Instructor:  Dr. Isabel K. Darcy,  Department of Mathematics, AMCS, and Informatics, University of Iowa
Office:B1H MLH
Phone: 335- 0778
Email: isabel-darcy AT uiowa.edu

Tentative Office hours: Tuesdays/Thursday 8:50 - 9:15am, 12:30 - 1:35pm and by appointment.

DEO Contact Information: Maggy Tomova, 14 MLH, maggy-tomova@uiowa.edu

Course website (including schedule): http://homepage.divms.uiowa.edu/~idarcy/COURSES/TDA/SPRING18/7450.html

Prerequisite: Graduate student standing. Note this is an interdisciplinary introduction to research course, and thus students from a wide variety of backgrounds are encouraged to take this course. We definitely won't avoid math, but we will cover all needed background to understand data visualization with TDA mapper. A couple of lectures will use linear algebra, but we will use a visual approach and a thorough understanding will not be required due to the interdisciplinary nature of this course.

Objectives and Goals of the Course: To learn introductory research skills in data analysis and visualization. Students will be graded (as described below) based on points earned. Students can choose from a variety of ways to earn points and thus objectives and goals may be individualized to meet the interests and background of each participant. Some standard goals include:

• Learn the basics of data analysis and visualization. Several classes will be held in a computer lab where students will learn to use software packages such as R. Some students may choose to delve deeper, but programming background is not required as we will start with the basics.
• Students will be encouraged, but not required, to work in groups. However, each member of a group will be graded individually. We will attempt to mimic how interdisciplinary research is conducted in real life. Thus students can choose to focus on different strengths. Moreover, a student may choose to contribute to multiple projects rather than focusing on a single project -- for example, several groups may consult with a student who has a strong background in statistics.
• The goal of most group projects will be to write a paper for possible submission to an undergraduate or research journal. Note achieving this goal is not required (but if you are interested in publishing your work, please let me know as I will try to facilitate the creation of groups with similar interests). Students will have access to a writing fellow to assist with their writing skills. Both feedback and points will be given throughout the semester on these projects (and other assignments).
• Presentation skills: Students will be given the opportunity to present their work both in class as well as outside of class at conferences and other venues. Feedback regarding slides, posters, and/or presentations will be provided.

Texts: None

Grading system:

You will need to earn a least 250 points to earn an S. Most of these points can be earned during Thursdays' labs.

You can earn points via HW, quizzes, exam, and project(s), etc.

Quizzes and Homework (approximately 100 points possible)

Midterm: 50 points. Tentative date: Thursday March 8.

We will not have a final exam.

Presentations (up to 150 points): We will have mini-presentations during week 7 as well as project presentations during week 15. You are also encouraged to give additional presentations both in class as well as outside of class as described here

Project: Points will be earned throughout the semester. I would expect a standard excellent class project would earn 250 points total, but a truly exceptional project could earn 500 points (but only 500 are needed for an A).

Note you will be turning in parts of your project throughout the semester and thus you will be earning points throughout the semester toward your project grade. Most Thursdays we will meet in a computer lab (B5 MLH). Many of these labs will be incorporated into your project.

While students are encouraged to work in groups, each student will be graded individually as described on the project webpage.

Most, if not all, projects will focus on analyzing data; but other ideas are welcome.

Please let me know if you would like to earn points using other methods (e.g. creating software, writing teaching materials, etc.).

Student Collaboration: You are encouraged to collaborate with other students on homework and projects.  Copying is not collaboration and will be prosecuted under scholastic dishonesty.  Any significant collaboration should be acknowledged.

Resources for Students:

From Writing Center website: Suggestions and feedback on all kinds of writing, from course papers to creative pieces and multimedia projects.

You can obtain feedback via individual appointments, online submissions or weekly appointments (for weekly appointments, space is limited so sign up NOW if you are interested).

From Speaking Center website: We work with a range of students from many disciplines on such issues as: effective participation in class discussions, crafting and delivering oral presentations, understanding unfamiliar cultural references, interview skills, creative performances, and speech anxiety.

The College of Liberal Arts and Sciences Policies and Procedures