CAP 6315: Social Networks and Big Data Analytics


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Class Time: 2017 Spring
Classroom: 2017 Spring
Office Hour: 2017 Spring

Textbook: Reference books: Other Useful Resources:
Course Description:   This course teaches students basic concepts of big data analytics, with an application in social network analysis. The class will cover three major topics including big data analytics platform, MapRedue programming, and social network analytics. Detailed topics include MapReduce based computing framework, general algorithms for data analytics, trend and outbreak detection from social network streams. The lectures will include practical sessions dedicated to the implementation of big data analytics with selected programming language and tools.

Topics:


Lectures, Assignments, and Projects

Course Schedule by Week
Resources
Homeworks

Dataset

Project


Grading policy:
Homework 30
Mid-term 10
Term project 20
Student Presentation 10
Final Course Report 25
Participation 5

Your final grade will be based on the scores you have earned from the above categories (compared to the performance of other students in the class).

For the term project and the final course report, students will form groups to work on some identified research projects (after discussion with the instructor), investigate new social netowrk analysis designs, and carry out implementations and report the validations and final outcomes in the report. The report should follow the research publication format, including abstract, introduction, design, experiments, conclusion and reference.

Late policy:

All assignments are due midnight on the assigned due date. Please refer to the Assignments and Projects for details on submission. Late submission is allowable, however, the late penalty is -2pts/day.

Communication:

All important course communication will be done using your fau.edu email address. Sending email to me from another account is disencouraged, and if you do you must set the reply-to field to your FAU email account if the message concerns grading or evaluation in any way. You must also include your name in all messages concerning the course. If you have your FAU email forwarded to an AOL or other email account, read this important notice concerning blocking of FAU email.

All work in this course must be INVIDUAL effort unless specified otherwise.