanish and English. Students in this program will be able to carry out international periods of stay abroad as exchange students, thanks to the international agreements that Comillas ICAI has signed with partner universities. The possibilities for employment in this degree include diverse posts in the major professions of the future. You may work in the field of Artificial Intelligence as a Data Scientist, Machine-Learning Engineer, or as a Computer Vision Engineer, among others, as well as in the creation and management of Technology-Based Companies, in Technological Consulting and in the field of Research and Development in Data Science and Artificial Intelligence.
(*) This degree is currently being approved for study.
Percentage of graduates of the program who have carried out international exchanges during their studies.
A Well-Rounded Education
Percentage of students from the ICAI School of Engineering who take subjects associated with the development of soft skills, (diploma for special skills).
Would you like to be the protagonist of the digital transformation of the future?
David Contreras Professor Comillas ICAI
Computer Vision Engineer
Entrepreneurship: creation and management of technology-based companies
Machine Learning Scientist
Head of Artificial Intelligence (Chief Artificial Intelligence Officer - CAIO)
Architect of Artificial Intelligence Systems
Natural Language Processing Engineer (NLP Engineer)
Research and Development (R&D) in Data Science and Artificial Intelligence.
You may participate in Q&A Sessions and Information Days. This step is not required, but potential candidates are encouraged to delve into the Programs, learn about Study Plans and Curricula, ask questions, and gather additional information.
Applying for admission. The process begins via the web page, once the decision has been made concerning the Degree in which applicants wish to enroll. If deemed necessary, you may apply for scholarships, grants and financial aid from the University at the same time as you apply for admission.
You will find information here on everything related to the process of admission and entrance exams.
Communication and legal requirements for access to the University. Having been admitted does not exempt you from proving that you meet the legal requirements for access to the University. Meeting these requirements is an essential prerequisite in order to begin your studies at the University.
Completing the registration process. Once admitted, students must complete the registration process, which is initiated on the web page. It is necessary to submit the registration form and the additional documentation required personally to the University General Registrar´s Office before the end of June.
The Pre-University Campus, is designed for those students who wish to facilitate a smooth beginning as they start their University life. It takes place at the end of August.
Applicant Profile/Requirements and Documentation
Profile for Graduates of the Degree:
Candidates are recommended to access the degree from the branch of studies in Science and Technology, followed during their High School Education, having taken subjects in Mathematics, Physics, Technical Drawing and Chemistry, which will facilitate their adaptation to Undergraduate studies. Similarly, the preferred fields of Advanced Vocational Training Programs (CFGS) (“Ciclos Formativos de Grado Superior”) for access to this degree are the areas of Electricity and Electronics, as well as Mechanical Manufacturing.
The main personal and academic characteristics that make up the recommended entry profile for candidates to the degree are the following:
- Interest in scientific and technological knowledge.
- Ease of calculation and logical reasoning in problem solving.
- Facility for learning, a large capacity for work and a predisposition for organizational skills.
- Ability to analyze and synthesize information.
- Responsibility in carrying out individual work and skills for teamwork.
- Predisposition to apply concepts and put knowledge into practice.
Requirements and Documentation
To begin your studies is a prerequisite condition prove you accomplish with the legal requirements of access to the University.
Information about the documentation to submit
|Algorithms and Data Structures||6.0 ECTS|
|Mathematical Analysis and Vector Calculus||12.0 ECTS|
|Algebra and Geometry||12.0 ECTS|
|Statistics and Probability||9.0 ECTS|
|Christianism and Social Ethics||6.0 ECTS|
|Differential Equations||6.0 ECTS|
|Discrete Mathematics||6.0 ECTS|
|Operative Systems fundamentals||6.0 ECTS|
|Data Visualization||3.0 ECTS|
|Data Acquisition||4.5 ECTS|
|Artificial Intelligence fundamentals||4.5 ECTS|
|Electronic Systems||6.0 ECTS|
|Numerical Methods||6.0 ECTS|
|Human cognition and Artificial Intelligence||4.5 ECTS|
|Machine Learning||6.0 ECTS|
|Computational Geometry||3.0 ECTS|
|Programming Paradigms and Techniques||6.0 ECTS|
|Optimisation and Simulation||6.0 ECTS|
|Computer vision I||3.0 ECTS|
|Big Data Architecture||3.0 ECTS|
|Dynamic Systems||6.0 ECTS|
|Time Series Analysis and Forecasting||3.0 ECTS|
|Deep learning||4.5 ECTS|
|Natural Language Processing I||6.0 ECTS|
|Autonomous mobile robots||7.5 ECTS|
|Applications and services development||6.0 ECTS|
|Big Data Processing Technologies||6.0 ECTS|
|Economy & Business||6.0 ECTS|
|Natural Language Processing II||6.0 ECTS|
|Reinforcement learning||3.0 ECTS|
|Computer vision II||6.0 ECTS|
|Advanced Mathematics||3.0 ECTS|
|Cybersecurity and data protection||3.0 ECTS|
|Quantum Computing||3.0 ECTS|
|Disruptive business models||3.0 ECTS|
|Ethics and Artificial Intelligence||3.0 ECTS|
|Internship / Entrepreneurship project / AI Lab||6.0 ECTS|
|Technologies for digital transformation||6.0 ECTS|
|Bachelor thesis||12.0 ECTS|
GENERAL SKILLS AND ABILITIES
- Ability to solve mathematical problems that may arise in Engineering
- Capacity for abstract reasoning and critical analysis, as well as for calculation, modeling, simulation, optimization and prediction, to respond to problems posed by Science, Technology and Society in general
- Understanding and mastery of the basic concepts of fields, waves and electromagnetism, electric circuit theory, electronic circuits, the physical principle of semiconductors and logic families, electronic and photonic devices, and their application for solving problems in Engineering
- Basic knowledge of the use and programming of computers, operating systems, databases and computer programs with applications to Engineering
- Knowledge of the structure, organization, operation and interconnection of computer systems, the fundamentals of their programming, and their application for solving problems in Engineering
- Utilize learning in a strategic and flexible way, depending on the objective pursued, based on the recognition of the learning system and awareness of learning, in themselves, within a rapidly evolving technological context
- Join work teams and collaborate actively with other people, areas and organizations in achieving the objectives linked to the activities of extracting value from data and Artificial Intelligence
- Identify, analyze and define the significant elements that constitute a problem related to the managing data and Artificial Intelligence applied to business activities, in order to arrive at fair and just conclusions in an efficient manner
- Effectively determine the objectives, priorities, methods and controls to carry out tasks related to the planning of the use of data and Artificial Intelligence projects, by organizing activities within time limits and with the means available
- Understand and accept the social and cultural diversity present in companies and organizations in the field, as a personal and collectively enriching component to foment coexistence among individuals, without perpetrating any type of discrimination based on sex, age, religion, social, political and / or ethnic grounds
SPECIFIC SKILLS AND ABILITIES
- Ability to solve mathematical problems that may arise in Engineering. Ability to apply knowledge regarding: Linear and Multilinear Algebra, Geometry, Differential and Integral Calculus, Differential Equations, Numerical Methods, Statistics and Optimization
- Ability to understand and master the basic concepts of discrete mathematics, logic, algorithmic and computational complexity
- Ability to know how to apply the most appropriate mathematical techniques in solving different problems, both technical and technological, raised in the fields of Engineering and Artificial Intelligence. Ability to know the range of applicability and limitations in solving problems of different mathematical tools
- Ability to use mathematical software skillfully and fluently, as well as to implement algorithms and develop computer programs that allow for solving mathematical problems posed in the fields of Engineering and Artificial Intelligence
- Ability to understand the mathematical foundations of logical and propositional systems, as well as the ability to work with complex logical expressions
- Knowledge of the basic fundamentals of Number Theory and Modular Arithmetic. Ability to manipulate algebraic expressions in fields other than real numbers, thus understanding Floating Point Arithmetic and the basic principles of modern Cryptography
- Ability to apply the techniques of Discrete Mathematics and Computational Geometry to the resolution of discrete optimization problems, to the modeling of the interaction between the components of a system, to the study of databases and hierarchy diagrams, to problems of encoding and decoding of information, modeling of computer networks and solving location problems and other geometric problems
- Ability to model and solve physical systems in the field of Engineering, using numerical calculation techniques, numerical algebra, difference equations, differential equations or techniques of discrete mathematics
- Analyze, design and solve real problems through algorithmic techniques using a programming language
- Know the syntax, the main structures and the basic elements of a programming language in the context of data analysis and Artificial Intelligence
- Master the main data structures and algorithmic techniques, being able to implement them in different programming languages, knowing their computational complexity
- Know the fundamentals and benefits of the different programming paradigms to be able to apply them to each particular problem, thus maximizing their computational efficiency and distinguish the difference that exists between native and interpreted programming languages
- Know the existing code parallelization techniques, both in stand-alone contexts and in distributed systems
- Master the most widely used concepts and techniques for the acquisition and transformation of information located locally or remotely, whether static or moving, in the field of Data Analysis and Artificial Intelligence
- Design and administer structured, semi and unstructured information storage systems and techniques, and implement software solutions that interact with these systems
- Design and implement web and mobile applications that allow for publishing and exchanging the results obtained by the analytical models carried out through various interfaces and communication services
- Know the architectures and technologies of wired and wireless communications used in the context of the interconnection of devices, from the physical level to the logical level of protocols
- Know the technologies that help to deploy and put systems into production, leading to innovation and creating disruptive models in any sector
- Know cybersecurity requirements, and especially those for privacy, in the data analysis field, mastering encryption and anonymization techniques to guarantee data security
- Master Big Data infrastructure for storage and distributed processing for the processing of massive data
- Design and implement end-to-end Big Data distributed solutions
- Analyze data by applying statistical methods and techniques, working with qualitative and quantitative data
- Develop and use visualization tools for large volumes of data to be able to communicate the results of the different analyses carried out on them
- Identify the most appropriate statistical and operational research models for decision-making
- Know and apply techniques of artificial intelligence, machine learning, deep learning and reinforcement learning that allow us to extract knowledge from large volumes of data
- Ability to apply adequate artificial intelligence techniques to carry out Engineering tasks and projects
- Design and use statistical and operational research software, knowing its scope and limitations
- Know and use different natural language processing, representation and analysis technologies.
- Be able to perform the processing and analysis of computer vision information, as well as the extraction of characteristics from this information
- Design and apply heuristic search algorithms and methods for decision-making
- Specify, design and implement Machine and Deep-Learning Techniques for solving complex problems
- Know the economic fundamentals of consolidated companies and the dynamics of emerging businesses
- Be able to analyze the behavior of physical systems in the time domain. Knowledge of the principles of closed-loop control systems: stability, precision, speed and damping
- Be capable of designing electronic systems that integrate analog and digital elements. Sensors, actuators and communications
- Specify, design and develop autonomous mobile robots capable of functioning autonomously in unknown environments
- Be able to integrate multidisciplinary knowledge in a specific project or system
- Be capable of analyzing the behavior of cognitive systems and apply them in the artificial domain. Knowledge of the principles of basic psychological processes
Porfile for Graduates of the Degree:
The profile for Graduates of the BACHELOR'S DEGREE IN ENGINEERING MATHEMATICS AND ARTIFICIAL INTELLIGENCE is determined by the acquisition of all of the generic and specific competences that are described in the Degree Verification Report. (“Memoria de verificación del Título”).
Opportunities for Professional Employment and Further Studies:
The most common professional opportunities for employment and further education with this degree are:
- AI Engineer
- Data Scientist
- Computer Vision Engineer
- Robotics Engineer
- Entrepreneurship: creation and management of technology-based companies
- Data Scientist
- Machine Learning Scientist
- Head of Artificial Intelligence (Chief Artificial Intelligence Officer - CAIO)
- Architect of Artificial Intelligence Systems
- Natural Language Processing Engineer (NLP Engineer)
- Technological Consulting
- Research and Development (R&D) in Data Science and Artificial Intelligence