Data Carpentry for Pharmacists

Teaching the tools to get computers to do cool science

Creative Commons License

Syllabus

Data Carpentry for Pharmacists

BPHS 3352 / PGEL 4001, 3 Credits, Fall 2018

Professor

Dr. Jeramia Ory

Office: Jones 1544

Email (best way to contact me): jeramia.ory@stlcop.edu

Phone: 314-446-8169

Times & Location

Monday & Wednesday 8:30 - 9:50

Office Hours

Times: By appointment

Location:

Appointments: Click here to schedule an appointment

Note: my schedule gets busy during the semester, and I’ve had bad luck setting office hours that students show up to. I have an open door policy, so please feel free to stop by at any time. However, if you want to make sure I’ll be in my office, I’ve cleared 12 hours during the week that are available to make appointments. Please try to schedule appointments as far in advance as possible. In general it will be very difficult to set up appointments less than 24 hours in advance.

Website

The syllabus and other relevant class information and resources will be posted at http://drlabratory.github.io/semester-pharmacy. Changes to the schedule will be posted to this site so please try to check it periodically for updates.

Course Communications

Email: jeramia.ory@stlcop.edu

Required Texts

There is no required text book for this class.

Course Description

Computers are increasingly essential to the study of all aspects of biology. Data management skills are needed for entering data without errors, storing it in a usable way, and extracting key aspects of the data for analysis. Basic programming is required for everything from accessing and managing data, to statistical analysis, to modeling. This course will provide an introduction to data management, manipulation, and analysis, with an emphasis on biological problems. Class will typically consist of short introductions or question & answer sessions, followed by hands on computing exercises. The course will be taught using R and SQLite, but the concepts learned will easily apply to all programming languages and database management systems. No background in programming of databases is required.

Prerequisite Knowledge and Skills

Knowledge of basic biology and chemistry.

Purpose of Course

In this course you will learn all of the fundamental aspects of computer programming that are necessary for conducting biological research. By the end of the course you will be able to use these tools to import data into R, perform analysis on that data, and export the results to graphs, text files, and databases. By learning how to get the computer to do your work for you, you will be able to do more science faster.

Course Goals and Objectives

Students completing this course will be able to:

Course Project

Projects offer an opportunity to work with bigger data-related computing tasks and learn specific computing tools you need for your research. Projects can involve programming, databases, or both. They should be on something you are excited about.

As a rough guideline projects should represent ~30-40 hours of work. Some class time will be provided for working on projects.

Get more details about the project from the Projects Introduction.

Teaching Philosophy

This class will be taught using a mix of short, introductory lectures and a more flipped, learner-centered approach. Learning to program and work with data requires actively working on computers. Flipped classes work well for all kinds of content, but I think they work particularly well for computer oriented classes. If you’re interested in knowing more take a look at this great info-graphic.

Instructional Methods

Students will be provided with either reading or video material that they are expected to view/read prior to class. Classes will involve brief refreshers on new concepts followed by working on exercises in class that cover that concept. While students are working on exercises the instructor will actively engage with students to help them understand material they find confusing, explain misunderstandings and help identify mistakes that are preventing students from completing the exercises, and discuss novel applications and alternative approaches to the data analysis challenges students are attempting to solve. For more challenging topics class may start with 20-30 minute demonstrations on the concepts followed by time to work on exercises.

Course Policies

Quiz/Exam Policy

There are no quizzes or exams in this course.

Attendance

Attendance in highly suggested, the material covered builds on previously discussed information. Please do not expect to be able to put off your reading for three weeks and magically understand everything in one crash study session. I will not provide handouts for a missed class without a formal excuse. There are always legitimate excuses for missing class, however, the definition of “legitimate” is at the discretion of the Dean. As per STLCOP policy:

“The School of Pharmacy expects student pharmacists to be present for course activities at which attendance is required as noted on a course schedule or syllabus, and to be present for all course-related assessments (e.g., exams, quizzes, case presentations, practicums, etc.). This is necessary to allow efficient and effective teaching of course material and active learning during class sessions, to show respect for instructors, and to ensure the security of examinations, quizzes, and other types of student assessments. However, the School of Pharmacy also recognizes that there are occasions when student pharmacist attendance at these activities is not possible or prudent. The attached policy is intended to inform P1-P3 student pharmacists of how absence requests and approvals will be processed. Starting today, all P1-P3 student pharmacists are expected to follow this policy when submitting requests for excused absences from class sessions. Please note that as stated in the policy, for expeditious processing, requests for excused absences should be directed via email to the Dean’s Office mailbox – not to the Dean of Pharmacy. Emails directed to Dean Canaday, Dean of Pharmacy, may take up to an additional 3 – 5 days for processing.”

Make-up policy

Late assignments will be docked 20% and will not be accepted more than 48 hours late except in cases of genuine emergencies that can be documented by the student or in cases where this has been discussed and approved in advance. This policy is based on the idea that in order to learn how to use computers well, students should be working with them at multiple times each week. Time has been allotted in class for working on assignments and students are expected to work on them outside of class. It is intended that you should have finished as much of the assignment as you can based on what we have covered in class by the following class period. Therefore, even if something unexpected happens at the last minute you should already be close to done with the assignment. This policy also allows rapid feedback to be provided to students by returning assignments quickly.

Assignment policy

Assignments are generally due by the start of the next class, and will be specified on the Github Classrooms assignment.

Course Technology

Students are required to provide their own laptops and to install free and open source software on those laptops (see Setup for installation instructions). Support will be provided by the instructor in the installation of required software.

Academic and General Conduct, Academic Dishonesty

Acts of academic dishonesty are outlined within the Academic Honor Code and Integrity Policy, which will be upheld to the highest standards in this course. For questions related to the Academic Honor Code and Integrity Policy, please contact the Academic Honor Code Committee co-chairs or the Dean of Arts and Sciences.

Special Accommodations:

If any student has a need for special testing arrangements, note-taking assistance, or other accommodations because of a documented disability, please feel free to discuss this with me privately. Rebecca Jones from the Student Affairs staff will need to evaluate and approve your accommodation needs.

Correspondance & Social Media

Grading Policies

Grading for this course will revolve around a combination of assignments (75%) and an independent project (25%).

All assignments will be equally weighted. One problem from each assignment (selected at the instructors discretion after the assignments have been submitted) will receive a thorough code review and a detailed grade. Other problems will be graded as follows:

Independent projects may focus on databases, programming, or a combination or the two.

Grading scale

Course Schedule

The details course schedule is available on the course website at: http://drlabratory.github.io/semester-pharmacy/schedule.

Disclaimer: This syllabus represents my current plans and objectives. As we go through the semester, those plans may need to change to enhance the class learning opportunity. Such changes, communicated clearly, are not unusual and should be expected.