CS627: Data Science Programming

image: 0_Users_kain_CloudStation_CSLU_edu_teaching_CS627-data-science-programming_admin_rp.png
Winter 2018
Class time:
Tuesdays and Thursdays, 2pm-3:30pm
Class location:
Gaines Hall 5

Course Description

This course represents a best-of compilation of concepts, practices, and R- and python-based software libraries (all free, open-source, and unrestricted) that allow for a relatively rapid, straight-forward, and easy-to-maintain implementation of new ideas and scientific questions. Students will gain awareness and initial working knowledge of some of the most fundamental computational tools for performing a wide variety of academic research. As such, it will focus on providing breadth instead of depth, which means that for each concept we will talk about motivation, key concepts, and concrete usage scenarios, but without mathematical background or proofs, which can be acquired in more specialized classes. In this class we will: use R for data exploration and visualization, write programs in python, perform numeric tasks using numpy and scipy, analyze data using pandas, discuss audio and image processing using scipy.signal and scikit-image, apply machine learning algorithms using scikit-learn, visualize data using matplotlib and pyqtgraph, use QT to build graphical user interfaces, learn how to version control files with git, address performance issues via compilation/profiling/parallelization tools, and much more.

Credit Hours


Pre-requisites or Concurrent Enrollment Requirements

There are no specific class pre-requisites for this course, but previous programming experience is required.

Faculty Information

Alexander Kain

Office Hours:
By appointment

Alison Presmanes Hill

Office Hours:
By appointment

Steven Bedrick

Office Hours:
By appointment

Course Objectives, Competencies, and Outcomes

After completing this course, students will be able to start their own research project with a minimum of startup time, since they can leverage on their awareness and initial knowledge of a wide range of supporting programming environments.

Required Texts or Readings


Supplemental or Suggested Readings or Reference Materials

Attendance Requirements

Students are expected to attend each lecture.

Grading Criteria, Academic Standards, & Release of Final Grades

20% of the grade will depend on in-class discussion and participation. Homework/project assignments will make up 80% of the grade. There is a penalty for turning in homework/projects late.

Homework Assignments

There may be several software-related / code-writing assignments. Please comment your code, and provide transcripts of example runs and figures of results, if applicable. Submit your files (code and/or any accompanying documents) as a single archive file (.zip, .tgz, etc.) by email. Please name the file by your last name! Homework assignments are due 1 week from the date of assignments, before class.

OHSU SoM Graduate Studies Grade Submission Policy

Graduate Studies in the OHSU School of Medicine is committed to providing grades to students in a timely manner. Course instructors will provide students with information in writing at the beginning of each course that describes the grading policies and procedures including but not limited to evaluation criteria, expected time needed to grade individual student examinations and type of feedback they will provide.
Class grades are due to the Registrar by the Friday following the week of finals. However, on those occasions when a grade has not been submitted by the deadline, the following procedure shall be followed:
  1. The Department/Program Coordinator will immediately contact the Instructor requesting the missing grade, with a copy to the Program Director and Registrar.
  2. If the grade is still overdue by the end of next week, the Department/Program Coordinator will email the Department Chair directly, with a copy to the Instructor and Program Director requesting resolution of the missing grade.
  3. If, after an additional week the grade is still outstanding, the student or Department/Program Coordinator may petition the Office of Graduate Studies for final resolution.
Final course grades will be posted with the OHSU Registrar the Monday following the last day of the term. OHSU's grading system for official grade reports includes: 4.0 = Exceptional 3.0 = Superior 2.0 = Average 0.0 = Failure

Copyright Information

Every reasonable effort has been made to protect the copyright requirements of materials used in this course. Class participants are warned not to copy, audio, or videotape in violation of copyright laws. Journal articles will be kept on reserve at the library or online for student access. Copyright law does allow for making one personal copy of each article from the original article. This limit also applies to electronic sources.

Syllabus Changes and Retention

This syllabus is not to be considered a contract between the student and Graduate Studies. It is recognized that changes may be made as the need arises. Students are responsible for keeping a copy of the course syllabus for their records.

Commitment to Equity and Inclusion

Oregon Health & Science University is committed to creating and fostering a learning and working environment based on open communication and mutual respect. If you encounter sexual harassment, sexual misconduct, sexual assault, or discrimination based on race, color, religion, age, national origin or ancestry, veteran or military status, sex, marital status, pregnancy or parenting status, sexual orientation, gender identity, disability or any other protected status please contact the Affirmative Action and Equal Opportunity Department at 503-494-5148 or aaeo@ohsu.edu. Inquiries about Title IX compliance or sex/gender discrimination and harassment may be directed to the OHSU Title IX Coordinator at 503-494-0258 or titleix@ohsu.edu.




New material is bolded. Subject to change.


Lectures are available here: http://cslu.ogi.edu/multimedia/Data_Science_Programming. Use the following credentials:
User name = csee
Password = TBD