Syllabus

This document and others linked within it should be your PRIMARY source for understanding the expectations of this course. Be sure to read it carefully. You must contact the instructor for clarification if you receive information from any other source that is in contradiction to what is provided below.

Below are the links to different sections of the syllabus:

An Opening Thought

This is a very stressful and unusual time for all of us. We recognize that many of you are sheltering in different parts of the world. First and foremost over the next couple of months, make sure you take care of yourselves and your families.
With that in mind, we are very excited to share this course with you. We want you to learn and have a great time in the process. Let this class be an escape from some of the uncertainty in the rest of the world. Welcome to Data Science Principles & Techniques!

COURSE INFORMATION

Prerequisites:

PSTAT 120A, CS 9 or CS 16, and Math 4a. All prerequisites with letter grade C or better. PSTAT 120B can be taken concurrently.

Course Description:

Overview of data science key concepts and the use of tools for data retrieval, analysis, visualization and, reproducible research with Python. Topics include an introduction to testing and uncertainty quantification via simulation, an introduction to regression, principles of measurement, missing data, and concepts in data ethics and privacy. Case studies will illustrate the importance of domain knowledge.

This course is primarily designed for students who are interested in data science and are majoring in Statistical Science (BS, BA), Actuarial Science (BS), Financial Mathematics and Statistics (BS), CCS Computing (BS), or Computer Science (BS). It is also suitable for students aiming for a Minor in Statistics. It serves as a complement to PSTAT 120B and a gateway to more advanced data science material.

Course Topics:

Textbook

A useful python reference text is an online book called Python Data Science Handbook

The computing platform (Jupyter Notebooks) for the course is hosted at https://ds100.lsit.ucsb.edu/. All of your work should be completed here.

Contact us on Piazza!

We will be communicating with you and making announcements through an online question-and-answer platform called Piazza. Our class page is here: https://piazza.com/class/k7l3jegotl95vg

We ask that when you have a question about the class that might be relevant to other students, post it on Piazza instead of emailing us (if you wish, you can post your question anonymously to your classmates). That way, all the staff can be on the same page and everyone can benefit from the response. You can also post private messages to instructors on Piazza, which we prefer to email.

Support

You are not alone in this course; the mentors (staff and the instructors) are here to support you as you learn the material. It’s expected that some aspects of the course will take time to master, and the best way to master challenging material is to ask questions.

We will be using Zoom to hold office hours and lab hours.

ASSESSMENTS AND GRADES

Your mastery of class material will be assessed in the following ways, and final grades will be computed as follows:

It is certainly possible for all students to receive high grades in this course if all of you show mastery of the homework and lab material.

Participation

Lecture attendance is optional but is highly encouraged. You are adults and are responsible for your learning. However, everybody benefits when there is more participation and engagement with the material during lab and lecture.

The participation portion of your grade will also include providing good answers on Piazza and engaging with the various activities that the instructor will provide throughout the quarter.

Assignments

Data science is about analyzing real-world data sets, and so a series of projects involving real data are a required part of the course. You may work with one partner, and we strongly recommend that you find a partner in your lab section.

Weekly homework assignments are a required part of the course. Each student must submit each homework independently, but you are allowed to discuss problems with other students without directly sharing the answers. Make a serious attempt at the assignment yourself, and then discuss your doubts with others. In this way you, and they, will get more out of the discussion. Please write up your answers in your own words and don’t share your completed work. You are never allowed to directly copy and paste somebody else’s code.

Labs

Weekly labs are a required part of the course. To receive credit, we encourage you to work on the lab assignment during th eassigned time until you’re finished or the lab period is over. Labs will be released on Tuesday night. If you cannot attend lab physically, you may complete a lab assignment remotely, but you must complete it by Friday at 5pm to receive credits. Each person must submit each lab independently, but you are encouraged to collaborate with other students during lab time via chat.

Exams

There will be no exams in this course.

Late Policy

Homework will be accepted up to 2 days (48 hours) late; a homework submitted less than 24 hours after the deadline will receive 3/4 credit, a homework submitted between 24 and 48 hours after the deadline will receive 1/2 credit, and a homework submitted 48 hours or more after the deadline will receive no credit.

If there is a properly documented family emergency, extended illness, documented required court appearance, or other situation beyond the students’ control (with appropriate official detailed documentation) the instructor may extend an assignment deadline, entirely at the instructor’s discretion.

Learning Cooperatively

We encourage you to discuss all of the course activities with your friends and classmates as you are working on them, either on Piazza, or through a personally chat or zoom. Although more difficult this quarter, you will definitely learn more in this class if you work with others than if you do not. Ask questions, answer questions, and share ideas liberally on piazza.

Academic Honesty

Cooperation has a limit. You should not share your code or answers directly with other students. Doing so doesn’t help them; it just sets them up for trouble on exams. Feel free to discuss the problems with others beforehand, but not the solutions. Please complete your own work and keep it to yourself. The exception to this rule is that you can share everything related to a project with your project partner and turn in one project between you.

Penalties for cheating are severe — they range from a zero grade for the assignment up to dismissal from the University, for a second offense.

Rather than copying someone else’s work, ask for help. You are not alone in this course! We are here to help you succeed. If you invest the time to learn the material and complete the projects, you won’t need to copy any answers.

Slides and Recordings

All lecture material including slides will be posted on the website after class. Recordings of the lectures will also be posted.

Copyright of Course Materials

My lectures and course materials, including PowerPoint presentations, tests, outlines, and similar materials, are protected by U.S. copyright law and by University policy. I am the exclusive owner of the copyright in those materials I create. You may take notes and make copies of course materials for your own use. You may also share those materials with another student who is enrolled in or auditing this course.

You may not reproduce, distribute or display (post/upload) lecture notes or recordings or course materials in any other way — whether or not a fee is charged — without my express prior written consent. You also may not allow others to do so.

If you do so, you may be subject to student conduct proceedings under the UC Santa Barbara Student Code of Conduct.

Similarly, you own the copyright in your original papers and exam essays. If I am interested in posting your answers or papers on the course web site, I will ask for your written permission.

Disclaimer

The rest of this page details the policies that will be enforced in the Spring 2020 offering of this course. These policies are subject to change throughout the remainder of the course, at the judgement of the course staff (with a potential announcement on Piazza).

Last major revision: March, 2020

Updated: