|
HU Credits:
2
Degree/Cycle:
2nd degree (Master)
Responsible Department:
Computer Sciences
Semester:
2nd Semester
Teaching Languages:
English and Hebrew
Campus:
E. Safra
Course/Module Coordinator:
Dr. Oded Schwartz
Coordinator Office Hours:
Wednesday, 16:00-17:00
Teaching Staff:
Prof. Omri Abend
Course/Module description:
Several different reading groups:
Oded Schwartz's: Studying algorithms, bounds, and challenges for fast matrix multiplication.
Omri Abend's: Natural Language Processing
Dafna Shahaf: Data Science
Course/Module aims:
At the end of the course students will be familiar with fundamental algorithmic methods for fast matrix multiplication, lower bounds, as well as challenges and open problems in the field.
Omri Abend: critical reading in scientific papers in NLP.
Learning outcomes - On successful completion of this module, students should be able to:
Oded Schwartz's: Understand the central algorithmic methods, understand which of them have practical application, and which are useful for theoretical purposes only.
Omri Abend's: understanding of advanced NLP literature.
Attendance requirements(%):
90%
Teaching arrangement and method of instruction:
Guided reading. In every meeting one participant will present a selected paper / topic.
In the NLP group: leading a discussion on a topic/paper.
Course/Module Content:
TBA in class.
Required Reading:
TBA in class.
Additional Reading Material:
TBA in class.
Grading Scheme :
Active Participation / Team Assignment 100 %
Additional information:
In Omri's group: the grades are pass/fail.
|
