DS504/CS586 - Big Data Analytics - Spring 2020

Grading:

Projects

We aim to do all work in teams, typically 2 to 4 per team. There will be several smaller course projects, and one more comprehensive semester-long project. These projects typically correspond to an implementation of some idea, application of some technology, or a research report. Projects can involve the utilization of existing big data analytics tools to extract knowledge from data sets; the development of new or the extension of existing tools with advanced features; the realization of a research idea or data mining algorithms that you find in the literature into software as proof of concept; or a comparative study of multiple alternative approaches for tackling a given problem.

You are expected to produce and submit a professional report on your project, complete with a clear motivation, full description with examples, and careful evaluation of the effectiveness of the solution.

The teams may also be asked to present their projects to the instructor.

Homeworks and Other Tasks

Homeworks will include doing your readings before you come to class, the writing of critiques on the assigned readings, and the preparation of presentations.

Grading Philosophy

Final grades will reflect the extent to which you have demonstrated understanding of the material, completed the assigned tasks, and participated actively in class. See the break-down of points above. The base level grade will be a "B" which indicates that the basic objectives for the course have been met. That is, if you do everything I expect of you (at a satisfactory level), you should expect to receive a "B" for the course. A grade of "A" will indicate significant achievement beyond the basic objectives - basically an excellent job. While a grade of "C" indicates that not all basic objectives were met, but work was satisfactory for credit. A "D" grade will be given if the student's performance in the course is unacceptable for graduate credit. A grade of "F" indicates that the student did not perform work suitable for receiving graduate credit, and this is usually associated with academic dishonesty or simply you stopping to do any work.

Late Policy

Reviews, presentations, and quizzes cannot be late. Projects can be submitted late (unless otherwise specified as part of the project assignment) with the following penalties: one day late, you loose 20% of max score, two days late, you loose 50% of max score, and three days late, you loose 100% of max score. Adjustments to this policy are at discretion of the instructor.