Natural Language Processing Master’s Degree
versiune în română
- Optional Courses
- Industry/Research Practice
- After graduation
- Invited speakers and special guests presenting their latest research at our master’s programme.
The Natural Language Processing (NLP) Master’s Degree is a research program held in English within the Faculty of Mathematics and Computer Science, at the University of Bucharest. The NLP program is one of the first of its kind in Romania, and it is based on a long and robust tradition, starting with the pioneering work in mathematical and computational linguistics of Solomon Marcus from the “60’s which is continued to the present day by well known researchers names in NLP.
The main objectives of the Master’s Degree are to train specialists with solid knowledge in the field of Natural Language Processing and Information Processing, to provide a vast theoretical and practical training for graduates combined with the latest developments in the field.
We also expect and encourage that part of the graduates of this program will continue to enhance their expertize by pursuing doctoral studies, either at University of Bucharest (within the Computer Science Doctoral School, or at the Interdisciplinary Doctoral School), or abroad, within the institutions of our worldwide partners.
The first year curriculum contains 6 fundamental disciplines, preparatory for the subsequent courses within the program. The second year curriculum contains 5 advanced and specialized disciplines, guiding students towards gaining a complex and interdisciplinary training, being oriented both to research and industry. Each year’s program is supplemented by optional courses to complement students’ knowledge about NLP and Computational Linguistics topics or connex computer science fields.
The program is based on a powerful and modern teaching staff, with constant presence in the main NLP journals and conferences. We will promote a modern, open and collegial atmosphere, based on the mutual respect and recognition of each member of the community. The Master’s Degree is addressed to all members interested in Natural Language Processing and Computational Linguistics, will promote gender equality, and will not tolerate any discrimination, regardless of its nature (gender, religion, race, ethnicity, age, etc.).
Main Domain: Computer Science
Type of program: full time research master
Schedule: 4 semesters / 120 ECTS
Academic year: 2020-2021
Admission: July & September 2020: 30 state-sponsored grants
The admission process has two steps: 1) application review and 2) individual interview. The interview can be conducted online regardless of the current crisis. An English language Certificate is requiered in order to attend a Master’s Degree in English.
More info will be available on the Computer Science Department page
A general guide and information for international students is available here.
- Course Director: Prof. dr. habil. Liviu P. Dinu email: liviu.p.dinu @ gmail.com, tel. +40 761 146 148
- Prof. dr. habil. Florentina Hristea email: fhristea @ fmi.unibuc.ro
- Asist. Drd. Sergiu Nisioi email: sergiu.nisioi @ unibuc.ro
International Relations and Foreign Students Office
Telephone: +4021 305.46.42 +4021 305.46.41 E-mail: firstname.lastname@example.org Schedule: Monday - Thursday: 11:00 – 13:00 EE(S)T
- Linguistics for Computer Science
- Practical Machine Learning
- Natural Language Processing
- Advanced Machine Learning
- Cognitive Computing (in collaboration with IBM)
- Information Retrieval and Text Mining
- Machine Translation
- Special Topics in Computational Linguistics
- Special Topics in NLP and HLT
The list of the optional courses will be updated annually according to the dynamics of the field, the programs of the existing masters in the faculty and the interaction with the companies interested in offering specialized practical training within the master.
- Example Optional courses for smester I: Knowledge Representation and Reasoning, Logic for Computer Science.
- Example Optional courses for semester II: Big Data, Statistics for Data Science.
- Example Optional courses for semester III: Deep Learning, Modern Technologies for Information Security
- Example Optional courses for smester IV: Information Visualization, Special Topics in Artificial Intelligence.
This module can be done within:
- NLP groups from local or international companies (IBM, UiPath, Oracle, etc);
- the Human Language Technologies Research Center or in other partner centers
- NLP research teams or by working for a research paper, guide or tutorial
- summer schools (ESSLLI), workshops, exchanges etc.
- or other related activities
- continue with a doctoral degree either in Romania or abroad in partner reserach centers and universities
- major opportunities to develop a career in industry (IBM, Google, Oracle, UiPath, dailight.ai etc)
- possibility to develop your own research project within the Human Language Technologies Research Center
Anul universitar 2020-2021 (anul I) – 60 ECTS
|Sem. I (14 săpt.)||Sem. II (14 săpt.)|
|1||Linguistics for Computer Science||2||1||E||6||-||-||-||-|
|2||Practical Machine Learning||2||1||E||6||-||-||-||-|
|3||Foundations of Natural Language Processing 1||2||1||E||6||-||-||-||-|
|6||Advanced Machine Learning||-||-||-||-||2||1||E||6|
|7||Natural Language Processing 1||-||-||-||-||2||1||E||6|
|8||Cognitive Computing (in collaboration with IBM)||-||-||-||-||1||2||E||6|
C = curs; S = seminar/laborator; Ob.xx = obligatoriu; Op.xx = opțional; EV = evaluare; E = examen; V = verificare; ECTS = număr de credite europene transferabile;
Anul universitar 2021-2022 (anul II) – 60 ECTS
|Sem. I (14 săpt.)||Sem. II (14 săpt.)|
|1||Information Retrieval and Text Mining||2||1||E||6||-||-||-||-|
|3||Special Topics in Computational Linguistics||2||1||E||6||-||-||-||-|
|7||Special Topics in NLP and HLT||-||-||-||-||2||1||E||6|
- NB1. The last two weeks of semester IV will be dedicated to finalize the dissertation.
- NB2. Optional courses will be chosen from a list of available courses from other master’s programmes within the Faculty of Mathematics and Computer Science.