| Study programme competencies |
|
Code
|
Study programme competences
|
| A20 |
CE19 - Knowledge of the different environments where AI based technologies can be applied and awareness of their capability to provide a differentiating added value |
| A21 |
CE20 - Ability to combine and adapt different techniques, extrapolating knowledge among different application domains |
| A22 |
CE21 - Knowledge of the techniques that facilitate the efficient organisation and management of AI projects in real environments, including resources management and tasks scheduling and taking into account the concepts of knowledge dissemination and open science |
| A23 |
CE22 - Knowledge of the techniques that facilitate the security of data, applications and communications and the derived consequences on different application domains in AI |
| A29 |
CE28 - Appropriate knowledge of the concept of enterprise, its organisation and management, and of the different business sectors, with the goal of providing solutions from the AI perspective |
| A30 |
CE29 - Being able to apply knowledge, abilities and attitudes to the business and professional world, by planning, managing and evaluating projects in the scope of AI |
| B1 |
CG01 - Maintaining and extending theoretical foundations to allow the introduction and exploitation of new and advanced technologies in the field of AI |
| B2 |
CG02 - Successfully addressing each and every stage of an AI project |
| B4 |
CG04 - Suitably elaborating written essays or motivated arguments, including some point of originality, writing plans, work projects, scientific papers and formulating reasonable hypotheses in the field |
| B5 |
CG05 - Working in teams, especially of multidisciplinary nature, and being skilled in the management of time, people and decision making |
| B6 |
CB01 - Acquiring and understanding knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, frequently in a research context |
| B7 |
CB02 - The students will be able to apply the acquired knowledge and to use their capacity of solving problems in new or poorly explored environments inside wider (or multidisciplinary) contexts related to their field of study |
| B9 |
CB04 - The students will be able to communicate their conclusions, their premises and their ultimate justifications, both to specialised and non-specialised audiences, using a clear style language, free from ambiguities |
| B10 |
CB05 - The students will acquire learning abilities to allow them to continue studying in way that will mostly be self-directed or autonomous |
| C5 |
CT05 - Understanding the importance of the entrepreneurial culture and knowledge of the resources within the entrepreneur person's means |
| C8 |
CT08 - Appreciating the importance of research, innovation and technological development in the socioeconomic and cultural progress of society |
| C9 |
CT09 - Being able to manage time and resources: outlining plans, prioritising activities, identifying criticisms, fixing deadlines and sticking to them |
| Learning aims |
| Learning outcomes |
Study programme competences |
| Know, understand and analyze the life cycle, the existing models and methodologies within the field of artificial intelligence that allow the design and implementation of reliable and efficient planning for the development of intelligent systems |
AC20
AC21
AC29
|
BC1
BC2
BC4
BC5
BC6
BC7
BC9
|
CC9
|
| Know the possibilities of public and private funding for research activities in the field of innovative and frontier technologies |
AC19
AC20
AC22
AC28
AC29
|
BC1
BC4
BC5
BC6
BC7
BC9
BC10
|
CC5
CC8
|
| Know and analyze real applications of software engineering methodologies and techniques applied to AI. Know how to use techniques and tools to support the planning and management of projects and risks |
AC20
AC21
AC28
AC29
|
BC2
BC4
BC5
BC6
BC7
BC9
|
CC9
|
| Be able to propose a complete plan for an R&D project in AI and know the mechanisms for managing and internationalizing the results |
AC19
AC20
AC21
AC22
AC28
AC29
|
BC1
BC2
BC4
BC5
BC6
BC7
BC9
BC10
|
CC5
CC8
CC9
|
| Know the implications of movements such as Open Access, Science and Data and the benefits of facilitating the participation of society in science and innovation (RRI) |
AC19
AC20
AC21
AC22
AC28
AC29
|
BC1
BC2
BC4
BC5
BC6
BC7
BC9
BC10
|
CC5
CC8
CC9
|
| Contents |
| Topic |
Sub-topic |
| Theory |
Typology of projects and models in Artificial Intelligence.
Introduction to the development model in Machine Learning.
Development and management methodologies for Intelligent Systems.
Conception, preparation, and financing of R+D+i projects in AI.
Entrepreneurship concepts and their application in AI: business models and methodologies.
Publication of results and Open Science, Open Data, and society participation (RRI) movements.
Science dissemination and internationalization. |
| Practice |
AI project planning and monitoring simulation |
| Planning |
| Methodologies / tests |
Competencies |
Ordinary class hours |
Student’s personal work hours |
Total hours |
| Objective test |
A20 A21 A22 A23 A29 A30 B1 B2 B4 B5 B6 B7 B9 B10 C5 C8 C9 |
2 |
10 |
12 |
| Seminar |
A20 A21 A22 A23 A29 A30 B1 B2 B4 B5 B6 B7 B9 B10 C5 C8 C9 |
10 |
10 |
20 |
| Problem solving |
A22 A29 A30 B2 B4 B5 B7 B9 C9 |
1 |
10 |
11 |
| Laboratory practice |
A22 A30 B2 B4 B5 B7 B9 C9 |
10.5 |
21 |
31.5 |
| |
| Personalized attention |
|
0 |
|
0 |
| |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
| Methodologies |
|
Methodologies |
Description |
| Objective test |
Exam to assess both the theory and the practice of the course |
| Seminar |
The teacher presents a topic to the students with the objective of providing a set of information with a specific scope. This teaching methodology will be applied to the training activity "Theory classes" |
| Problem solving |
Students are given practical projects whose scope requires that a significant part of the student's total dedication to the subject be devoted to them. In addition, due to the scope of the work to be done, students are required to apply not only managerial skills but also technical skills |
| Laboratory practice |
The teacher presents the students with a problem or problems of a practical nature, the resolution of which requires the understanding and application of the theoretical-practical contents presented. Students can work on the solution to the problems individually or in groups |
| Personalized attention |
|
Methodologies
|
| Laboratory practice |
| Seminar |
| Problem solving |
|
| Description |
Seminar/expository method/master class: the teacher presents a topic to the students with the objective of providing a set of information with a specific scope. This teaching methodology will be applied to the training activity "Theory classes".
Laboratory practices: the teacher presents the students with a problem or problems of a practical nature, the resolution of which requires the understanding and application of the theoretical-practical contents presented. Students can work on the solution to the problems individually or in groups.
Problem solving/Project-based learning: students are given practical projects whose scope requires that a significant part of the student's total dedication to the subject be devoted to them. In addition, due to the scope of the work to be done, students are required to apply not only managerial skills but also technical skills. |
|
| Assessment |
|
Methodologies
|
Competencies |
Description
|
Qualification
|
| Laboratory practice |
A22 A30 B2 B4 B5 B7 B9 C9 |
The teacher presents the students with a problem or problems of a practical nature, the resolution of which requires the understanding and application of the theoretical-practical contents presented. Students can work on the solution to the problems individually or in groups. |
50 |
| Objective test |
A20 A21 A22 A23 A29 A30 B1 B2 B4 B5 B6 B7 B9 B10 C5 C8 C9 |
The questions of the theoretical exam will focus on the specific contents, which have been developed in the subject, in relation to their competences and which may have been acquired both in the expository and interactive part. |
50 |
| |
|
Assessment comments |
In order to pass the subject, students must pass both the theory and the practice of the course separately. The practices are not recovered in July; except in those cases in which the student reaches 40% of the maximum grade of practices, allowing then to perform all the practices with respect to a new case study specifically raised for a possible recovery. In this case, the new practical case will be uploaded to the virtual platform two weeks before the theoretical exam of the course. In the evaluation of the work delivered by the students, the degree of achievement of the competences will be assessed, in particular the implementation of the contents provided by the course to these competences. In addition, the transversal competences will be assessed insofar as they are required for the development of these works.
The questions of the theoretical exam will focus on the specific contents, which have been developed in the subject, in relation to their competences and which may have been acquired both in the expository and interactive part. The average duration of the exam is approximately 2 hours and may consist of multiple-choice questions, short questions and case study problems. The exam will evaluate the degree of assimilation of the teaching objectives established in the syllabus of the subject.
There will be no partial exam.
Once both parts have been approved separately, each part will account for 50% of the final grade.
In order to receive a NO SHOW evaluation, one of the following circumstances must be present: 1. Not to have attended at least 85% of the practices of the subject. 2. Not having taken the theoretical exam of the subject in spite of having passed the practicals of the subject. 3. Not having taken the theoretical exam of the subject and having communicated explicitly and in writing to the person in charge of the subject that the subject is abandoned when, even having taken at least 80% of the practices of the subject, the practices of the subject have not been passed.
Weight of the continuous evaluation in the extraordinary opportunity of recovery (July tests): 1. The grade obtained in the practices during the course is maintained and also its weight in the final grade.
For cases of fraudulent performance of exercises or tests, the provisions of the Regulations for the evaluation of the academic performance of students and grade review will apply. |
| Sources of information |
|
Basic
|
|
|
PMBOK. A Guide to the Project Management Body of Knowledge: PMBOK Guide. 6th Ed. Project Management Institute, 2017. |
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Complementary
|
|
|
SCRUM and XP from the trenches. How we do SCRUM. 2nd Ed. Henrik Kniberg. InfoQ, 2007. |
| Recommendations |
| Subjects that it is recommended to have taken before |
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| Subjects that are recommended to be taken simultaneously |
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| Subjects that continue the syllabus |
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| Other comments |
|
Professors will facilitate, to the best possible option and within the hours established for the subject, attendance at the theory and practice groups that best suit the needs of students who are enrolled part-time, to which also applies the form of evaluation established here. Students with an academic waiver of attendance exemption must attend all assessment tests. |
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