Duration

3 weeks	2 weeks
Dates: June - July, 2021	Dates: June - July, 2021
Tuition & Service Fees: 800 USD*	Tuition & Service Fees: 400 USD*
ECTS: 5	ECTS: 3

Computer Science

Program Outline

The Program is designed for students who wish to deepen knowledge in software engineering and computer hardware. System programming aims to produce software which provides services to computer hardware, hence the need for proficiency in both software and hardware. Classes will include lectures where new theoretical material will be presented, labs and computer workshops for practical trainings, and seminars where students will present the results of their project. Ural Federal University has the modern IT infrastructure. The networking laboratory equipped with the high performance computing cluster. The program also gives a wonderful opportunity to see “inside” how these aspects of work organized in real organizations thanks to the practical-oriented part, visiting different enterprises.

List of Projects

MANAGEMENT OF PRODUCTION EQUIPMENT USING MACHINE LEARNING

This project is the result of the cooperation of the Ural Federal University with the Group of Companies of the Chelyabinsk Tube Rolling Plant. Within the course students learn how the work is organized and the technological processes are set up at one of the leading Russian enterprises for the production of pipes of different diameters. They will be asked to solve a specific production task as part of their educational project. The project will be led by professors of UrFU. Specialists from the factory will check and assess the results of the work.

Pre-requisites: Basic knowledge of Python, basic knowledge of statistics and theory of probability

Supervisor: Andrey V. Sozykin

FORECASTING THE COST OF THE RESOURCES (SCRAP)

Pre-requisites: Basic knowledge of Python, basic knowledge of statistics and theory of probability

Supervisor: Andrey V. Sozykin

FORECASTING POWER CONSUMPTION

Pre-requisites: Basic knowledge of Python, basic knowledge of statistics and theory of probability

Supervisor: Andrey V. Sozykin

IMAGE ANALYSIS USING DEEP NEURAL NETWORKS

Nowadays, deep neural networks are one of the most popular approaches to artificial intelligence system development. The program covers the foundation of deep learning using popular open-source Python library Tensorflow, which was created by Google. You will learn how to use convolutional neural networks for various image analysis tasks such as classification, segmentation and object detection. Also, you will have hands-on experience with free machine learning cloud platform Google Colaboratory (https://colab.research.google.com/) Project. The goal of the project is an analysis of medical images. You will create and train the neural network for automatic tuberculosis detection on the chest X-ray images. You will use several pre-trained neural networks, such as Inception from Google or ResNet from Microsoft, and fine-tune them for the tuberculosis detection task.

Pre-requisites: Basic knowledge of Python or any other program language

Supervisor: Andrey V. Sozykin, Irina Iumanova, Alexander Aksyonov

CYBERSECURITY

The program covers the foundation of cyber security and penetration testing (ethical hacking). You will learn how to find vulnerabilities in computer systems and how to fix them. The program is created by the members of HackerDom team, which organises the RuCTF international computer security competition (https://ructf.org/).

Pre-requisites: Basic knowledge of computer hardware and software, operational systems and networks. It would be great if you had some experience with Linux command line.

Supervisor: Natalia M. Neustroeva, Alexander Bersenev

Partner companies

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