Department of Mathematical Modelling and Data Analysis
Educational and Research Institute of Physics and Technology NTUU "Igor Sikorsky Kyiv Polytechnic Institute"
To the attention of applicants to the master’s program who did not have time to register for the professional exam!
You still have an additional opportunity to register 27-28.07.2023 from 09:00 to 18:00 in your personal account!… Continue reading
Important for applicants for bachelor’s degree!
The registration of applications for admission to the specialty 113 Applied Mathematics has started on July 19, so it’s time to apply!
If you have already submitted your application, you can follow its status on the official edbo database page at the link:
Dear applicants!
We remind you that starting today, July 1, 2023, the electronic offices of the applicant are open for registration at https://cabinet.edbo.gov.ua/login. Therefore, do not hesitate to register if you are interested in applied mathematics, dream of finding like-minded people and participating in real projects of machine learning, artificial intelligence and computer vision, gaining experience of international cooperation and internships, and enrolling in our master’s program in the ONP “Mathematical Methods of Modeling, Pattern Recognition and Computer Vision” in the specialty 113 “Applied Mathematics”.… Continue reading
We have good news again!
The educational and professional program «Mathematical methods of modeling, pattern recognition and computer vision» in the specialty 113 Applied mathematics has now passed the accreditation of the first (bachelor’s) level!
Congratulations to all who have worked fruitfully on this extremely important process.… Continue reading
We are pleased to announce the successful completion of the second (master’s) level accreditation process of «Mathematical methods of modeling, pattern recognition and computer vision» in specialty 113 Applied mathematics!
Accreditation of an educational program is an extremely important stage for any educational institution and its staff.… Continue reading
Dear students!
If you are a bachelor’s student and dream of reaching career heights in the field of artificial intelligence and computer vision – you are right here!
The Department of Mathematical Modeling and Data Analysis invites you to the master’s degree in the educational program “Mathematical methods of modeling, pattern recognition and computer vision” in the specialty 113 Applied Mathematics.… Continue reading
To the attention of entrants to the master’s degree in specialty 113 – Applied mathematics for the educational and scientific program “Mathematical methods of modeling, pattern recognition and computer vision” 113_МММРОКЗ… Continue reading
If you haven’t had time to submit documents for the master’s degree, you should come to us!
Right now, the collection of second (master’s) level documents for the educational program “Mathematical methods of modeling, pattern recognition and computer vision” in specialty 113 – Applied mathematics is taking place.… Continue reading
Department of Mathematical Modeling and Data Analysis (MMDA) of the Educational and Research Institute of Physics and Technology NTUU “Igor Sikorsky Kyiv Polytechnic Institute” invites you to study!
Established in 2021, the MMDA department prepares highly qualified specialists under the innovative educational program “Mathematical methods of modeling, pattern recognition and computer vision” offers three levels of education:
• Bachelor’s degree
• Master’s degree
• Doctors of philosophy
The acquired fundamental knowledge in mathematics, physics, programming and computer sciences will allow students to master a wide range of professional disciplines dedicated to the development and application of mathematical models, methods and the latest technologies in specialized fields.… Continue reading
On June 6, 2022, there was a workshop by our successful FTI student, CEO of Harmix startup and research intern at the University of Toronto – Nazar Ponochevny on “Autoencoders. Introduction ”.
We talked about the use of auto-encoders in applied problems, understood why we need auto-encoders on examples and understood the direction of movement of successful students.… Continue reading