Teaching

Courses taught at Ariel University and other institutions, covering data science, machine learning, and computer science.

Ariel University

2018 – present
  • Machine Learning UndergraduateSupervised & unsupervised learning, decision trees, SVMs, neural networks, and model evaluation.
  • Advanced Topics in Machine Learning UndergraduateDeep learning, CNNs, RNNs, transformers, and applied project work on real datasets.
  • Introduction to Computing (Python) UndergraduateProgramming fundamentals, algorithms, and data structures using Python for first-year students.
  • Search Engines and Recommendation Systems UndergraduateInformation retrieval, indexing, ranking algorithms, collaborative filtering, and content-based recommendations.

Vanderbilt University

2016 – 2018
  • Advanced Artificial Intelligence GraduateSearch, planning, probabilistic reasoning, machine learning, and AI ethics for graduate students.
  • Computational Economics GraduateGame theory, mechanism design, auctions, and algorithmic approaches to economic modeling.

Bar-Ilan University

2011 – 2016
  • Introduction to Computer Science Undergraduate 2012–2016Core CS concepts, problem-solving, and introduction to programming for engineering students.
  • Object-Oriented Programming Undergraduate 2013–2016OOP principles — classes, inheritance, polymorphism, and design patterns in Java.
  • Operating Systems Undergraduate 2013–2016Processes, threads, scheduling, memory management, file systems, and concurrency.
  • VERILOG Undergraduate 2014–2016Hardware description language for digital design, simulation, and FPGA synthesis.
  • Simulation and Simulation Languages Undergraduate 2011–2014Discrete-event simulation theory, modeling methodologies, and simulation tools.
  • Microprocessor Laboratory (ADuC841) Undergraduate 2011–2013Hands-on microcontroller programming, interfacing, and embedded systems experiments.