Policies
Table of contents
Presentation of Course Material
Overview
This course will be taught in a seminar style, with lectures, 7 homeworks, 5 labs, 2 midterms, and a final project. All submissions will go through Gradescope. There is also an Ed page for students to discuss homeworks and projects.
Each week, there are 3 hours of lecture, 1 hour of discussion, and 3 hours of organized lab sections. All of these and office hours will be hosted in-person. You are expected to work on projects during your own time. Lecture and discussion sections will be recorded and posted.
Lecture
Lectures will be on Mondays and Wednesdays 2-3pm in Hearst Field Annex A1. Recordings of all lectures will be posted on bCourses and you can access them by going to “Modules” in bCourses, and then clicking on the page associated with the specific lecture that you want to view. They will also be accessible via the “Media Gallery” in bCourses.
Discussions
There will be one offered discussion section on Friday from 2:00pm to 3:00pm in Hearst Field Annex A1. It will have a review of important topics and go over practice problems related to the material to supplement lecture content. Attendance is encouraged but optional for discussion. The TA giving the discussion may vary from week to week according to the subject matter. The discussions each week will be recorded and posted on bCourses.
Homeworks
Homeworks will be collected and graded using the Gradescope system. Create an account on gradescope.com with your Berkeley email account and SID, and you can add this class using this code: G673ER.
There will be seven homeworks, done on Gradescope and due on Monday nights. We will post the homeworks at least one week before they are due, and we aim to provide graded HW within two weeks of the deadline. Some homework problems will be graded by completion (to encourage self-study and development of understanding) and some will be graded by correctness. All of Homework 4 will be based on completion.
Homeworks must be completed in LaTeX! This is so that you can practice writing professionally typeset documents in your future careers. It is the crown-jewel of the STEM world. We recommend that you use Overleaf or edit it locally through VS Code.
Collaboration on homework sets is encouraged, but all students must write up their own solution set. Additionally, every student is accountable for the solutions they submit and may be asked to discuss them with a TA or instructor. Please list all collaborators at the top of each submitted homework set.
| Homework | Due Date |
| Homework 0: Electronics and Circuits Review | 1/26 |
| Homework 1: Statistics and Hypothesis Testing | 2/9 |
| Homework 2: Non-Parametric Statistics and Coding | 2/23 |
| Homework 3: Frequency Analysis and Bode Plots | 3/9 |
| Homework 4: Designing and Anlyzing Sensors | 4/3 |
| Homework 5: Image Processing | 4/13 |
Lab Sections
Lab sections are not offered asynchronously. At the beginning of lab section, the TA/tutor will go over any announcements and a general overview of the lab. There will be 5 labs in this course.
- Labs 0 and 1 are introductory and are designed to get you familiar with the equipment in the lab and comfortable with thinking about measurement errors. These two labs will have light lab reports associated with them and will cover AC measurements, signal processing, and filters.
- Lab 2 will be more in-depth and will focus on calibration of instruments and resulting calibration curves. You will also have a larger lab report to hand in.
- Lab 3 will be more in-depth and will integrate your learning about dynamic system responses, displacement and acceleration sensor technology, and data interpretation. You will have a large lab report to discuss your results, record a first cut of that presentation, receive feedback from course staff, and then give a live version of your revised presentation, with Q&A.
- Lab 4 will be a Design Project based lab made to assist you with initial data collection and processing. It will cover statistical methods that may be helpful for analyzing your project data, and help you complete Milestone C
Please remember to bring your personal safety glasses to every lab session and microkit. Labs must be completed in LaTeX! We will provide a template. This is so that you can practice writing professionally typeset documents in your future careers. It is the crown-jewel of the STEM world. We recommend that you use Overleaf o-r edit it locally through VS Code.
Midterms
There will be 2 midterms covering course material. Students are allowed one, front and back, 8.5x11” cheat sheet per exam
Midterm I will be held during lab sessions the week of March 30th - April 3rd. This exam will be hands on with your lab groups.
Midterm II will be on April 22nd, 7-9 PM in Hearst Field Annex A1
Final Project
The ME 103 course culminates in an open-ended, team-based measurement project in which you pose and answer a question about the world using mechanical measurements. Your research question should emerge from genuine curiosity and may draw on areas such as sports performance and safety, extracurricular engineering projects, environmental comfort and safety, transportation systems, music and acoustics, or energy efficiency. To address your question, you will apply core ME 103 concepts including experimental design, uncertainty analysis, hypothesis testing, sensor selection, data acquisition, and data fitting. The project concludes with an 8–10 page research paper, written and formatted to professional standards as if submitted to a journal such as Measurement Science and Technology. Through an iterative proposal and consultation process, course staff will help you refine a feasible and compelling experiment, with data collected either in real-world settings or in the Hesse Hall laboratories.
You will work in teams of four to six and have access to a wide range of instrumentation, including the Berkeley ME Microkit (ESP32-based data acquisition with multiple sensors), additional sensors and actuators in Hesse Hall, core lab facilities (e.g., wind tunnel, Instron, model racetrack, engine testbed), and sensors embedded in modern smartphones. The project unfolds through five milestones: a one-page proposal, a detailed experimental plan, a figure plan with preliminary data, a full paper draft, and a final presentation, culminating in a polished journal-style paper. Example projects include studies of indoor air quality, material performance for race vehicles, UAV rotor efficiency, drag-reducing surfaces, and musical acoustics. Overall, the project is designed to foster experimental creativity while reinforcing the rigorous measurement principles at the heart of ME 103.
| Milestone | Due Date @11:59PM |
| A. One-page Project Proposal | 2/20 |
| B. Detailed Exprimental Plan | 3/06 |
| C. Figure Plan & Preliminary Data | 3/20 |
| D. First Draft of Paper | 4/6 |
| E. Final Presentation | RRR Week |
| F. Final Version of Paper | 5/6 |
Due to the types of deliverables involved, extension days may not be used on project deliverables, and late work will not be accepted.
As in most classes, all students must complete a final project. Failure to complete a final project will result in a failing grade.
Office Hours
The instructors will hold weekly office hours to discuss lecture content, homework assignments, projects, and other course material. We will try our best to schedule them so that each student has the opportunity to attend at least one office hour each week. When discussing a current homework assignment, instructors will not provide solutions. Rather, instructors will be happy to help clarify fundamentals and to guide students’ reasoning in related problems.
Content questions can go to any TA or the professor. Questions regarding homeworks should be directed to any TA/Tutor. Questions regarding projects can be directed to any TA. Questions regarding course logistics should be directed to Larry, Dalil, or Alyn. All questions can be directed to Ed for the fastest response. When emailing us, please prefix the subject line with [ME 103], otherwise your email may be missed. Allow up to 24 hours for our response before following up.
Grading
Grade Breakdown
| Homeworks | 15% |
| Midterms | 35% |
| Labs | 20% |
| Measurement project | 30% |
Homeworks
15%, equally weighted between the 6 homeworks (6 because lowest is dropped)
Midterms
35%, equally weighted between the 2 midterms
- Midterm 1 Lab Based: 17.5%
- Midterm 2 Lecture/Homework Based: 17.5%
Labs
20%, equally weighted between 5 labs
Measurement project
30%, of which:
- Milestone A: 1% of overall course grade
- Milestone B: 1%
- Milestone C: 1%
- Milestone D: 2%
- Milestone E: 12.5%
- Milestone F: 12.5%
There is no final exam in this class.
One feedback survey will be posted after the midterm, worth an extra 0.5% of your grade. An additional 0.5% will be granted for completing the end-of-semester university feedback.
Regrade Requests
If you feel that your work has been graded unfairly, you may request a regrade by submitting a request on Gradescope with a written statement explaining the mistake. Be aware that points may be deducted as well as added if a regrade is requested. The deadline for requests will be announced when grades are released.
Effort, Participation, and Altruism (EPA) Points
We want to reward you for engaging respectfully with the course! You are eligible to earn up to 2% extra credit via Effort, Participation, Altruism (EPA) points. These points can be earned in a variety of ways:
- Attending lecture and discussion
- Asking questions in class
- Helping others in lab section
- Answering questions on Ed
- Coming to Office Hours
Please remember to treat your peers (and hopefully your instructors!) with kindness and respect.
A Note on Late Work
We ask that you plan to complete all assignments by their posted deadlines. Due to the tightly coordinated nature of this course, no extensions will be granted for labs, homeworks, or project milestones under any circumstances. This policy applies uniformly to ensure fairness, timely feedback, and smooth course logistics.
To provide some built-in flexibility, your lowest homework score will be dropped automatically at the end of the semester. We encourage you to use this as a buffer for an unusually busy week or an unexpected conflict, rather than relying on deadline adjustments
Because labs and project milestones build directly toward later work and feedback, it is especially important to submit on time. We encourage you not to make the perfect the enemy of the good—submit what you have by the deadline so that you can continue to make steady progress in the course. We will be lenient with grading for lab reports.
If you are struggling with the material or feeling overwhelmed, please communicate early with Larry (larryhui7@berkeley.edu), either in person or by email. While deadlines cannot be extended, we are happy to help you find strategies and resources to stay on track and succeed in the course.
Miscellaneous Information
Disability Accommodations & Emergencies
If you need disability-related accommodations in this class, if you have emergency medical information you wish to share with us, or if you need special arrangements in case the building must be evacuated, please inform us immediately. Please see the professors or admin TA privately after class, or send us an email.
DSP Letters should be sent as soon as possible to ensure that we can make accommodations before they are needed.
Student Technology Equity Program
The campus operates a free program to provide students with laptops, WiFi hotspots, and other technology to make studying more convenient. I encourage you to take advantage of this scheme if you have any technology needs: https://technology.berkeley.edu/STEP
Collaboration Policy
Students are allowed—and in fact, encouraged—to collaborate on how to approach problems. This can include talking through approaches and whiteboarding together. However, each student is responsible for writing their own responses, both for typical written questions and coding assignments. Students should never be in possession of another student’s code.
Online material is also open to use. However, it must not be copied directly, and any references should be credited in your work. Using previous years’ solutions from ME103 or any other class constitutes plagiarism and will be punished accordingly.
When debugging, students are encouraged to come to office hours for assistance. If debugging with peers, we encourage you to do this in person with others in small groups. However, we understand that this is not always possible, so screen sharing code for debugging assistance is permissible. When debugging, please do so in pairs or very small groups, and always do so in controlled settings to minimize sharing answers.
Students should never screenshare their code or answers directly on public platforms like non-private posts on Ed, the class Discord, or Zoom rooms. Please note that screen sharing on Discord can be viewed even without directly joining the call, so there can be no record of who is viewing your stream at any time. ALWAYS list collaborators.
tl;dr: Work together on approach, but write your own answers. If you need direct help debugging, ask a TA for help, or do so in controlled environments where the only people who see your code are your approach collaborators. ALWAYS list collaborators and cite sources on your submissions.
AI Guidelines
As we navigate the new landscape with AI and LLMs, we want to be transparent about and provide guidelines for acceptable and unacceptable uses of AI in the course. We provide these guidelines with the note that we warn against an overreliance on these kinds of tools that might preclude you from developing a strong grasp on/intuition about the course material. We strongly remind you that these tools are meant to assist your learning process, not to replace your learning.
Guidelines: The grading staff does not allow the use of AI for writing any part of your Lab or Project reports or Homework. We do not permit using AI to directly answer questions for any assignment. This means that copy-pasting full questions into AI for an answer is explicitly disallowed. If you use concepts not related to class material to answer your questions, which we suspect were synthesized by AI, we reserve the right to call you in to orally explain your answer. Furthermore, using AI to write your code or LaTeX is explicitly disallowed (not a bluff—several students have failed the course in the past because of this). Remember, you must submit your LaTeX .zip files with every assignment and include all code in the appendices (it is quite easy to tell when code is the output of an LLM).
However, you may find it beneficial to “bounce ideas” or ask auxiliary questions to help frame a problem. For example, you might ask ChatGPT when you use active components for a filter or what benefits there are to spectral analysis, as you would with a traditional search engine. Still, you must not copy-paste an answer from AI into your assignment. It is easy to tell when this is done, and doing so constitutes academic dishonesty.
We encourage you to utilize the resources we provide to you (e.g., lectures, office hours, discussion sections) to further clarify any questions you have or to verify the information you receive from an AI agent. We reserve the right to give no credit for dishonest use of AI.
Leaning too heavily on these kinds of tools can detract from your learning. A weak grasp of the material will be reflected in project, lab, homework, and midterm scores, which are the primary source of spread in grades for the course.
If you received a score of 0 on an ENTIRE assignment or have questions or concerns about AI usage, grading, or academic integrity, please reach out directly to dalilashong@berkeley.edu.
In the end, it’s just not worth it—just come to office hours instead, we’re here to help!
Advice
The following tips are offered based on our experience.
Do the homeworks! The homeworks are explicitly designed to help you to learn the material as you go along. There is usually a strong correlation between homework scores and final grades in the class.
Keep up with lectures! Discussion sections, labs, and homeworks all touch on portions of what we discuss in lecture. Students do much better if they stay on track with the course. That will also help you keep the pace with your homework and study group.
Take part in discussion sections! Discussion sections are not auxiliary lectures. They are an opportunity for interactive learning. The success of a discussion section depends largely on the willingness of students to participate actively in it. As with office hours, the better prepared you are for the discussion, the more you are likely to benefit from it.
Come to office hours! We love to talk to you and do a deep dive to help you understand the material better.
Form study groups! You are encouraged to form small groups (two to four people) to work together on homeworks and on understanding the class material on a regular basis. In addition to being fun, this can save you a lot of time by generating ideas quickly and preventing you from getting hung up on some point or other. Of course, it is your responsibility to ensure that you contribute actively to the group; passive listening will likely not help you much. Also, recall the caveat above, that you must write up your solutions on your own. We strongly advise you to spend some time on your own thinking about each problem before you meet with your study partners; this way, you will be in a position to compare ideas with your partners, and it will get you in practice for the exams. Make sure you work through all problems yourself, and that your final write-up is your own. Some groups try to split up the problems (“you do Problem 1, I’ll do Problem 2, then we’ll swap notes”); not only is this a punishable violation of the university’s collaboration policies, it also ensures you will learn a lot less from this course.
A Final Note
We understand that there is a lot happening, and every semester will have its unique challenges. We are here to support you throughout the semester, both as students and as people. Life happens, and we want to make sure you are always receiving a quality education. Please communicate with us if you are experiencing extenuating circumstances and need extra support. We’re here for you.