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SENG550

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Scalable Data Analytics

Computer Science EN - Schulich School of Engineering

Subject

SENG - Software Engineering

Description

Sources and characteristics of large scale data, i.e., "big data", large scale data analysis, benefits of large-scale data analysis to various industry domains, programming paradigms and middleware technologies for scalable data analysis, algorithms that enable large-scale data processing, application of large scale data algorithms in selected application domains, e.g., Web user behaviour analysis and text processing, analytics frameworks.

Prerequisite(s): 3 units from Computer Science 319, 331 or Software Engineering for Engineers 338; and 3 units from Software Engineering 300, 301 or Software Engineering for Engineers 480.

Antirequisite(s): Credit for Software Engineering 550 and 501.05 will not be allowed.

Course Attributes

Fee Rate Group(Domestic) - D, Fee Rate Group(International) -C, GFC Hours (3-2)

Courses may consist of a Lecture, Lab, Tutorial, and/or Seminar. Students will be required to register in each component that is required for the course as indicated in the schedule of classes. Practicums, internships or other experiential learning modalities are typically indicated as a Lab component.

Component

LAB

Component

LEC

Units

3

Repeat for Credit

No

Subject code

SENG
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