Course number: BOT6935/ZOO6927
611 Carr Hall
Fridays periods 6-8 (12:50 - 3:50 pm)
Instructor: François Michonneau, email@example.com, Dickinson Hall
Office hours: By appointment only
Course communication: All communications for this course will take place on Github.
Enrollment cap: 12
As science becomes increasingly more data and computation intensive, maintaining the ability to build on our own or other’s prior work requires that the process that takes data and other inputs all the way to the results presented in a paper is documented and made available in full detail.
This course will teach participants how to develop workflows going from raw data to graphics and statistical analysis, using the programming language and statistical environment R. Over the course of the semester, participants will learn the skills to write scripts to automate data formatting and analysis, making their studies replicable.
There will be three 3-hour long lectures on January 16th, Februrary 13th, March 13th. The other weeks, the lab will be open and the instructor will be present to help working towards the final project and the package presentation.
Towards the end of the semester, each week, a group will present a package of their choice to the rest of the class. This presentation will include a general overview of the package as well as an hands-on part where everyone in the class will have the opportunity to use the package. A draft of the handout and exercises will need to be posted on Github at least 1 week before presentation so that feedback can be provided.
It’s easier to learn programming by doing. Because many of the concepts covered in the class will be new, they will require a significant time commitment to embrace them. Recognizing that time in graduate school is precious, and that the skills taught in this class should be directly applicable, students will work in groups to design a project that will improve, facilitate their current or future research. Working on the project will take most of our classroom time (and will also take time outside of class, actually it has been recommended that students should program at least every other day when learning).
This schedule is tentative. Topics and coverage may change. Other topics will be covered in short lectures depending on the interests of the class and needs for the final projects (potential topics include: data manipulation, working with dates, regular expressions, etc.)
|January 9||Software installation, organization of the class, how to use Github|
|January 16||Introduction to programming in R|
|January 23||Data frames part 1||Project pitches 1|
|January 30||Data frames part 2||Project pitches 2|
|February 6||Data frames part 3||groups are formed|
|February 13||Flow and functions||Project updates|
|February 20||Advanced functions + Introduction to GitHub||Project updates|
|Feburary 27||Review and challenges||Project updates|
|March 13||markdown + Open Lab|
|March 20||Open Lab||François out of town|
|March 27||Open Lab||François out of town|
|April 3||Open Lab|
|April 6 (9:35-12:35)||Your first R package|
|April 10||Open Lab||Package demonstration 1|
|April 17||Open Lab||Package demonstration 2|
|April 24||—||Project presentations|
Grading Scale (& GPA equivalent):
Participation online (commenting on issues/submit pull requests, etc.) and in class: 34% Package demonstration: 33% Final Project presentation: 33%
No harassment of participants in any form will be tolerated. Harassment includes offensive verbal comments related to gender, sexual orientation, disability, physical appearance, body size, race, religion, sexual images in public spaces, deliberate intimidation, stalking, following, harassing photography or recording, sustained disruption of talks or other events, inappropriate physical contact, and unwelcome sexual attention.
All communication should be appropriate for a professional audience including people of many different backgrounds. Be kind to others. Do not insult or put down other attendees. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate.
Attendees violating these rules may be asked to leave the classroom at the sole discretion. Participants asked to stop any harassing behavior are expected to comply immediately.
Be careful in the words that you choose. Remember that sexist, racist, and other exclusionary jokes can be offensive to those around you.
If a participant engages in behavior that violates this code of conduct, the instructor may take any action they deem appropriate, including warning the offender or expulsion from the classroom.
Students who will require a classroom accommodation for a disability must contact the Dean of Students Office of Disability Resources, in Peabody 202 (phone: 352 -‐ 392 -‐ 1261). Please see the U niversity of Florida Disability Resources website for more information at: http://www.dso.ufl.edu/drc/ . Note that the student should provide documentation of a requirement for accommodation by the second week of classes . No accommodations are available to students who lack this documentation , and accommodations are not retroactive . It is the policy of the University of Florida that the student, not the instructor, is responsible for arranging accommodations when needed. Once notification is complete, the Dean of Students Office of Disability Resources will work with the instructor to accommodate t
Resources are available on-campus for students having personal problems or lacking clear career and academic goals.
The resources include:
UF Counseling & Wellness Center, 3190 Radio Rd, 392-‐1575, psychological and psychiatric services.
Career Resource Center, Reitz Union, 392-‐1601, career and job search services.
Many students experience test anxiety and other stress related problems. “A Self Help Guide for Students” is available through the Counseling Center (301 Peabody Hall, 392-‐1575) and at their web site: hWp://www.counsel.ufl.edu/ .
All students registered at the University of Florida have agreed to comply with the following statement:
“I understand that the University of Florida expects its students to be honest in all their academic work. I agree to adhere to this commitment to academic honesty and understand that my failure to comply with this commitment may result in disciplinary ac3on up to and including expulsion from the University.”
In addition, on all work submiWed for credit the following pledge is either required or implied:
“On my honor I have neither given nor received unauthorized aid in doing this assignment.”
If you witness any instances of academic dishonesty in this class, please notify the instructor or contact the Student Honor Court (392-1631) or Cheating Hotline (392‐6999). For additional information on Academic Honesty, please refer to the University of Florida Academic Honesty Guidelines at: http://www.dso.ufl.edu/judicial/procedures/academicguide.html .