Summer Courses

Course Description: This course is an introduction to the organization and programming of systems comprising multiple computers. Topics include the organization of multi-core computers, parallel computer clusters, computing grids, client-server systems, and peer-to-peer systems; computer networks and network protocols; network security; multi-threaded programming; and network programming. Programming projects will be required.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course provides an introduction to the design and analysis of algorithms. It covers a variety of classical algorithms and data structures and their complexity and will equip students with the intellectual tools to design, analyze, implement, and evaluate their own algorithms.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course provides an introduction to the theory of computation, including formal languages, grammars, auto-mata theory, computability, and complexity.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course provides a broad introduction to the principles and practice of modern data management, with an emphasis on the relational database model. Topics in relational database systems include data modeling; the relational model; relational algebra; Structured Query Language (SQL); and data quality, transactions, integrity and security. Students will also learn approaches to building relational database application programs. Additional topics include object-oriented and object-relational databases; semi-structured databases (such as XML); and information retrieval. A database project is required.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: An introduction to the theories and algorithms used to create artificial intelligence (AI) systems. Topics include search algorithms, logic, planning, machine learning, and applications from areas such as computer vision, robotics, and natural language processing. Programming assignments are an integral part of the course.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course is a study of the syntax and semantics of a diverse set of high-level programming languages. The languages chosen are compared and contrasted in order to demonstrate general principles of programming language design and implementation. The course emphasizes the concepts underpinning modern languages rather than the mastery of particular language details. Programming projects will be required.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course is an in-depth study of data communications and networks. The course covers design of, and algorithms and protocols used in, the physical, data link, network, transport, and application layers in the Internet; methods for modeling and analyzing networks, including graphs, graph algorithms, and discrete event simulation; and an introduction to network science. Programming projects will be required.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course provides a broad introduction to cybersecurity principles and practices, and emphasizes policies and mechanisms for building secure and trusted computer systems. It will cover cybersecurity principles, policies and mechanisms; core knowledge areas of data, software, component, connection, system, human, organizational and societal security; and crosscutting concepts of confidentiality, integrity, availability, risk, adversarial thinking, and systems thinking. Topics in privacy, and legal and ethical aspects will also be emphasized. Presentations, reports and projects are required. Students cannot take and receive credit for this course if they have credit for CSCI-655. This course requires the knowledge of computer science theory and concepts of computer systems.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course focuses on developing and improving verbal and written communication skills specific to the discipline of computer science. Topics include the different forms of writing in computer science (books, theses, journal articles, technical reports, manuscripts, etc.), writing styles of computer scientists, document readability and usability, documents for career readiness, effective presentations, teamwork and peer review, research methods, experimentation, documenting mathematics and algorithms, proper formatting of graphs, figures, and tables, and ethical, social, and professional issues facing Computer Scientists. This course is approved as Writing Intensive.

Session: 6-Week Session 2 (7/1-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course allows students to pursue two threads of research in computer science. One thread is the discovery and analysis of previous work in the field. Students will select, read and collectively discuss papers from conferences and journals in CS. A survey paper on a topic of the student's choice will be required. The other thread is an independent project. Students will select a topic, lay out weekly goals, and meet with the instructor weekly. A final report and presentation will be required.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course provides a broad introduction to the exploration and management of large datasets being generated and used in the modern world. First, practical techniques used in exploratory data analysis and mining are introduced; topics include data preparation, visualization, statistics for understanding data, and grouping and prediction techniques. Second, approaches used to store, retrieve, and manage data in the real world are presented; topics include traditional database systems, query languages, and data integrity and quality. Case studies will examine issues in data capture, organization, storage, retrieval, visualization, and analysis in diverse settings such as urban crime, drug research, census data, social networking, and space exploration. Big data exploration and management projects, a term paper and a presentation are required. Sufficient background in database systems and statistics is recommended.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course provides a broad introduction to database management systems including data modeling, the relational model, and SQL. Database system implementation issues are covered next, where the focus is on data structures and algorithms used to implement database management systems. Topics include physical data organizations, indexing and hashing, query processing and optimization, database recovery techniques, transaction management, concurrency control, and database performance evaluation. Current research topics in database system implementation are also explored. Programming projects, a term paper, and presentations will be required. Note: Students who take this course may not take CSCI-421 for credit.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: An introduction to the theories and algorithms used to create artificial intelligence (AI) systems. Topics include search algorithms, logic, planning, machine learning, and applications from areas such as computer vision, robotics, and natural language processing. Programming assignments and oral/written summaries of research papers are required.

Session: 6-Week Session 1 (5/15-6/26)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: An introduction to the underlying concepts of computer vision and image understanding. The course will consider fundamental topics, including image formation, edge detection, texture analysis, color, segmentation, shape analysis, detection of objects in images and high level image representation. Depending on the interest of the class, more advanced topics will be covered, such as image database retrieval or robotic vision. Programming assignments are an integral part of the course. Note: students who complete CSCI-431 may not take CSCI-631 for credit.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course offers an introduction to supervised machine learning theories and algorithms, and their application to classification and regression tasks. Topics include: Mathematical background of machine learning (e.g. statistical analysis and visualization of data), neural models (e.g. Convolutional Neural Networks, Recurrent Neural Networks), probabilistic graphical models (e.g. Bayesian networks, Markov models), and reinforcement learning. Programming assignments are required.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course offers an introduction to supervised machine learning theories and algorithms, and their application to classification and regression tasks. Topics include: Mathematical background of machine learning (e.g. statistical analysis and visualization of data), neural models (e.g. Convolutional Neural Networks, Recurrent Neural Networks), probabilistic graphical models (e.g. Bayesian networks, Markov models), and reinforcement learning. Programming assignments are required.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course provides an introduction to cryptography, its mathematical foundations, and its relation to security. It covers classical cryptosystems, private-key cryptosystems (including DES and AES), hashing and public-key cryptosystems (including RSA). The course also provides an introduction to data integrity and authentication. Note: students who complete CSCI-462 may not take CSCI-662 for credit.

Session: 6-Week Session 1 (5/15-6/26)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course provides an introduction to cryptography, its mathematical foundations, and its relation to security. It covers classical cryptosystems, private-key cryptosystems (including DES and AES), hashing and public-key cryptosystems (including RSA). The course also provides an introduction to data integrity and authentication. Note: students who complete CSCI-462 may not take CSCI-662 for credit.

Session: 6-Week Session 1 (5/15-6/26)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: This course provides a graduate-level introduction to the concepts and techniques used in data mining. Topics include the knowledge discovery process; prototype development and building data mining models; current issues and application domains for data mining; and legal and ethical issues involved in collecting and mining data. Both algorithmic and application issues are emphasized to permit students to gain the knowledge needed to conduct research in data mining and apply data mining techniques in practical applications. Data mining projects, a term paper, and presentations are required.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.

Course Description: Project capstone of the master's degree program. Students select from a set of possible projects and confirm that they have a project adviser. Students enroll in a required colloquium component that meets weekly, during which they present information, related to their projects. Projects culminate with delivery of a final report and participation in a poster session open to the public.

Session: 12-Week Session (5/15-8/13)

For prerequisites, availability, other details and to register, go to http://sis.rit.edu/.