Grading
The course grade is based on 5 Core Modules. Each module is worth 20 points, for a total of 100 points. Participation and engagement are assessed as part of the score for each module.
| Component | Points |
|---|---|
| Module 1: The AI-Data Analyst | 20 |
| Module 2: Spatial Data & Environmental Justice | 20 |
| Module 3: Working with LLMs & Unstructured Data | 20 |
| Module 4: Scaling & Cloud Computing | 20 |
| Module 5: Capstone Project | 20 |
| Total | 100 |
Participation & Engagement
Participation and engagement is a holistic assessment across all aspects of the course and reflects meeting the expectations of the course. Active engagement is expected both in class and online. This includes engagement with the instructional team, classmates, and teammates. A core tenant of our course is the opportunity for one-on-one and small group discussion with Berkeley faculty, GSIs, and fellow students; the chance to build rapport and get to know each other through dialogue (both in-person and online).
Participation is not based on attendance. Participation will be assessed as part of each module grade, based on: - Fully engaged: Active contributor to team work, class discussions, and online interactions - Partially engaged: Some contributions but inconsistent engagement - Minimally engaged: Rare contributions and limited interaction - Disengaged: Little to no participation or engagement
Attendance Policy
This is a hands-on, team-based course rooted in experiential learning and in-person attendance is required. We operate on a flipped-classroom model in which video lectures and reading and simple practice problems must be consumed and prepared prior to class. Class time focuses on active learning around solving hard and open-ended problems in climate solutions by applying data science tools creatively in small teams with the assistance of instructors and classmates; participating in classroom discussion or debate; or in presenting finished work to the class for feedback.
If you anticipate an absence, you must: 1. Notify the instructor and your team prior to the absence if possible 2. Propose a plan for making up missed work with your team 3. Submit this plan to the instructor
Late Assignment Policy
Late assignments may be docked 20% and will not be accepted more than 48 hours late except in cases of genuine emergencies or in cases where this has been discussed and approved by the faculty instructor in advance. If you need an extension due to extenuating circumstances, contact the instructor as early as possible to discuss options.
Community, Diversity, and Inclusion
Integrating and honoring a diverse set of experiences, knowledges, and histories is essential for a comprehensive understanding of environmental science. Additionally, scientific research and the process of science can contribute to a more equitable and just society when pursued intentionally. Thus, as part of this course, we would like to discuss, practice, and critically evaluate diversity, representation, and equity in environmental science and resource management.
Furthermore, we would like to create a learning environment for all of us that supports a diversity of thoughts, perspectives and experiences and that honors your identities (including race, gender, class, sexuality, religion, and ability), with an understanding that systems of privilege and oppression have influenced all of us and may appear in the classroom. To help accomplish this: - If you have a name and/or set of pronouns that differ from those that appear in your official Cal records, please let the teaching team know. - If something is said in class (by anyone) that makes you feel uncomfortable or targeted, please talk to an instructor or GSI about it. Anonymous feedback is always an option. - As a participant in this class, you should strive to honor the identities and histories of your classmates. Consider how your speech connects or alienates. We recommend that you speak from your own experience, avoid generalizations, and acknowledge both the intent and actual impact of your words.
Academic Integrity
Generative AI Policy
You may use AI programs to generate ideas and/or refine your work or brainstorm. We encourage the use of AI tools as a core part of the workflow in this class! However, you must be transparent about your use of AI. If you include any material generated by an AI, it must be cited and a note included explaining its role. You should also be aware that existing tools make significant mistakes and are often incomplete and inaccurate. You remain responsible for all work you submit.
Academic Community Values
You are a member of an academic community at one of the world’s leading research universities. Universities like Berkeley create knowledge that has a lasting impact in the world of ideas and on the lives of others; such knowledge can come from an undergraduate paper as well as the lab of an internationally known professor. One of the most important values of an academic community is the balance between the free flow of ideas and the respect for the intellectual property of others. Researchers don’t use one another’s research without permission; scholars and students always use proper citations in papers; professors may not circulate or publish student papers without the writer’s permission; and students may not circulate or post materials (handouts, exams, syllabi–any class materials) from their classes without the written permission of the instructor.
Collaboration and Independence
Reviewing lecture and reading materials and studying for exams can be enjoyable and enriching things to do together with one’s fellow students. We recommend this. However, homework assignments should be completed independently and materials turned in as homework should be the result of one’s own independent work. Some assignments, namely the preparation for the debate arguments, are meant to be done together in a group.
Consequences of Academic Dishonesty
The consequences of cheating and academic dishonesty—including a formal discipline file, possible loss of future internship, scholarship, or employment opportunities, and denial of admission to graduate school—are simply not worth it.
Plagiarism
You must be original in composing the writing assignments in this class. To copy text or ideas from another source (including your own previously, or concurrently, submitted course work) without appropriate reference is plagiarism and will result in a failing grade for your assignment and usually further disciplinary action. For additional information on plagiarism, self-plagiarism, and how to avoid it, see: - UC Berkeley Library - Plagiarism Guide - GSI Teaching Guide - Preventing Plagiarism
Additional Resources
Academic Accommodations
The purpose of academic accommodations is to ensure that all students have a fair chance at academic success. If you have Letters of Accommodations from the Disabled Students’ Program or another authorized office, please share them with me as soon as possible, and we will work out the necessary arrangements. While individual circumstances can vary, requests for accommodations often fall into the categories listed on the Academic Calendar and Accommodations website. The campus has well-developed processes in place for students to request accommodations, and you are encouraged to contact the relevant campus offices listed on the Academic Accommodations Hub. These offices, some of which are confidential, can offer support, answer questions about your eligibility and rights, and request accommodations on your behalf, while maintaining your privacy.