ECTS credits ECTS credits: 3
ECTS Hours Rules/Memories Hours of tutorials: 1 Expository Class: 10 Interactive Classroom: 15 Total: 26
Use languages Spanish, Galician
Type: Ordinary Degree Subject RD 1393/2007 - 822/2021
Departments: Electronics and Computing
Areas: Computer Architecture and Technology
Center Higher Technical Engineering School
Call: Second Semester
Teaching: With teaching
Enrolment: Enrollable
Quantum computers represent a highly promising alternative to classical systems for solving certain types of problems. Among these are binary optimization problems and classical Machine Learning algorithms such as Support Vector Machines (SVM) or neural networks. This course aims to serve as an introduction to quantum computing, focusing on these types of problems.
• Fundamentals of quantum computing: qubits, quantum gates
• Types of quantum computers and programming languages for quantum computing
• Quantum optimization algorithms: Quantum Annealing, QAOA, etc.
• Quantum Machine Learning: quantum support vector machines, quantum neural networks, etc.
Basic bibliography
- E.F. Combarro and S. González-Castillo, "A practical guide to Quantum Machine Learning and Quantum Optimization", Packt Publishing, 2023
Complementary bibliography:
- Thomas G. Wong, "Introduction to Classical and Quantum Computing", Rooted Grove, 2022.
- M.A. Nielsen and I.L. Chuang: "Quantum Computation and Quantum Information", Cambridge, 2010.
- "Getting started with Qiskit" curso online
This course contributes to the development of the following competencies as defined in the Bachelor's Degree in Artificial Intelligence:
- Basic and general: CB2, CB5, CG2, CG4, CG5
- Transversal: TR2, TR3
- Specific: CE2, CE5, CE6, CE4, CE12
The teaching methodology focuses on the fundamental aspects of quantum computing, the concepts that differentiate this paradigm from other computing approaches, and the solutions it offers in the fields of optimization and machine learning. Students are expected to understand the advantages and limitations of this new programming model and to be able to develop applications that can run on both simulated and real quantum systems.
Two types of learning activities are distinguished: lectures and practical sessions. Specifically:
- Lectures: 10 hours of lectures will be delivered in 1-hour sessions. These are designed to explain the core concepts underlying the quantum computing paradigm, with special emphasis on its advantages over classical computing models.
- Practical sessions: 15 hours of practical classes will be held in the computer lab across 10 sessions of 1.5 hours each. These sessions will allow students to become familiar with the theoretical content from a practical perspective. Attendance to these classes is mandatory (Article 1c of the attendance regulations for official bachelor's and master's degrees at USC).
Face-to-face learning activities and their relation to degree competencies:
- Lectures and seminar presentations. Competencies developed: CG4, CG5, CE2, CE3, CE5, CE6, CE4, CE12
- Lab sessions, problem solving, and case studies. Competencies developed: CB2, CB5, CG2, TR2, TR3, CE6, CE12
- Scheduled tutorials: guidance for individual or group assignments, Q&A sessions, and continuous assessment activities. Competencies developed: TR2
- Final exam. Competencies developed: CG4, CG5, CE2, CE3, CE5, CE6, CE4, CE12
Student evaluation will be based on continuous assessment and a final theoretical exam. Assessment includes attendance and participation in interactive sessions, completion of practical assignments throughout the semester, and the final exam covering all course content. Passing both the continuous assessment (practical work) and the final exam is mandatory to pass the course.
Weight of each component in the final grade:
Continuous assessment: 60%
Final exam: 40%
INTERACTIVE CLASSES
Students will tackle various problems proposed during the computer lab sessions. They will be required to submit assignments presenting their results. Several assignments will be mandatory, while others will be optional and may help improve the final grade. All assignments must be submitted by the specified deadlines and meet minimum quality standards to be considered. Evaluation criteria will include completion, methodology, rigor, and presentation of results.
REQUIREMENTS TO PASS THE CONTINUOUS ASSESSMENT
To pass the continuous assessment, students must have submitted and passed at least 75% of the mandatory assignments and obtained an overall grade higher than 5.
ATTENDANCE TO INTERACTIVE CLASSES
Due to the practical nature of the course, attendance at interactive classes is mandatory for both the regular and resit examination periods (Article 1 of the attendance regulations for official bachelor's and master's degrees at the University of Santiago de Compostela, approved by the Governing Council on November 25, 2024). Students who attend fewer than 80% of interactive sessions without valid justification will fail the course in both calls. In case of justified absences (according to Article 3 of the same regulation), students may either complete the missed practical sessions on their own or recover them in other lab shifts. Attendance will be recorded using a sign-in sheet.
PASSING THE COURSE IN THE REGULAR EXAMINATION PERIOD
Provided the minimum attendance requirements for lab sessions are met, students must obtain a total score equal to or greater than 5 in both the continuous assessment and the final exam. Submitting all mandatory assignments is essential to pass.
PASSING THE COURSE IN THE RESIT EXAMINATION PERIOD
If the minimum attendance requirement is met, students can retake any part not passed in the regular period, including assignments, practical work, and exams.
“NO SHOW” STATUS
Students who are not assessed in any aspect of the course will be marked as "No Show." Additionally, students whose grades do not exceed 10% of the maximum possible final score may request to be considered as “No Show” by informing the course coordinator.
REPEATING STUDENTS
Repeating students are generally subject to the same rules as regular students and must attend the interactive classes under the same conditions. However, if they achieved a grade of 7 or higher in the practical assignments from the previous academic year, they may retain that grade and only need to complete the assignments they did not submit previously.
In cases of academic dishonesty during assignments or exams, the Regulations on student academic performance evaluation and grade review will apply. According to the ETSE’s Plagiarism Policy (approved by the ETSE Council on 19/12/2019), any partial or complete plagiarism of practical or theoretical assignments will result in a failing grade (0.0) for both the regular and extraordinary examination periods.
In-class work:
- Lectures: 10 hours
- Practical classes: 15 hours
- Small-group tutorials: 1 hour
- Evaluation activities: 3 hours
Total in-class work: 29 hours
Individual student work:
- Independent study: 10 hours
- Programming/experimentation/computer-based assignments: 30 hours
- Evaluation activities (assignments, projects, exams): 9 hours
Total individual work: 49 hours
Due to the close interconnection between theoretical and practical content and the progressive introduction of closely related concepts, it is advisable to dedicate daily time to study and review.
The USC virtual campus will be used for all teaching activities, publication of materials, lab instructions, and assignment submission. Cloud-based tools such as Google Colab and IBM Quantum Experience will also be used.
The preferred language for both lectures and interactive classes is Spanish.
Anselmo Tomás Fernández Pena
Coordinador/a- Department
- Electronics and Computing
- Area
- Computer Architecture and Technology
- Phone
- 881816439
- tf.pena [at] usc.es
- Category
- Professor: University Professor
Samuel Soutullo Sobral
- Department
- Electronics and Computing
- Area
- Computer Architecture and Technology
- s.soutullo [at] usc.es
- Category
- Ministry Pre-doctoral Contract
| Wednesday | |||
|---|---|---|---|
| 16:30-17:30 | Grupo /CLE_01 | Spanish | IA.01 |
| Thursday | |||
| 17:00-18:30 | Grupo /CLIL_01 | Spanish | IA.03 |
| 06.01.2026 16:00-20:00 | Grupo /CLIL_01 | IA.01 |
| 06.01.2026 16:00-20:00 | Grupo /CLE_01 | IA.01 |
| 07.03.2026 09:30-14:00 | Grupo /CLIL_01 | IA.11 |
| 07.03.2026 09:30-14:00 | Grupo /CLE_01 | IA.11 |