Computer Science & Engineering

Machine Learning for Big Data / Statistics for Big Data

Course number: 
CSE 599 C1 / STAT 592

T/Th 10:30-11:50, EEB 045

Today, data analysis methods in machine learning and statistics play a central role in industry and science. The growth of the Web and improvements in data collection technology in science have lead to a rapid increase in the magnitude and complexity of these analysis tasks. This growth is driving the need for scalable, parallel and online algorithms and models that can handle this "Big Data". This course will provide a broad foundation for this timely challenge.

Computational Biology

Course number: 
CSE 527

Biological sciences are becoming data-rich and information-intensive. Nowadays it became possible to obtain very detailed information about living organisms. For instance, we can obtain DNA sequence (3 billion-long string) information, expression (activity) levels of >20,000 genes, and various clinical measurements from humans. The growing availability of such information promises a better understanding of important questions (e.g. causes of diseases).

Introduction to Databases

Course number: 
CSE 344

Databases are at the heart of modern commercial application development. Their use extends beyond this to many other environments and domains where large amounts of data must be stored for efficient updated, retrieval, and analysis. The purpose of this course is to provide a comprehensive introduction to the use of management systems for applications. Some of the topics covered are the following: data models (relational and XML), query languages (SQL, catalog, XQuery), transactions, parallel data processing, and database as a service.

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