General Information

When:   Tue/Thu, 1:00 pm - 2:15 pm
Where: 5129 Sennott Square Building (map)
Instructor: Prof. Alexandros Labrinidis (contact)
TA: Phuong Pham (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, 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: 48 students currently registered
Textbook: There is no single textbook with enough coverage of all the material that we will discuss in this class. In addition to the material prepared by the instructor, we will rely on other online material and on selected book chapters, available from O’Reilly’s Safari Bookshelf for which the University has institutional access (i.e., you will not have to buy extra textbooks).
Web page:
Class Blog:
TopHat: (New)

December 3: Assignment #5 released
December 2: Assignment #4 deadline now Dec 6th (no late submissions allowed)
November 13: Assignment #3 deadline extended by one day
October 5: Assignment #2 posted
September 25: Assignment #1 due date extended by 2 days

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