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The two-year Data Artificial Intelligence Master’s program covers artificial intelligence (AI) and large-scale data management. Students will acquire the basics of machine learning, logic, big data systems, and databases, before diving into applications in advanced machine learning, symbolic AI, swarm intelligence, natural language processing, visual computing, and robotics.
As a student in the MSc Data Sciences & Artificial Intelligence course at Université Côte d'Azur, you will be trained to become a specialist in the mathematical techniques and computational tools needed to extract knowledge from large amounts of data. Students will receive a thorough grounding in theory as well as technical and practical data science skills, enabling them to apply advanced data science methods to real-world problems.
With the explosion and profusion of data available in a large number of fields, new collection and analysis techniques are having a profound effect on all sectors of economic life, but also on certain research sectors. The course offers an introduction to the best methodological tools for understanding and exploiting data, particularly massive data (Big Data). An immersion in the world of data through an intensive course on the fundamentals of data science.
High Performance Computing (HPC) is the use of powerful processors, networks and parallel supercomputers to tackle problems that are very computationally or data-intensive.
This programme aims to provide you with in-demand skills and knowledge of the techniques and technologies underpinning parallelism and HPC. Skills and knowledge will be gained across a wide range of industries and academic disciplines.
The goal is to provide an understanding of high performance computing, how it works, and introduce its best practices and use cases to enable efficient calculations with large complex data.
The "High Performance Computing and Data Science" course is a joint course between Enseirb-Matméca and the University of Bordeaux. It is aimed at students from Enseirb, Matméca and the Bordeaux Master's in Computer Science who wish to become experts in high-performance computing and data processing and analysis.
You will study at EPCC, the UK’s leading supercomputing centre and a Centre of Excellence within the University's College of Science and Engineering. EPCC is a major provider of high performance computing (HPC) training in Europe with an international reputation for excellence in HPC education and research.
This programme aims to provide students with in-demand (for both a wide range of industries and academic disciplines) skills and knowledge of the techniques and technologies underpinning parallelism and High Performance Computing (HPC).
The rapid growth of the internet has led to vast amounts of data being collected. As analyzing this data requires tremendous computing power, high-performance data analytics employs various parallelization techniques to reduce the execution time. These techniques can be applied to various domains such as high-performance computing, artificial intelligence and big data.
The convergence of the fields of High Performance Computing (HPC) and massive data processing (HPDA) is now allowing the creation of intelligent systems that the professional world is taming to invent breakthrough solutions. This convergence requires the development of new interdisciplinary skills with a solid foundation in both mathematics and computer science.
The current training offer only partially covers this field of expertise, while the need for skills is constantly increasing.
The two-year Master’s programme in Image Processing and Computer Vision (IPCV) trains specialists in a field of increasing importance in our daily lives. Processing images and videos is essential in domains such as medicine, surveillance, industrial control, remote sensing, e-commerce, automation, etc. The IPCV programme offers extensive theoretical and practical knowledge to train highly-qualified graduates in this field.
Programme scheme:
Постдипломските студии по интелигентни системи имаат за цел обезбедување на врвен научен и истражувачки кадар за задоволување на сé поголемата побарувачка за висококвалификувани инженери способни за совладување на најпредизвикувачките развојни, истражувачки и процесни проблеми.
The development and implementation of intelligent systems and robotic machines, from the processing of sensor output to its high-level interpretation by artificial intelligence methods, meets a growing need of industrialists in sectors with high employment demand. The ISI course aims to train students in research and development in the fields of intelligent systems and robotics, and in particular on subjects such as multimodal interaction, image and sound analysis, and the design and control of robotic systems, at the interface of computer science, electronics and mechanics.
Постдипломските студии по Интернет технологии имаат за цел да обезбедат квалитетно и врвно европско образование и обучување на ИКТ инженери со длабоки познавања на Интернет мрежите, технологиите и безбедноста. По завршувањето на студиите овие инженери ќе можат да заземат одговорни позиции во процесите на планирање, дизајн, управување и безбедност на Интернет мрежи и работа со различни видови на најнови технологии вклучувајќи ги и нивните бизнис аспекти.
Within this subject, you can familiarize yourself with the following topics:
Тhе MSc programme Nuclear and Particle Physics aims to prepare highly qualified specialists in the field of nuclear physics, particle physics, radiation physics.
Lector: Professor, Dr. Todor Vassilev Gurov
E-mail: todor.gurov@iict.bas.bg
Workload: 30 hours
The course aims to acquaint the PhD students with parallel architectures and algorithms. It also includes practical exercises using standard parallel programming MPI and OpenMP. The course covers:
Artificial intelligence (AI) is a rapidly growing interdisciplinary field, driven in particular by proven successes in image processing and natural language handling. successes in image processing and natural language processing. In its entirety, it offers the In general, it offers the possibility of responding to a strong need of industrialists who are seeking to make the best use of data. This may involve gaining a better understanding of complex systems or predicting their behaviour, with the aim of increasing the competitiveness of companies.
This course aims to give students a very clear intuition behind the most essential Machine Learning methods. Therefore, we will practice implementing some of the key algorithms (like decision trees, backprop, bagging tree) in machine learning, so that it can be done if the need arises. We will discuss and gain practical experience with `sklearn` library. We will build an understanding as to when some algorithms should be preferred to other algorithms.
