Programs

Bioelectrical engineering is a field of study that combines electrical engineering and biology to develop new technologies for medical diagnosis and treatment. Students in this field study electrical subjects and learn to serve patients and people in the community with different methods, including medical imaging, bio-signals, medical instrumentation, and biosignal processing

Indeed, the data sciences orientation within the field of data science is recognized as a major branch of applied mathematics. It involves the extraction of knowledge from a vast array of data and information. Data science employs methods and principles derived from various scientific fields, including pattern recognition, data engineering, statistical engineering, and mathematics. Therefore, it serves as a multidisciplinary approach to harnessing the power of data for decision-making and problem-solving, making it a critical field in today's data-driven world.

The field of "Mathematics and Applications" is a novel discipline that has emerged as a replacement for the fields of pure mathematics and applied mathematics. The integration of these two disciplines into one is due to the similarity in the lessons and concepts taught in both fields. This new field provides a comprehensive understanding of both theoretical and practical aspects of mathematics.

Applied mathematics involves the application of mathematical concepts to address various engineering and economic problems. This field utilizes mathematical modeling software and investigates the practical application of mathematical issues. It plays a crucial role in providing solutions to real-world challenges using mathematical approaches.

Indeed, this field is grounded in the theoretical development of the discipline. If an individual successfully completes courses in Mathematical Statistics 1, Mathematical Statistics 2, and Statistical Methods, they can continue their studies in this area. This progression allows students to build on their foundational knowledge and delve deeper into more complex statistical theories and methods. It's a rigorous and rewarding field that offers valuable insights into data analysis and interpretation.