The Efi Arazi School of Computer Science has built an innovative and intensive M.Sc. program in Machine Learning & Data Science, aimed at providing a deep theoretical and practical understanding of machine learning and data-driven methods. The program will address foundations and techniques, as well as application domains and use cases.
About the Program
- Part-time program: 4 semesters over the course of 2 calendar years. Timeline may vary and is highly flexible to accommodate the students’ needs.
- Mandatory courses and core elective courses will be given on Thursdays and Fridays. Some elective courses, preparatory courses, office hours and hands-on support sessions may extend to weekdays.
- Applicants should have a Bachelor of Science (B.Sc.) degree in computer science or in an exact/natural science (physics, chemistry, biology, statistics, math, economics).
- Students may be required to take prerequisite courses including, but not limited to, Linear Algebra for Data Science, Calculus A+B, and Probability Theory.
- Practical experience will include small projects as part of each elective course, plus one mandatory, large, structured project.
- All Mandatory classes and some of the elective courses are taught in English, to prepare students for international working environments. Some of the elective courses are given in Hebrew, but English speaking students can complete all academic requirements with courses taught in English.
- working environments. Students can complete all academic requirements with courses taught in English.
- Answers the growing demand for top-level and highly skilled researchers, both in academia and industry.
- Trains future technology leaders of the highest caliber in the field of computer science, who will be able to pursue careers in both academia and industry.
- Students will attend frontal lectures and seminars, and will produce projects of different scales that will provide them with hands-on experience in data science and machine learning.
- Provides a community and partnering opportunities for students, scientists, and researchers from the entire scientific spectrum.
What Are You Going To Study?
Mandatory Core Courses (16 Credits)
Applied Machine Learning and Data Science Elective Courses
Machine Learning and Deep Learning Elective Courses
Big Data and Statistics Elective Courses
Infrastructure and Computer Science General Course Electives
Preparatory Courses for Non-Computer Science Graduates
Mandatory Final Project (5 Credits)
- For the entire list of courses please refer to the Student Handbook
Students are required to take 36 credits: 21 credits of mandatory core courses including a final project, 3 credits of mandatory electives, and 12 credits from a list of general computer science electives. Any student with an insufficient background in either computer science or math will be required to take additional preparatory courses, to be determined by the Admissions Committee.
- The academic administration of Reichman University reserves the right to make changes to the curriculum.