Email: abrooks[at]physics.rutgers.edu
Office hours: TBD
Teaching Assistant's email: TBD
Teaching Assistant's office hours: TBD
This is a 1.5 credit Pass/No-credit course introducing first year students to research and the research community in Physics & Astronomy. There are three components to the course: (i) introduction to coding in Python; (ii) a hands-on research project in a sub-field of Physics; and (iii) interactive professional development discussions.
No previous research or computing experience is assumed. We will start at the beginning!
Prerequisites: None. Registration requires special permission of Undergraduate Program Director, upd@physics.rutgers.edu
Foundational Coding Skills:
Students will learn the fundamentals of coding in Python and the basics of data visualization.
Understanding of Research:
Students will learn the framework of a research project via analysis on data to address a science
question. Students will also learn how to create a final work product in the form of a figure, and
work on science communication skills via presentation of their results.
Community Building and Professional Development
Students will build their network within the Physics and Astronomy department via connections with
peers, near peer mentors, graduate students, and faculty. Students will also develop skills that
will help them succed in Physics and Astronomy, both during their undergraduate career at Rutgers and beyond.
There will be one 80-minute lectures per week in Allison Rd Classroom (ARC) 333 on Busch Campus. Attendance and active participation in class is required.
The first part of the course we’ll equip you with the skills you need to start working on an
astro/physics research project. These skills include programming in Python, and critical reading and
writing of science literature. No previous research or computing experience is assumed.
Computer Programming: Introduction to working in a UNIX-based environment, and introduction
to programming in Python. Many of the lessons will be asynchronous, leaving class time open for
active coding of assignments with support from the instructor and TA.
Understanding Science and Reading Scientific Papers: We will build up to reading peer-reviewed
articles in scientific journals. Through these readings we will become familiar with the methods
and results of some recently published research.
The second part of the course will be guided research with your research mentor and your class partner(s).
Research Projects:>There are several projects proposed by Rutgers Physics and Astronomy faculty,
postdocs, and graduate students. You will rank the projects that interest you most, and will be assigned
to projects in teams of two (three if necessary). Examples of past project descriptions can be found
here. Your research mentor
will lead one-on-one, hands-on lessons for you and your partner(s) throughout the second half of the
semester.
Research Presentations:One of your most important roles as a scientist is to communicate your
research to your colleagues and the broader public. At the end of the semester, each research team
will give a 5-minute presentation to research collaborators and mentors, which will also be open to
the Physics and Astronomy Department. You will receive public speaking training in class.
The third part of the course (interweaved with the other two) will be focused on professional
development and how to build experiences that make you competitive for different undergraduate opportunities.
Professional Development: We will cover a variety of topics, including career paths in physics
and astronomy, learning strategies, Rutgers resources, speaking skills, and how to find and apply
for internships. This will give you a head start on pursuing opportunities after the semester is over.
This syllabus may be modified as the semester progresses.
Social events will be scheduled throughout the semester. We will schedule these soon and update the calendar accordingly.
Week |
Topics |
Due |
| Sept 8 | Introduction to the seminar | |
| Sept 15 | Learning Strategies and RU resources; reading a popular science article |
Writing assignment #1; Meet with TA |
| Sept 22 | Intro to Unix and text editors | Unix exercises |
| Sept 29 | Intro to Python: notebooks/numpy | Coding assignment #1 |
| Oct 6 | Research project pitches | Ranked project choices |
| Oct 13 | Python coding, cont'd: loops and functions | Meeting with TA; Coding assignment #2 |
| Oct 20 | Python cont'd: plotting | Coding assignment #3; Meet with project mentor(s) |
| Oct 27 | Internships, REUs, etc | Writing assignment #2; Meet with project mentor(s) |
| Nov 3 | Research projects | Read/discuss relevant paper with mentor |
| Nov 10 | Research projects | Develop elevator pitch for project |
| Nov 17 | Research projects | Write Intro slides for research talk |
| Nov 24 | Research projects; How to give a talk | Methodology slides preparation |
| Dec 1 | Navigating RU; UPD; career services | Research; slide preparation |
| Dec 8 | Final presentations to department |
The course will have a graduate Teaching Assistant (TA). The TA is an additional resource for students to use throughout the entire academic year (yes, even after the seminar ends), and maybe even beyond. The TA is available to guide students on homework, research, selecting courses, and in-class assignments. The TA will be present at the in-class exercises. The TA is around to help with anything students may want to talk about. In fact, students will be required to periodically meet with the TA to guarantee that they take advantage of this excellent resource!
The seminars is credit/no credit. To receive credit for the seminar, students are expected to participate. Every writing and coding assignment will be graded on a 10 and 20 point scale, respectively. To receive credit for the seminar, students are expected to achieve 70% of the points. Additionally, students must participate in the final research project and presentation, or they will not receive credit for the seminar. Finally, the seminar requires that students not miss more than three classes. Missing more than three classes will result in no credit. If you expect to miss a class, please use the University absence reporting website to indicate the date and reason for your absence. An email is automatically sent to me.
Late homework: Seek arrangement with the instructor at least 24 hours in advance if you think you have a legitimate excuse for late work.
Re-grades: You will be allowed to make corrections to any mistakes on the coding assignments and have it regraded.
All assignments will be found under the "Modules" link from our Canvas course site, and you will be required to submit your completed assignments through Canvas as well.
Please note that for each writing assignment, I will require the use of turnitin, which will scan your document for signs of plagiarism (which is never allowed). When your writing assignments ask you to answer straightforward questions about reading assignments, please do your best to answer the questions using your own words and explanations. Students will be held to the Rutgers policy on academic integrity.
Coding assignments are meant to be straightforward practice of what we have learned in class. All assignments come from the online resource "Learn Python The Hard Way" (LPTHW). To complete an assignment, please create a new Jupyter notebook in your home directory when you are logged in to the class server.
There is no textbook for this seminar, but you should expect to take notes. Note that access to a computer outside of the classroom time is also required. We are happy to help identify resources if access to computing is an issue.
The Python lessons will be taught from instructional iPython Notebooks which will be found in Canvas.
There are also many freely available textbooks on programming in Python, which you could optionally use for Python help (no readings will be assigned from these books). Take a look at this webpage's free Python texts labeled "beginner" for supplemental texts that might be useful programming references appropriate for this course. Three reference texts that I recommend include Learn Python the Hard Way (which isn't actually hard!), A Byte of Python, and A Whirlwind Tour of Python.
Here are some web resources you may find illuminating or indispensable:
Students with disabilities should consult the department policy.
Disability Services
(848) 445-6800 / Lucy Stone Hall, Suite A145, Livingston Campus, 54 Joyce Kilmer Avenue, Piscataway, NJ 08854
Rutgers University welcomes students with disabilities into all of the University's educational programs.
In order to receive consideration for reasonable accommodations, a student with a disability must contact
the appropriate disability services office at the campus where you are officially enrolled, participate
in an intake interview, and provide documentation.
If the documentation supports your request for reasonable accommodations, your campus’s disability services office
will provide you with a Letter of Accommodations. Share this letter with your instructors and discuss the
accommodations with them as early in your courses as possible. To begin this process, please complete the
Registration form on the ODS web site.
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Astrophysics at Rutgers • Department of Physics and Astronomy • Rutgers University
Last updated: Mar 27, 2024 by Alyson Brooks