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.
  • Courses will be given 2 days a week: Thursdays and Fridays, with office hours and hands-on support sessions extending to Sundays and Wednesdays.
  • 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 A+B, Calculus A+B, and Probability Theory.
  • Practical experience will include small projects as part of each elective course, plus one mandatory, large, structured project.

Program Highlights


  • All classes taught in English, to prepare students for international working environments.
  • 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?

  • 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.​

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