Please see departmental courses page for the latest schedule.
Introduction to database structure, organization, languages, and implementation. Relational and object-oriented models. Query languages, query processing, normalization, file structures, concurrency control and recovery algorithms, and distributed databases. Coverage of modern applications such as the Web, but with emphasis on Database Management Systems internals.
Prerequisites: CS 22 and 31
Explores the fundamental principles and practice underlying networked information systems, first we cover basic distributed computing mechanisms (e.g., naming, replication, security, etc.) and enabling middleware technologies. We then discuss how these mechanisms and technologies fit together to realize distributed databases and file systems, web-based and mobile information systems.
Prerequisite: CS 32 or 36
Data is the new soil of business and (soon) at the core of essentially all domains from material science to healthcare. Mastering big data not only requires skills in a variety of disciplines from distributed systems over statistics to machine learning, but also requires an understanding of a complex ecosystem of tools and platforms. This seminar will try to shed some light into the complex space of data science covering aspects from data management, distributed algorithms, virtualization, data mining, machine learning, and statistics. We will discuss how these techniques complement each other to make sense of data at massive scale.
Prerequisite: CS 32 and 127, or equivalents, or instructor permission.
In-depth treatment of advanced issues in database management systems. Topics vary from year to year and may include distributed databases, mobile data management, data stream processing and web-based data management.
Prerequisite: CS 127
Sensor networks combine sensing, computing, actuation, and communication in a single infrastructure that allows us to observe and respond to phenomena in the physical and cyber world. The sensors range from tiny ‘smart dusts’ to dime-sized RFID tags and large-scale weather sensors. This course will cover the state-of-the art in designing and building sensor networks, focusing on issues that revolve around data and resource management.
This course explores data and resource management issues that arise in the design, implementation, and deployment of networked information systems by covering the state of the art in research and industry. Topics include mobile data access and dissemination, sensor networks, and Internet-scale information systems and services.
Prerequisites: CS 138 or permission of the instructor
Enabling visual data exploration at “human speed” is key to democratizing data science and maximizing human productivity. Unfortunately, traditional data management systems like PostgreSQL, Microsoft SQL Server, or more recent analytical frameworks, like Hadoop, Spark, and many others, are ill-suited for that purpose. This seminar course will cover the State-of-The-Art data exploration systems that better support the requirements of interactive data explorations; students are expected to build a prototype data exploration tool, and write a short research paper on their contributions.
Prerequisites: One of CSCI 0320, CSCI 0330; and one of CSCI 1270, CSCI 1951-A, CSCI 1670 or permission of the instructor