Academic Year of Degree:
2024/25
658 - Master in Telecommunications Engineering
61069 - Machine learning in communications
Teaching Plan Information
Academic year:
2024/25
Subject:
61069 - Machine learning in communications
Faculty / School:
110 - Escuela de Ingeniería y Arquitectura
Degree:
658 - Master in Telecommunications Engineering
ECTS:
6.0
Year:
1
Semester:
First semester
Subject type:
Compulsory
Module:
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1. General information
The subject Machine Learning in Communications focuses on the knowledge and understanding of the different blocks that integrate the modern digital communication systems, as well as the digital signal processing and machine learning techniques, which play an increasingly prominent role in their design and implementation. The main objectives of the subject are the acquisition of the learning results indicated in the following section.
2. Learning results
- HA_01: Ability to design, calculate, and plan products, processes, and installations in all areas of telecommunications engineering.
- HA_04: Ability to perform mathematical modeling, calculation, and simulation in technology centers and corporate engineering, particularly in research, development, and innovation tasks related to telecommunications engineering and related multidisciplinary fields.
- HA_10: Ability to apply methods of information theory, adaptive modulation, and channel coding, as well as advanced digital signal processing techniques to communication and audiovisual systems.
- CP_02: Teamwork. (APC UZ1)
- CP_06: Lifelong self-learning (UZ5)
- CP_07: Ability to communicate (both orally and in writing) the conclusions—and the knowledge and underlying reasons supporting them—to specialized and non-specialized audiences in a clear and unambiguous manner
3. Syllabus
- TOPIC 1. Machine learning with application to communications
- TOPIC 2. Neural networks with application to communications
- TOPIC 3. Advanced channel coding
4. Academic activities
Participative master classes: 42 hours
Presentation by the teacher of the main contents of the subject.
Problem solving and case studies: 8 hours
Problem solving and case studies of the fundamentals presented in the master classes.
Laboratory work: 10 hours
Laboratory practices to consolidate the theoretical concepts developed in the lectures.
Study and personal work. 84 hours
Assessment tests. 6 hours
5. Assessment system
The subject will be evaluated through the following activities:
E1: Laboratory practices (20% of the grade, minimum score 4 out of 10): Evaluation will be based on the reports provided by the students and their attitude and performance in the laboratory.
E2: Practical teaching projects (20% of the grade, minimum score 4 out of 10): Evaluation will consider the student's analytical and critical capacity, the originality of the solutions, and especially the ability to work in a team and the skill to convey relevant information both orally and in writing.
E3: Mid-term written test (30% of the grade, minimum score 4 out of 10): Approximately halfway through the course, a written test will be conducted, accounting for 30% of the final grade based on the content covered up to that point. Obtaining a score of 4 out of 10 or higher in this test will exempt students from this part of the final exam. In any case, they can take this part to improve their grade.
E4: Final written test (30% of the grade, minimum score 4 out of 10): At the end of the syllabus, another written test will be conducted, accounting for 30% of the final grade based on the remaining content of the subject. Obtaining a score of 4 out of 10 or higher in this test will exempt students from this part of the final exam. In any case, they can take this part to improve their grade.
The total score E1+E2+E3+E4 must be higher than 5 to pass the subject.
The student will have a comprehensive test in each of the established sessions throughout the course. The dates and times will be determined by the School. The grade of this test must be higher than 5 to pass the subject and will be obtained as follows:
- Laboratory practices (20% of the grade, minimum score 4 out of 10)
- Practical teaching projects (20% of the grade, minimum score 4 out of 10)
- Final exam (60% of the grade, minimum score 4 out of 10 in each of its 2 parts): The final exam will consist of a written test divided into two parts, both with the same weight and the same minimum score.
6. Sustainable Development Goals
8 - Decent Work and Economic Growth
9 - Industry, Innovation and Infrastructure