Your Professor:
Matt Lavin
My Email:
lavinm@denison.edu
My Office:
Knapp 205-B
Office Hours
1:30-3:00 p.m. MW by appointment and Th 10-11:30 drop-in
Our Classroom:
BMRG 115
When We Meet:
T 11:30 a.m.-12:20 p.m.
The Data Analytics colloquium involves three central learning components. 1) regular engagement with guest presentations and community activities in data analytics, 2) group discussion featuring critical analysis and connection of themes found in the guest presentations and in related data analytics topics, and 3) preparation and refinement of professional communication skills necessary for the required internship component of the data analytics major. This course provides an opportunity for students to connect on data analytics ideas and applications, using a range of perspectives that may or may not be normally encountered in a traditional course. Students will develop the knowledge, skills, and methods they need to progress to more advanced learning, while also creating bridges with members of the data analytics community within and outside of Denison. The course must be taken twice by majors: once as a sophomore, and again as either a junior or senior.
This semester, I will be using a mix of drop-in office hours and in-person appointments via Google Calendar. For office hours by appointment, visit my appointment page, where you will see a real-time account of when I am available. My standard appointment slots will be divided into 20-minute blocks from 1:30 to 3 p.m. on Mondays and Wednesdays. Note that these appointment slots will disappear from my calendar once I've been booked. Please book appointments at least 24 hours in advance. If I ever need to cancel by-appointment office hours on a given day (say, for example, if I'm ill), I will update the calendar and email anyone with an appointment.
Drop-in office hours will be held in my office from 10 to 11:30 a.m. on Thursdays. For these, you will not need an appointment, but I will see students in the order they arrive, so there is no guarantee that I will have time for everyone on a given day. If your question is time sensitive, you should make an appointment. If I ever need to cancel office hours on a given drop-in day (say, for example, if I'm ill), I will e-mail the entire class.
Here you will find information on required readings, import university policies, and course-specific policies like attendance and cell phone use.
This course is graded P/F and is based on 2 parts: (1) weekly attendance and (2) homework assignments. You are expected and required to attend and participate in each of the colloquium events and to submit all required materials. If you cannot attend a class meeting, you should contact your professor beforehand, and arrange for an alternate assignment and/or to view the recorded presentation.
Coming to class prepared means that you have the day's reading in hand (printed or digital) and have come to class with a way to take notes (printed or digital). If you are not prepared for class, I reserve the right to grade as if you were absent for that day. Anything due on a given day is due at the start of class. Any digital submission of material is due by the time class starts on the day the hard copy is due unless otherwise noted.
Cell phones should be off and put away. Laptops are okay for notes and such, but you should not be messaging, using Facebook, etc. I’ll check screens regularly give you a verbal warning on your first offense. After that, I reserve the right to ask you to leave class and mark you absent if you are creating a distraction.
Last but certainly not least, engagement and active participation are required for all in-class activities as part of the colloquium.
There are several homework and classwork assignments noted on the weekly calendar. In the case of homework, turning in a completed assignment will generally be sufficient to earn a passing grade, but I reserve the right to give a failing grade that is incomplete with respect to the assignment requirements, overly rushed or sloppy, or work that is not your own (as would be the case if you take work from your classmates or plagiarize from any publicly available material). In general, classwork assignments will consist of written work that is completed during class time. You must attend class to complete these assignments. In the event of an excused absence, I reserve the right to require a make-up assignment for the missed classwork.
If you have a legitimate emergency such as a serious illness, a mental health emergency, or a death in the family, I will grant an appropriate extension with a new due date. If you miss a deadline entirely without getting an extension, you will automatically lose 10 points off the top of your grade for each day it is late, in addition to any points you lose for the quality of the work. Numerically, this means that any assignment turned in more than three days late will receive a failing grade.
No required textbook. Selected readings will be made available on Notebowl, and linked to the course website (expect to spend a little more than normal on printing fees) |
Computers: Students are required to provide their own laptops and to install free and open source software on those laptops. Support will be provided by the instructor in the installation of any useful or required software. If at any time you don’t have access to a laptop please contact the instructor and the Data Analytics Program can provide you with a loan from the laptop cart. In class, please use eduroam to connect to the Internet instead of Denison Guest. Please be respectful with your use of laptops and technology in class. I request that you only use them for class related purposes, as I and others may find them distracting (For example, no email or social media should be open in your browser tabs!). Cell phones should be kept silent and put away. |
Github, Programming Languages, Software: We will be using git and Github for version control and collaboration, as well as Github classroom as a means for you to access assignment templates and turn in your work. We will also have a workshop on using Github Pages to host a website. We will also have a mini hack-a-thon later in the semester, for which you can use Python or R. |
Proposed and developed by Denison students, passed unanimously by DCGA and Denison’s faculty, the Code of Academic Integrity requires that instructors notify the Associate Provost of cases of academic dishonesty. Cases are typically heard by the Academic Integrity Board, which determines whether a violation has occurred, and, if so, its severity and the sanctions. In some circumstances the case may be handled through an Administrative Resolution Procedure. Further, the code makes students responsible for promoting a culture of integrity on campus and acting in instances in which integrity is violated.
Academic honesty, the cornerstone of teaching and learning, lays the foundation for lifelong integrity. Academic dishonesty is intellectual theft. It includes, but is not limited to, providing or receiving assistance in a manner not authorized by the instructor in the creation of work to be submitted for evaluation. This standard applies to all work ranging from daily homework assignments to major exams. Students must clearly cite any sources consulted--not merely for quoted phrases, but also for ideas and information that are not common knowledge. Neither ignorance nor carelessness is an acceptable defense incases of plagiarism. It is the student’s responsibility to follow the appropriate format for citations. Students should ask their instructors for assistance in determining what sorts of materials and assistance are appropriate for assignments and for guidance in citing such materials clearly.
Denison's mission statement articulates an explicit commitment to liberal arts education. It emphasizes active learning, which defines students as active participants in the leaning process, not passive recipients. Denison seeks to foster self-determination and to demonstrate the transformative power of education. A crucial aspect of this approach is what Denison's mission statement refers to as "a concern for the whole person," which is why the university provides a "living-learning environment" based on individual needs and an overriding concern for community. This community is based on "a firm belief in human dignity and compassion unlimited by cultural, racial, sexual, religious or economic barriers, and directed toward an engagement with the central issues of our time."
In this class, we will discuss inequality directly. In many cases, you will asked to apply quantitative reasoning skills to these subject, which can be difficult because there is always the potential for the available data to complicate or contradict something you may feel very passionate about. In these cases, you should aspire to adopt an attitude of critical skepticism, i.e. wary of claims that are not supported by evidence but potentially willing to be persuaded by evidence if you find it compelling, and willing to give that evidence a fair hearing.
How we treat one another will be a cornerstone of these conversations. Denison's "Guiding Principles" speak of "a community in which individuals respect one another and their environment." Further, "each member of the community possesses a full range of rights and responsibilities. Foremost among these is a commitment to treat each other and the environment with mutual respect, tolerance, and civility." It's easy to treat someone this way when you like them and agree with their ideas, but the real challenge is treating those who differ from us with the same compassion and respect. However, I consider disruptive, deceitful, or hateful behavior to be breaches of these responsibilities. Bullying, trolling, hate speech, and harassment of any kind will not be tolerated.
Mock application materials based on a real interneship or job advertisement of your choice.
A professional website where you can later build an online portfolio, if you like.
A short writing assignment asking you to think critically about the subject of "Everyday Code" and how it can apply to you.
A short writing assignment asking you to think critically about our Portfolio workshop and what you can learn from it.
A draw.io diagram and a short writing assignment asking you to construct a plan for your DA major and think about how you can build on your interests.
Note: More detailed assignment descriptions will be added to Notebowl as we approach each deadline.
Week 1: Data Analytics at Denison (and everywhere)
Homework: Submit resume and cover letter assignment to Notebowl
Week 2: Resumes and cover letters
Homework: None
Week 3: Majoring in DA
Homework: Read "How to Get a Data Science Internship — Technical Expertise vs Personality"
Week 4: Internships
Homework: None
Week 5: Blend360 Recruiting Event
Homework: None
Week 6: Making a Github Pages Website
Homework: Publish your Github Pages site and share the link on Notebowl
Week 7: Looking Back
Homework: None
Week 8: Everyday Code
Homework: Complete the "Everyday Code" Reflection by March 22, 2022
Week 9: SPRING BREAK - NO CLASS
Week 10: Portfolios
Homework: Turn in Your Portfolio Reflection
Week 11: DA Domains
Homework: None
Week 12: Entrepreneurship
Homework: Read "6 Questions I was Asked at Data Scientist Interviews"
Week 13: Technical interviews and/or coding task
Homework: Read Calling BullSh*t excerpt (Notebowl)
Week 14: Spotting and Calling BS
Homework: Read Grit excerpt (Notebowl)
Week 15: Developing Your Passion in Data Analytics
Homework: Complete your DA Goals Hierarchy assignment