Program Overview

Master Courses in Computer Science - Digital International Program

The DIGIT International program aims to open the master's degree to outstanding international students by offering an opening to the thematics of the SU Computer Science master's degree: bioinformatics, computer network, image processing, quantum information, security and reliability, etc.

1st Year Master Courses (M1) Taught in English

These courses are accessible to 4th year undergraduate exchange students provided they have the necessary prerequisites.

Semester 1

• ARCHI: Processor Architecture (MU4IN100): This course focuses on processor architecture and optimizations. It uses MIPS to illustrate the following concepts: pipeline, superscalar, memory hierarchy, and code optimization.
• BIMA: Fundamentals of Image Processing (MU4IN600): This course includes Fourier analysis, acquisition and theory of sampling, filtering and denoising, edge detection, segmentation. Applications are given on a few concrete problems (key-point detection, face recognition...), with practical works.
• COMNET: Computer Networking (MU4INX05): This course focuses on core network applications requested by users and services needed at the network level. The TCP/IP architecture and all the main associated protocols are detailed with particular emphasis on multimedia applications, end-to-end control mechanisms, and routing hierarchy.
• DIGCOM: Digital Communication (MU4INX06): This course provides the tools that are necessary for analyzing, modeling, and designing digital transmission systems. The first part of the course focuses on the necessary bases in deterministic and random signal processing.
• MODEL: Numerical and Symbolic Algorithms Modeling (MU4IN901): Mathematical algorithms play a central role in many fields of computing, whether it is to secure the transmission and/or exchange of data (by cryptography), to analyze large masses of data, or to optimize criteria under possible constraints.
• PPAR: Parallel Programming for High-Performance Computing (MU4IN903): Large-scale computations require both a massive amount of computing hardware, which is thus necessarily parallel, and programmers with a specific training to exploit it.
• QCLG: Quantum Circuits and Logic Gates (MU4INQ05): Quantum circuits are a common language in quantum information, blending insights and techniques from both computer science and physics.
• QPh4CS: Quantum Physics for Computer Scientists (MU4INQ02): Quantum cinematics needed to understand theoretical quantum information (Hilbert spaces in physicists notations, unitary transformations, projective measurements and POVMs, density matrices and partial traces).

Semester 2

• MULTI: Architecture of Multiprocessor Systems (MU4IN106): This course introduces the notions of cache and memory consistency, peripheral access, task synchronization in a shared application.
• ANUM: Numerical Algorithms (MU4IN910): This unit is the natural continuation of MODEL. It provides the knowledge in mathematical tools and algorithms in order to be able to solve concrete problems of large sizes.
• CLOUD: Cloud Computing (MU4INX30): Introduction to cloud computing principal, IaaS (Infrastructure as a Service), PaaS (Plateform as a Service), and Saas (Software as a Service), cloud computing architectures, cloud providers, etc.
• FLAG: Basics of Algebraic Algorithms (MU4IN902): This course presents algebraic algorithms for basic and building blocks problems, targeting quasi-optimal complexity.
• IG3D: Introduction to Computer Graphics (MU4INX42): This course introduces the domain of 3D computer graphics, including geometric modeling and processing, image synthesis, with implementation in OpenGL and C/C++.
• WIMOB: Wireless and Mobile Computing (MU4IN013): The main objective of this course is to present how user mobility and wireless transmissions affect computer communications.

2nd Year Master Courses (M2) Taught in English

Semester 1

• ANET: Autonomic Networks (MU5IN063): Main scientific and technological issues of autonomous and ubiquitous networks.
• AQAlg: Advanced Quantum Algorithms: Shor algorithms, Quantum Fourier Transform, phase estimations and applications, quantum random walks, query complexity (algorithms, lower bounds).
• AQCrypt: Advanced Quantum Cryptography: The use of quantum states has many cryptographic applications.
• BIOMED: Biomedical Imaging (MU5IN654): This course presents the main acquisition techniques both in medical imaging and in biological imaging.
• CELL: Cellular Networks (MU5IN050): This course presents network architecture and protocols of 2G-GSM, 3G-UMTS, 4G-LTE networks and the upcoming 5G technologies.
• DAAR: Development of Algorithms for Reticular Application (MU5IN552): We address both theoretical and implementation aspects of usual, non-trivial algorithms for web/mobile applications.
• IG3DA: Advanced Methods for Computer Graphics (MU5IN653): This course presents advanced methods for computer graphics: offline rendering, ray tracing, direct rendering, surface deformations.
• NAM: Network Analysis and Mining (MU5IN062): Network Analysis and Mining is a course at the crossroad between data mining and graph algorithmic.
• NETMET: Internet Measurement (MU5IN066): This course presents the measures that can be performed in local networks, access networks, and transit networks.
• AFAE: Floating-point Arithmetic and Error Analysis (MU5IN950): This course is at the intersection of algorithmic and mathematics.
• HPCA: Advanced High-Performance Computing and Programming Many Core Architectures (MU5IN952): Two thirds of this course are dedicated to CUDA programming.
• POSSO: Polynomial Systems Resolution (MU5IN953): Polynomial systems model static nonlinear situations.
• PhQC: Photonics Quantum Computing: Photonics is an essential platform for quantum communications and a promising one for quantum computing.
• PRAT: Image Seminar and Projects (MU5IN656): This course presents briefly a few topics not addressed in the other courses, in the form of seminars given by experts of the domain.
• QIT: Quantum Information Theory: The quantum analogue of Shanon theory and complexity theory are very rich, with many applications.
• RDFIA: Pattern Recognition and Machine Learning for Image Understanding (MU5IN652): This course presents theory and algorithms for classification and image understanding.
• TADI: Advanced Methods for Image Analysis (MU5IN650): This course presents advanced theories of image processing and analysis.
• VISION: Advanced Methods for Computer Vision (MU5IN651): This course provides an overview of advanced techniques for computer vision, either 2D or 3D, either static or dynamic.