Computer Science

This course offers a study of advanced Big Data analytics. Topics include: e-business and market trends; supply chain management; enterprise resource planning and customer relationship management; applications of advanced Big Data analytics.

This is an individual study project. Students must have a well thought-through idea of the theme of the study. A faculty teacher is appointed as supervisor, and an agreement is signed between the student and the teacher describing the title, contents, and ECTS credits of the study. A supervisor normally meets with the student between two and four times to discuss the progress of the individual study, or any problems encountered. Most supervisors also choose to read and comment on parts of the study. Students applying to do an individual study must submit a detailed project description with their application. Exams for Individual Study Projects may be oral, written or a combination of the two. This version of the course is worth 12 quarter units and corresponds to a workload of 412 hours. 

This course introduces classic and state-of-the-art methodology in computer graphics. We will focus on methods and best practices in geometry and physical simulation, which are the basic building blocks for downstream applications such as animation, industrial design, game engineering, structural analysis, AR/VR, and medical imaging. Our curriculum will cover basic representations of shapes, geometric optimization, analysis, and principles of robust digital simulation of physical scenes. The techniques employed will involve classical numerical analysis up to deep geometric learning.

The course will include programming tasks to implement a few key algorithms in geometry processing, geometric learning, and physical simulation, to the extent that they can independently run and be analysed on modest open-source data.

This course (CGGS) and Computer Graphics: Rendering (CGR) are both courses that require no previous knowledge of computer graphics. These two courses may be taken independently or together. CGGS focusses on the representation, processing, and dynamics of 3D objects in the virtual world while CGR focusses on the rendering of virtual worlds as photo-realistic images.

This course examines advanced topics and techniques in database systems, with a focus on the system and algorithmic aspects. It will also survey the recent development and progress in selected areas. Topics include: query optimization, spatial-spatiotemporal data management, multimedia and time-series data management, information retrieval and XML, data mining.

PSYE60 is an introductory course to human and artificial cognition. During the course, students learn about how artificial intelligence (AI) can be used to understand human behavior and how psychological phenomena in people can be found in artificial intelligence. The course emphasizes understanding of how natural cognition can be understood with the help of artificial cognition and how psychological phenomena arise in artificial cognition. Application is made in neural networks, natural language processing, AI-generated images, and how AI affects society.

The course introduces basic theory and algorithms of machine learning. Topics include: supervised learning setting; unsupervised learning setting; concentration of measure inequalities; analysis of generalization in classification; algorithms; assumptions behind the algorithms taught in the course, their implications, and common pitfalls; and correlation versus causality. The course assumes solid math and programming skills, including knowledge of linear algebra, calculus, probability theory, discrete mathematics, and programming. 

The Individual Research Training Senior (IRT Senior) Course is an advanced course of the Individual Research Training A (IRT A) course in the Tohoku University Junior Year Program in English (JYPE) in the fall semester. Though short-term international exchange students are not degree candidates at Tohoku University, a similar experience is offered by special arrangement. Students are required to submit: an abstract concerning the results of their IRT Senior project, a paper (A4, 20-30 pages) on their research at the end of the exchange term, and an oral presentation on the results of their IRT Senior project near the end of the term.

After completing this module, the participants have gained practical experience in designing, implementing, and testing of applications for the internet of services within a small team and therefore gained significant knowledge and insights within the areas of mobile devices, communication and services, location-based services, cloud computing and digital communities. Furthermore, the participants have gained important knowledge of how to organize and realize IT projects, including controlling, reporting, planning, and communicating with external partners. 
 

The following topics are covered in this course: computer arithmetic, number formats (place value systems, fixed- and floating-point numbers); basics of digital design ((combinatorial logic, gates, truth tables, storage elements, finite state machines); basic technologies and components of a (secure) computer architecture; assembly programming (MIPS): assembly language, control flow, addressing; structure and operation of a multi-cycle data path (MIPS), structure and operation of a multi-cycle implementation; measuring and evaluating performance (SPEC benchmarks, Amdahl's law); structure and operation of a simple Von Neumann model; introduction to pipelining: concepts, hazards, forwarding, solutions; memory hierarchy, caches, virtual memory; input/output techniques (addressing, synchronization, direct memory access).