Data Science is an interdisciplinary field that uses several concepts and skills from mathematics. Important concepts from different areas of mathematics are used in Data Science such as linear algebra, calculus, and discrete mathematics. Also problem solving strategies are needed when exploring applications to different fields.
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COMMUNICATION
Messages and announcements will be done using Canvas. When you need to contact your instructor or TA, please use Canvas as email messages will NOT be replied. This is to make communication more efficient, so we can correctly identify your section and other important information.
We will use ed for questions regarding HW, exams, lectures, etc. This tool is great for collaboration and to write math. It is difficult to type math in an email or in Canvas, so use ed for all content related questions!
For anything else, you can reach your instructor but please use this as the LAST method of communication.
Grade
Grades will be assigned using the +/- system.
Homework (25%+5%)
Homework problems (25%) will be assigned during lecture time and will be due every Sunday on Canvas. For each homework you will have the option of two submissions: after your first submission you will get feedback which you can take into account for your second submission. The best grade of the two submissions will be your assingment grade.
We are dropping the lowest 2 homeworks in order to account for any abscences or issues.
Peer-review (5%) qill be required for each homework. This consists on checking the work of your peers and making comments and/or suggestions. This is an opportunity to help your peers and also to learn from their writing style and problem solving strategies.
Journal (10%)
The proof journal consists on a collection of proofs used in class. This includes the proofs done or referenced in lecture, as well as selected proofs from homework. Here you should include:
There will be partial submissions of the journal and a final submission.
Commentary (10%)
This is a class assingment. It will be completed and assignend by all students in the class. The idea is to create a document that supports the class notes provided on Canvas. This document can include:
Roughly, it is expected that each section of the class notes will have a corresponding commentary.
Article (5%)
This a essay-style article and can be over any topic related to data science and mathematics, broadly considered. It will consist on three submissions:
Participation (5%)
This includes participating in Canvas discussions and attending to class. You will have four permited absences to account for any special circumstances.
Midterm (15%)
The midterm will include definitions, statements, and examples given in class, can include homework problems and new problems.
Final (15%)
The midterm will include definitions, statements, and examples given in class, can include homework problems and new problems.
Prerequisite and degree relevance
Provides students with exposure to some of the most relevant mathematical concepts appearing in data science. Applications of linear algebra, optimization, graph theory, and topology are explored. No prior mathematical requirements are expected and this course will introduce the necessary theory needed. The intention is to focus on the theoretical aspects of the mathematical problems arising in data science and to provide exposure to mathematical proofs. No coding experience is required nor will it be used.
Prerequisite(s): No prerrequisites needed.
The UC Santa Cruz community includes students, staff, faculty, and others who have a vested interest in the University. As members of an academic community, integrity, accountability and mutual respect are vital pillars of being part of this community. The Principles of Community further illustrate the values and expectations set forth for being a part of this community.
The use of generative AI in academic environments must be considered with care. A good rule to keep in mind that using generative AI to replace what a human could do might conflict with general rules of academic honesty. For our course, the recommendation is to avoid the usage of generative AI tools for assignments unless explicitely stated.
UC Santa Cruz is committed to creating an academic environment that supports its diverse student body. If you are a student with a disability who requires accommodations to achieve equal access in this course, please submit your Accommodation Authorization Letter from the Disability Resource Center (DRC) to me privately during my office hours or by appointment, preferably within the first two weeks of the quarter. At that time, I would also like us to discuss ways we can ensure your full participation in the course. I encourage all students who may benefit from learning more about DRC services to contact DRC by phone at 831-459-2089 or by email at drc@ucsc.edu.
We understand that our members represent a rich variety of backgrounds and perspectives. UCSC is committed to providing an atmosphere for learning that respects diversity. While working together to build this community we ask all members to:
