- סטטיסטיקה (10015)
תקציר הקורס:
Abstract:
Statistical analysis is a basic tool needed by every researcher. In this course, we will learn how to draw statistical conclusions from a dataset.
We will learn to compare distributions of different data types and sample groups.
We will learn parametric and non-parametric tests, we will learn to conduct variance analysis, correlation tests and linear regression.
The topics will be studied in a theoretical way and will be practiced on representative examples using R programming language in the computer lab.
- מודלים חישוביים (10139)
תקציר הקורס:
Abstract:
Students will learn about models of computing machines: finite automata, pushdown automata, and Turing machines. Students will demonstrate knowledge of Formal languages, their descriptions, and their relationships to the computational models; Students will learn the limits of the various models.
- סמינר מדעי מחשב (11015)
תקציר הקורס:
Abstract:
The seminar focuses on algorithms for robotics and on scientific research and communication skills. Each student will select a robotics topic and build a literature review based on three central scientific papers. The emphasis is on constructing an integrated scientific story - not summarizing papers separately - including the problem, comparison of approaches, identification of a research gap, and proposed future directions. During the semester, students will practice an Elevator Pitch, a 45-minute scientific presentation, a scientific poster, peer review, and the use of AI tools for literature review. At the end of the semester, a short quiz will cover the main principles from all projects presented in class.
- למידת חיזוק ורובוטיקה (65026)
תקציר הקורס:
Abstract:
Multi-agent systems (MAS) is a subfield of artificial intelligence that investigates systems composed of multiple interacting intelligent agents. These agents can be software programs, robots, or humans, and they operate in a shared environment. The study of MAS focuses on the design, analysis, and implementation of such systems, particularly on understanding the interactions, cooperation, and competition among agents. Key research areas include agent modeling, communication protocols, coordination mechanisms, and the application of MAS to real-world problems.
