Resources

Neural Machine Translation: a Practical Session
A Google Colab notebook which presents a practical session to introduce the training of neural machine translation systems to students. It was created for the lab sessions of the Machine Translation module of the IARFID master from Universitat Politècnica de València.

Experience

September 2021–February 2022

Machine Translation, Master’s Degree in Artificial Intelligence, Pattern Recognition and Digital Imaging, Departament de Sistemes Informàtics i Computació - Universitat Politècnica de València.

The goal of this course is to train students in techniques based on automatic learning that allow the construction of translation systems using datasets formed by sentences and their corresponding translations. First, students will study the fundamentals of translators based on statistical alignment models and translators based on dynamic neural networks. Then, they will implement and evaluate automatic translators using public tools.

Teaching assistant.

February–July 2021

Programming, Bachelor’s Degree in Data Science, Escola Tècnica Superior d’Enginyeria Informàtica - Universitat Politècnica de València.

Programming course taught in Python. Its goal is to deep into the study of dictionary-type data structures; dataframes; object-oriented programming; recursivity programming; algorithm analysis; and linear data structures (heaps, queues and lists).

Teaching assistant.

September 2020–February 2021

Machine Translation, Master’s Degree in Artificial Intelligence, Pattern Recognition and Digital Imaging, Departament de Sistemes Informàtics i Computació - Universitat Politècnica de València.

The goal of this course is to train students in techniques based on automatic learning that allow the construction of translation systems using datasets formed by sentences and their corresponding translations. First, students will study the fundamentals of translators based on statistical alignment models and translators based on dynamic neural networks. Then, they will implement and evaluate automatic translators using public tools.

Teaching assistant.

September 2020–February 2021

Computer Science, Bachelor’s Degree in Geomatic and Surveying Engineering, Escola Tècnica Superior d’Enginyeria Geodèsica - Universitat Politècnica de València.

Programming course taught in Python. Its goal is to instill to students the ability to program, since programming is more a skill than a knowledge. The aim is for students to be able to carry out small programs in a high level language based on problem-solving in an informal language. Given the basic fundamentals of programming through this course, students should be able to make programs in other languages/environments after consulting the relevant manuals in a self-taught manner. The teaching of the basic concepts of programming allows its applicability in the context of the career in which it is located.

Teaching assistant.

January–June 2020

Programming, Bachelor’s Degree in Data Science, Escola Tècnica Superior d’Enginyeria Informàtica - Universitat Politècnica de València.

Programming course taught in Python. Its goal is to deep into the study of dictionary-type data structures; dataframes; object-oriented programming; recursivity programming; algorithm analysis; and linear data structures (heaps, queues and lists).

Teaching assistant.

January–June 2020

Computer Science, Bachelor’s Degree in Electrical Engineering, Escola Tècnica Superior d’Enginyeria del Disseny - Universitat Politècnica de València.

Programming course taught in C. Its goal is to introduce students to the fundamentals of computer science. The course will focus mainly on computer-related aspects of computer programming, since the large number of applications that programming has in engineering makes it an essential requirement in the training of every engineer. In addition, students will be introduced to the use of computer applications related to engineering.

Teaching assistant.