Policies

Meetings

We have weekly lectures Wednesday mornings 9-9:50 am in 100 Broad. On Tuesdays, you may attend one of two lab sessions, 1-4 pm, or 7-10 pm, both in 200 Broad. Bring your laptop and charger. You should always attend the same lab session (either 1 pm or 7 pm), unless you have a conflict and let the course instructors know.


Lab sessions

The lab sessions are spent working on the week's homework, which always includes working with real data sets with your teammates. You are expected to be working diligently during this time, and it is a golden opportunity to do so. The course staff will be there to help you.


Lessons and lesson exercises

With the exception of the first one, prior to each lab session, you must go through the lessons listed on the course website for the week. These will give you the requisite skills you need to work on the homework problems of the week. To verify completion of the lessons and to identify points of confusion ahead of time, you will individually need to commit a small exercise to the repository in the GitHub group. Place this in the lesson_exercises/ directory in a file named l##_your_name.ipynb, where ## is the number of the lesson. Lesson exercises are due at 11 am the Tuesday of the lab session.


The lesson exercises are not graded for correctness, but for thoughtfulness. A perfectly reasonable answer to a problem in a lesson exercise is, "I am really having trouble with this concept. Can you please go over it in class?"


The BE/Bi 103 GitHub group

A BE/Bi 103 GitHub group is set up for the class. You will be part of the group through your GitHub account. All homeworks and lesson exercises are submitted by pushing to the GitHub repository.



Homework

We typically have weekly homework assignments. These consist almost entirely of working up real data sets.


Data analysis is almost always a collaborative effort in both research and industry. Therefore, you will be assigned to teams of three (possibly with a couple teams of four depending on course enrollment). You will submit your homework as a team. The following homework policies apply.



Grading

85% of your grade is determined from homework. Everyone on your team will get the same grade on the homework.


15% of your grade is determined from submission of your lesson exercises and participation in the lab sessions. You are expected to work together with your team members and course instructors with your full attention during the lab sessions.



Collaboration policy and Honor Code

Some of the data we will use in this course is unpublished, generously given to us by researchers both from Caltech and from other institutions. They have given us their data in good faith that it will be used only in this class. It is therefore imperative that you do not disseminate data sets that I ask you not to distribute anywhere outside of this class.


Since the homework is done in assigned teams, you obviously should collaborate heavily with the other members of your team. You are free to discuss the homework with other teams, including via Ed, but the work you submit must be the work of your own team.


You may not consult solutions of homework problems from previous editions of this course.


You are free to consult references, literature, websites, blogs, etc., outside of the materials presented in class. (The exceptions are places where homework problems are completely worked out, such as previous editions of this or other courses, or other students' work.) In fact, you are encouraged to do so. If you do, you must properly cite the sources in your homework. Be warned: doing homework by Google fishing will not work! The problems are too open ended and the techniques are too varied.



Excused absences/extensions

Under certain circumstances, missed lab or lecture sessions will be excused and extensions given on the homework without costing grace days. The reasons for the excuses or extensions must be compelling, such as health or family issues. Graduate school interviews are common during the winter term, and extensions are also typically granted for these. In all cases extensions must be requested from the course instructor.



Course communications

You are free to contact the course staff at any time, but we encourage you to use the class Ed page for questions course topics and homework. Most of our mass communication with you will be through Ed, so be sure to set your Ed account to give you email alerts if necessary.


Prerequisites

BE/Bi 103 a or equivalent is a prerequisite for this course. In particular, you should be comfortable using Python fo scientific computing, including use of Numpy, Pandas, Jupyter/JupyterLab with LaTeX, and plotting, e.g., with Bokeh. You should also be able to use Git. If you need to brush up on these skills, you can visit the BE/Bi 103 a website. In particular, you should check out the lessons on Jupyter, LaTeX, and Git since all assignments in this class use these tools.