General Information

When:   Tue/Thu, 9:30 am - 10:45 am
Where: 233 David Lawrence Hall
Instructor: Prof. Alexandros Labrinidis (contact)
TA: Anatoli Shein (contact)

Purpose: This course will provide an overview of data science technologies and techniques, offering a holistic view of the field, from data management & manipulation, to data analysis, and data presentation. The course will cover the main data management/querying paradigms (Relational/SQL, XML/XQuery, RDF/SPARQL, Graph/Cypher) along with information retrieval, data warehousing, data mining, data visualization, and other data analysis topics. The course will utilize Python as the default programming language and leverage existing libraries, as appropriate.
Prerequisites: A grade of C or better in CS 1501 is required (or permission of the instructor). Good working knowledge of Java and familiarity with Unix are assumed. Having passed a statistics course is highly encouraged.
Anti-requisites: Given the significant overlap with past offerings of CS1655, students who have already passed CS1655 will not be allowed to register for this class. The same applies for students who have passed CS1699 in the Spring 2015 term.
Enrollment: 40 students currently registered
Textbook: There is no single textbook with enough coverage of all the material that we will discuss in this class. We will rely on online references and also on O'Reilly's Safari Bookshelf for which the University has institutional access (i.e., you will not have to buy extra books).
Web page:
Class Blog:
Socrative: (OR download the Socrative app and select Room CS1656)

April 23: Final Exam + Office Hours
April 21: All lecture and recitation notes have been uploaded
April 18: Last assignment released
February 20: Posted recommender systems material
February 7: Posted material on data warehousing and data summarization/visualization

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