The course will include 3-4 programming assignments as well as a final project. Grading will be broken down as follows:
- Assignments: 40%
- Project: 50%
- Class participation: 10%
Class participation includes attending class, speaking up in class, participating in the online forum, and helping out fellow students. Students are expected to attend class, and may miss up to 2 classes without penalty. Missing more than 2 classes will result in a reduction of the class attendance grade.
The intent of the programming assignments is to get you familiar with some of the data analysis tools that organizations like Twitter use to process big data. Thus, they will be exercises and not necessarily connected to one another.
Because we are working with the Twitter engineers on the design of the assignments, we do not have all the details planned out fully in advance. Below is a rough outline of the timeline for the assignments, but this is subject to change. If you are not comfortable with this, then please do not take the course:
- Assignment 1: Programming with Pig /Hadoop (due 9/14)
- Assignment 2: Programming streaming to find trends using twitter4j API (due 10/1)
- Assignment 3: Graph algorithm assignment (due 10/15)
Students must agree to work on projects on teams of size three as a requirement of the course; we do not have the resources for individuals or two-person teams.
The project will have several deliverables, some graded and some not. These will include but not be limited to:
- A proposal, which must be approved before you can proceed
- A team structure, which must also be approved
- A literature review (graded)
- The project itself: design, coding, execution (graded)
- The presentation of the project (at Berkeley, and optionally at Twitter headquarters)
More details of project grading will come later.
About Working With Other Students
Some assignments will require you to do your own work; others will allow for team work. Each assignment will state which is the case explicitly. For those assignments requiring individual work, discussion with instructors and classmates is allowed/encouraged, but each student must turn in individual, original work and cite appropriate sources where appropriate. Please take the time to read the following documents to get a good understanding of the rules surrounding academic integrity: