Mass Data Processing/Cloud Computing
Summer 2010

Instructor: Hongfei YanúČBo Peng

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Textbook

Prerequisites

Some experience with computer programming, preferably in Java. No previous knowledge of distributed computation is assumed.

Format

The course is lecture-based with homework, labs and a final course project. There are also regular assignments, which often involve implementation of an algorithm and/or experimentation with real text data.

Course Policy and Grading

  1. Attendance
  2. Attendance is mandatory, but use common sense if you are sick or have other constraints. Note that attending the lectures is often the only chance for you to learn certain materials as you may not find them in any textbook or other readings.

  3. Assignments
  4. The assignments are designed to ensure that students have a deep and precise understanding of the lectures, thus the students are required to complete them independently. However, discussion with others is allowed to the extent of helping understand the material. The purpose of student collaboration is to facilitate learning, not to circumvent it. The actual solution must be done by each student alone, and the student should be ready to reproduce their solution upon request. In any case, you must exercise academic integrity.

    Note that: Late submission of an assignment would result in a zero grade for the assignment.

  5. Grading
  6. Grading will be based on the following weighting scheme.

Acknowledgements:

This course is supported by Google Inc,