Degree | Type | Year |
---|---|---|
2504392 Artificial Intelligence | OB | 2 |
You can view this information at the end of this document.
There are no official prerequisites but it is recommended to have completed the subjects of Fundamentals of Programming I and II, Fundamentals of Mathematics I and II, Probability and Statistics, Data Engineering and Fundamentals of Machine Learning.
This course provides an overview of the fundamentals techniques for natural language processing (NLP), covering classical approaches for text processing and parsing, language and sequence modelling and text representation, showing their application to usual NLP problems. The course also covers an introduction to the application of recent deep learning techniques to NLP. The content of the course will be expanded in subsequent optional courses, where deep learning-based approaches will be covered in greater depth, along with other more advanced topic such as semantic analysis, language generation or speech processing.
By the end of this course, students will be able to:
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Problems sessions | 16 | 0.64 | 1, 2, 3, 4, 5, 6, 7, 9, 10, 11 |
Project sessions | 4 | 0.16 | 1, 2, 3, 4, 5, 6, 9, 10, 12 |
Theory classes | 25 | 1 | 1, 3, 5, 6, 7, 8, 9, 10 |
Type: Supervised | |||
Work on the project | 50 | 2 | 1, 2, 4, 5, 6, 10, 12 |
Type: Autonomous | |||
Individual studying | 24 | 0.96 | 5, 6, 7, 8, 9, 10 |
Problem solving (individual) | 25 | 1 | 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 |
There will be three types of teaching activities: theory classes, solving practical exercises individually (problems) and developing a project in small groups of 2-3 students.
2.1. Problems: A set of problems to work through will be used, provided in Jupyter notebooks that exemplifies the coding details of the concepts exposed during theory classes. Work on the problems will begin in class and must be completed at home. Students will be required to make regular submissions of their work, which will comprise the problems portfolio.
2.2. Project: A project will be carried out during the semester, where students will have to solve a specific problem of certain complexity. The project will be solved in small groups of 2-3 students, where each member of the group must contribute a part and put it together with the rest to obtain the final solution. These working groups must be maintained until the end of the semester and must be self-managed in terms of distribution of roles, work planning, assignment of tasks, management of available resources, conflicts, etc. To develop the project, the groups will work autonomously, while the practical sessions will be used (1) for the teacher to present the project theme and discuss possible approaches, (2) for monitoring the status of the project and (3) for the teams to present their final results.
The above activities will be complemented by a system of tutoring and consultations outside class hours.
All the information of the subject and the related documents that the students need will be available at the virtual campus (cv.uab.cat).
Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Exams | 40 | 4 | 0.16 | 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 |
Problem solving | 20 | 0 | 0 | 1, 2, 4, 5, 6, 8, 9 |
Project | 40 | 2 | 0.08 | 1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12 |
The evaluation will be continuous, so there is no unique evaluation modality. To assess the level of student learning, a formula is established that combines knowledge acquisition, the ability to solve problems and the ability to work as a team, as well as the presentation of the results obtained.
Final grade
The final grade is calculated in the following way and according to the different activities that are carried out:
Final grade = 0.4 * Theory Grade + 0.2 * Problems Grade + 0.4 * Project Grade
This formula will be applied as long as the theory and the Project grades, are higher than 5. There is no restriction on the problems grade. If doing the calculation of the formula yields >= 5 but the student does not reach the minimum required in any of the evaluation activities, then a final grade of 4.5 will be given.
Theory Grade
The theory grade aims to assess the individual abilities of the student in terms of the theoretical content of the subject. This is done continuously during the course through two partial exams:
Theory Grade = 0.5 * Grade Exam 1 + 0.5 * Grade Exam 2
The mid-term exam (Exam 1) is done in the middle of the semester and serves to eliminate part of the subject if it is passed. The final exam (Exam 2) is done at the end of the semester and serves to eliminate the rest of subject if it is passed.
In order to obtain a final pass theory grade, it will be required for the partial exam grades 1 and 2 to be both higher than 4.5 and the average to be above 5.0.
Recovery exam: In case the theory grade does not reach the adequate level to pass, the students can take a recovery exam, destined to recover the failed part (1, 2 or both) of the continuous evaluation process.
Problems Grade
The aim of the problems is for the student to become familiar with the practical implementation of the theoretical concepts. The regular submission of problem solutions will be used as evidence of this work.
In order to obtain a grade for exercises, it is necessary that more than 50% of the exercises are submitted during the semester. In the contrary, the problems grade will be 0.
In each of the two partial exams there will be some questions about the problems of that part of the subject. The final problems grade will be the combination of the problems portfolio and these questions in the exam.
Problems Grade = 0.5 * Portfolio evaluation + 0.5 * Exam questions
Project Grade
The project carries an essential weight in the overall mark of the subject. Developing the project requires that the students work in groups and design an integral solution to the defined challenge. In addition, the students must demonstrate their teamwork skills and present the results to the class.
The project is evaluated through its deliverable, an oral presentation that students will make in class, and an individual-evaluation process. The participation of students in all three activities (preparing the deliverable, presentation and individual evaluation) is necessary in order to obtain a projects grade. The grade is calculated as follows:
Project Grade = 0.6 * Grade Deliverables + 0.3 * Grade Presentation + 0.1 * Grade Individual evaluation
If performing the above calculation yields >= 5 but the student did not participate in any of the activities (deliverable, presentation, individual evaluation), then a final grade of 4.5 will be given to the corresponding project.
In case the deliverable is presented, but the final project grade does not reach the minimum of 5, there will be a recovery of the project. In case of not presenting the deliverable or considering it copied, there will be no recovery and the subject will be considered failed. The maximum project grade that can be obtained in case of recovery is 7.
Important notes
Notwithstanding other disciplinary measures deemed appropriate, and in accordance with the academic regulations in force, evaluation activities will be suspended with zero (0) whenever a student commits any academic irregularities that may alter such evaluation (for example, plagiarizing, copying, letting copy, ...). The evaluation activities qualified in this way and by this procedure will not be recoverable. If you need to pass any of these assessment activities to pass the subject, this subject will be failed directly, without opportunity to recover it in the same year.
In case the student does not deliver any problems solutions, does not attend any project presentation session during the laboratory sessions and does not take any exam, the corresponding grade will be a "non-evaluable". In another case, the "no shows" count as a 0 for the calculation of the weighted average.
In order to pass the course with honours, the final grade obtained must be equal or higher than 9 points. Because the number of students with this distinction cannot exceed 5% of the total number of students enrolled in the course, it is given to whoever has the highest final marks. In case of a tie, the results of the partial exams will be taken into account.
For the problems and projects of the course we will use Python, along with some Python libraries for NLP that will be specified during the course.
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PAUL) Classroom practices | 711 | English | second semester | afternoon |
(PLAB) Practical laboratories | 711 | English | second semester | afternoon |
(PLAB) Practical laboratories | 712 | English | second semester | afternoon |
(TE) Theory | 71 | English | second semester | afternoon |