• To develop NLP applications using existing ready-to-use tools
• To analyze the interdisciplinarity involved in developing NLP applications

The objective of this course is to introduce the field of Natural Language Processing (NLP) through the most used applications both in academia and the industry. The course contents will include basic techniques of NLP: document classification, sequence labeling for opinion mining, vector-based word representations (embeddings), and normalization and pre-processing of texts. The course will have a practical focus based on laboratories and practical tasks learning to use NLP tools based on machine and deep learning.

• Labs. Students will be assessed on the activities proposed during the module. Max. 5 points (50%)

• Project. Students can undertake an optional submodule-specific project of their choice. Max. 3.5 points. (35%). The evaluation will be based on the following criteria: initiative, workload (min. 15 hours), application of concepts learned in the course and documentation (2 people group):

  • Evaluation criteria: initiative, workload (min. 15 hours), application of concepts learned in the module and documentation.
  • Important dates:
    • February 15: publish project proposals on egela
    • March 02: Students decide on a project or submodule to work on and notify me
    • April 7: deadline for submission (submissions after this date will be penalized by 0.5 points)
    • April 17: hard deadline (no submission will be accepted after this date)

• Attendance. 1 point if you attend 80% of the classes (including invited talks)

• Participation. The remaining 0.5 points (5%) will be based on the students participation in class discussions and activities.