Master’s Degree in Data Science (with or without thesis)

עברית

Master’s Degree in Data Science (with or without thesis)

What will you learn in the program, and why choose Bar-Ilan University?

What is special about the Master’s Degree in Data Science at Bar-Ilan University?

As technological systems become increasingly complex, the demand grows for professionals who understand the mathematical principles behind the models, not just how to use them. The Master’s Degree in Data Science in the Department of Mathematics at Bar-Ilan University provides exactly this combination: theoretical depth alongside a practical foundation that enables students to understand how models work in practice, analyze their limitations, and develop new solutions.

The combination of mathematical principles, Data Science tools, and hands-on laboratory experience creates a comprehensive professional foundation. Graduates report that this integration of theoretical courses, algorithmic thinking, and research work gives them a significant advantage in development roles, research positions, and work with data-driven systems.

The Department of Mathematics is one of Israel’s leading research centers: it hosts several active research institutes, seminars in areas such as analysis, combinatorics, cryptography, and algebraic geometry, visiting scholars, and advanced computing infrastructure. Faculty achievements — including the Krill Prize, Levitzki Prize, Alon and Rothschild fellowships, and more — reflect the high level of exposure students experience every day.

The program is designed for students with a Bachelor’s degree in exact sciences —mathematics, computer science, engineering, physics, or bioinformatics — who wish to advance into development, research, or Data Science roles, and to build on mathematical knowledge that enables creation, not just the use of existing tools.

Apply for the Master’s Program

What are the employment and career opportunities?

Graduates of the program integrate into roles in development, research, and data analysis, such as:

  • Data Scientist and Machine Learning Engineer
  • Algorithm development in high-tech, defense, and cybersecurity
  • Applied research in R&D laboratories
  • Financial and insurance modeling
  • Signal processing, image processing, and complex network analysis
  • Academic research toward a PhD in Israel and abroad
How Is the Study Program Structured?

Structure of the Study Program

The program is offered in two tracks: a thesis (research) track and a non-thesis (coursework) track.

Research Track (with thesis) – 32 credits

Intended for students who wish to pursue academic or industrial research or develop strong theoretical foundations.

Program components:

  • Foundation courses: 9 credits
  • Core courses: 4–9 credits
  • Specialization cluster: 7–10 credits
  • Seminar: 2 credits
  • Elective courses: up to a total of 32 credits
  • Research thesis: 14 credits (Course 88-3002)

Coursework Track (non-thesis) – 46 credits

Intended for students seeking to deepen their applied knowledge without committing to a long-term research project.

Program components:

  • Foundation courses: 9 credits
  • Core courses: 4–9 credits
  • Two specialization clusters: 14–20 credits (at least 7 credits in each cluster)
  • Seminars: 4 credits
  • Elective courses to complete a total of 46 credits

In both tracks, students must also complete foundation courses in English and Jewish studies, in accordance with university requirements.

Which courses are included in the degree?
  • Specialized Courses
  • Research Reproducibility – analysis of key papers and reconstruction of their algorithms or results.
  • Bayesian Inference – advanced probabilistic methods forming the foundation of machine learning.

  • Additional courses in the specialization clusters include Machine Learning, NLP, probabilistic models, networks, computational optimization, scientific data processing, and more.

    A. Algebra and Geometry:

  • 88-813    Commutative Algebra
  • 88-815    Noncommutative Algebra
  • 88-825    Algebraic Geometry 2

  • 88-854    Lie Algebras and Groups

    B. Analysis:

  • 88-831    Complex Analysis
  • 88-833    Functional Analysis

  • 88-835    Harmonic Analysis

    C. Topology and Geometry:

  • 88-821 A lgebraic Topology 2
  • 88-826    Differential Geometry 2

  • 88-8520  Smooth Manifolds and Lie Groups

    D. Applied Analysis:

  • 88-900    Mathematical Methods for Differential Equations
  • 88-902    Numerical Methods and Scientific Programming
  • 88-809    Dynamical Systems

  • 88-784    Optimization

    E. Probability and Statistics:

  • 88-962    Probability and Stochastic Processes
  • 88-7750  Statistical Theory and Inference (for students who have not taken course 88-775 Statistical Theory)
  • 88-779    Random Graphs and Networks
 

 

 

What practical experiences are offered in the program?

The Master’s program in Data Science operates within a research environment that includes seminars in areas related to Data Science, such as analysis, probability, applied mathematics, combinatorics, cryptography, and algebraic geometry. In addition, students participate in study groups, conferences, and guest lectures by leading researchers.

Students in the research track engage in laboratories in areas such as machine learning, cryptography, stochastic processes, and networks, applying theoretical learning principles in practice.

What are the admission requirements for the degree?
  • Research Track: Average grade of 84+ in a bachelor’s degree in exact sciences
  • Coursework Track: Average grade of 80+
  • Interview with the program advisor
  • A suitable mathematical background is required
How can you contact us?

Interested in learning more about the Master’s program in Data Science, with or without a thesis?