Final Project

At the end of the semester, the class will host a convention-style demo day, with an interactive booth experience. Each team will present their application and prepare a report.

Back to the Data Engineering Course - 2024 Spring (AI5308/AI4005)

Timeline for 2024 Spring

Here is the tentative timeline for your project.

Click here to see the general instruction of the project.


  • Team 1: 류현석, 조강인, 김병창, 박종연, 강제이
  • Team 2: Ananda, 윤수인, 원상혁, 이한결, 이민욱
  • Team 3: Tepy, Malika, Zubia, Mary, Rakishev
  • Team 4: 황인선, 박시원, 조민준, 이상유, 김영목
  • Team 5: 김민성, 박순철, 주진식, 이지오
  • Team 6: 임동규, 이경규, 임민하, 오민우
  • Team 7: 우성윤, 조재범, 양승유, 신서현

Project proposal

Project proposal (Gradescope) - Ensure that each team submits one by March 31, 23:59.

  • Deliverables: Submit up to 3 page PDF-formatted project proposal outlining your preliminary project idea.
    • Team members: Each member’s student ID and name, with your team number (1-7)
    • A list of up to two potential ideas, each of which should include:
      • Problem definition
      • The proposed solution, i.e., the application you want to build
      • Address all points mentioned in the section Aspects to consider below
      • Specify what that MVP should be
      • Clarify whether this project is being used in other classes or is related to your other projects. See FAQs for more detail.
    • If you have 2 ideas, specify which idea you prefer as well as all the contexts you might have that the course staff can use to help you decide which idea to go with. This initial concept does not need to be your final project idea.
    • Refer to resource collections for ideate your project
  • Grading criteria (5 points)
    • The project proposal is mainly intended to make sure you decide on a project topic and get feedback from the course staff. As long as your proposal touches on all the points above and your ideas seem to have been thought out with a reasonable plan, you should receive 100% of the grade.
    • The reason that we ask for up to 2 potential ideas is to encourage you to think more deeply about what you build and think outside the box. Sometimes the first idea is the best idea, more often than not, however, it’s not.
    • (1 points) Application overview (Motivation, description)
    • (3 points) Address all sections mentioned in aspect to consider
    • (1 points) Description of the Minimum-Viable-Product (MVP) you want to build

Demo Video

Submit your demo video (Gradescope) by Apr 28, 23:59

  • Deliverables: Up to 7 minute long video containing 3-page slide pitch + Demo of an MVP
    • In the April 30 class, we will watch your video and ask questions of each other, instead of giving a live presentation.
    • Prepare your video (content and pitch) in English.
  • 3-page slides pitch 🗣️ [x minutes]: We just want 3 slides:
    • Slide 1 [Pitch]: What’s the problem you’re addressing and why? What are the key objectives?
    • Slide 2 [System & Challenges]: A layout of the system you’re developing (consider a system diagram). Guide us through your system and tell us what you’ve accomplished.
    • Slide 3 [Future Work]: What additional work is needed? We want to understand the key challenges you anticipate.
  • A demo of an MVP [y minutes; x+y < 7]: We want to see that you’ve built something that aligns with what you promised. The focus here is on:
    • demonstrating that you’ve made an initial effort on all components of the system you’re building.
    • convincing us that you have a strategy to evolve the application from MVP to final-demo-ready.
    • Having an MVP at this stage will enable us to provide you with meaningful feedback.
  • Grading criteria (9 points): The video will be graded using the following rubric:
    • (1 points) Compelling pitch. The problem the team is trying to solve, the users, and the value proposition are clearly identified.
    • (1 points) Clear system layout and explanation. It is easy to understand how the different components of the system interact to create the system the team has designed.
    • (1 points) Strong understanding of future work and key challenges.
    • (2 points) The team has made good decisions — and justified them during their presentation — about what to prioritize in developing their MVP. The team’s decisions reflect a careful consideration of their anticipated challenges associated with the design of their system.
    • (2 points) The MVP demo showcases an end-to-end system, rather than independent, disjointed system components. Though the MVP is obviously a minimum viable product, it should be clear that the demo is the result of careful consideration and substantial effort.
    • (2 points) If the course staff is particularly impressed by your progress toward the MVP at this stage, we’ll award your team up to a 2 point bonus for staying on top of things. 🚀
  • Reference

Submitted Videos

Rehearse and Commentary

  • When: June 4, 2023, 13:00-14:15
  • Where: AI Graduate School, TED-Hall (S7 building, 2F)
  • Things to prepare: Setup your demos and receive critique on your final report draft 🔍
  • Instructions for both students and TAs:
    • Students:
      • Plan the arrangement of your demo alongside TAs, consider using the TV screen and iMacs.
      • Discuss how to make your booth unique during the demo day.
      • Consult with the instructor and seek advice on your final report, bring your draft (6 minutes each, starting with Team 1)
    • TAs:
      • Aid in the demo setup.
      • Determine what needs to be prepared for the demonstration day, and sequence them accordingly (Purchase).
      • Distribute emails and advocate for the demo day amongst members of the AI Graduate School and EECS undergraduates.

Demo Day

Get ready for our Demo Day - a convention style, interactive booth experience!💥 Showcase your project, learn from your peers, and bring your ideas to life! 🚀

  • Logistics
    • Date and Time: June 11, from 13:00 to 16:00
    • Venue: AI Graduate School, TED-Hall (S7 building, 2F)
      • Equipped with three 65-inch TVs, and dozens of 27-inch iMacs available at 1F.
  • What you should prepare
    • Your demo product
    • (Optional) Videos you would like to stream using TV or laptop. e.g., teaser video.
    • Short pitch up to 3 minute: You will deliver a short pitch at the beginning of the day. Slides are not required.
  • What you will do
    • Introduce your demo at the booth (at least one team member should stay at your booth at any time).
    • Visit other team’s booths and experience their demos.
    • Attract attendees and promote your demo.
    • Provide suggestions and note down feedback from others.
  • Ingredients of a live demo
    • Introduce yourself: Spend a few seconds telling customers who you are.
    • Motivate your problem: Describe the goal of your application, describe why your team was interested in this problem. Set context and expectations.
    • Describe the technology: Impress us with what you’ve accomplished. Talk about the technical depth of your system, show us that you thought through the design
  • Live demo: The live demo is done in real-time, but every single aspect of the demo is scripted ahead of time.
    • You should know exactly how you’ll be walking through your application.
    • Think about what you want to highlight. You should script what you’ll be saying and where you’ll be drawing the attention of viewers.
    • Plan your pauses, and think about places to ask the audiences for input so that they feel involved.
    • Be aware of balancing two needs: 1) showing off your applications in the best possible light, 2) Making the audience feel involved so that demo doesn’t feel scripted.


Time         Agenda
13:00 - 13:10 Demo setup
13:10 - 13:40 Short pitch by each team (up to 3 min)
13:40 - 15:30 Booth management and exploration of other team’s products
15:30 - 16:00 Event closing and wrap-up

Grading criteria:

Your demo will take 15 points of your grade. Below is the tentative grading criteria to consider.

  • (1 points) Compelling pitch: The problem the team is trying to solve, the users, and the value proposition are clearly identified.
  • (3 points) Practicality: Is the application you built a compelling, practical use case for applying ML?
  • (3 points) ML tech: The depth and overall sophistication of the technical backbone of your system. What models you used and how appropriate they are for the overarching goal of your application.
  • (2 points) User experience: How easy is it to use your application? Does the overall design fit the problem?
  • (2 points) Novelty: How interesting, exciting and novel is the problem you set out to solve?
  • (2 points) Students’ choice awards: top 3 projects voted by students
  • (2 points) Judges’ choice awards: top 3 projects voted by judges

Final Report

The last part of your grade is based on a report that summarizes your work. The report will be written in the style of a blog post (good examples: here, here, here, here).

Submit your final report and peer evaluation result by Jun 16, 23:59 (Google Form)

  • Deliverables
    • Your report should summarize your project work and learning. It’d be at most 2500 words long.
    • Please see Grading criteria below for the required components of the writeup.
    • You can write your report on your own project page (e.g., Github or Notion) and provide us the link of it. It will be published on the course website after the conclusion of the course.
    • You will submit the url for your final project demo.
    • If you prefer not to make your project page public, you have the option to submit your final report as a zip file that contains two components:
      • Code, data, and associated materials used for the project. You can submit this component directly or include a link to a GitHub repo where it’s hosted. Please contact us if this information is proprietary.
      • An HTML folder:
        • index.html: an HTML file containing your report
        • All associated images and support files referenced by the HTML file. You should contain all supporting documents such that the HTML file, when opened, will properly render on any machine with a web browser and an Internet connection.


Here are the aspects you should include in your final report (with suggested lengths). See the sample reports that follow this structure. You can decide the length of each part, but make sure that final report length is no longer than 2,500 words. The report will take 12 points of your grade.

  • Team information
    • Mention each members’ name and put the link of their website.
  • Problem definition (Suggested: 250 words)
    • Explain the problem the team is solving, discusses related work, and proposes and justifies their solution.
  • System design (500 words)
    • Details the key components of the system, including, but not limited to, data pipelines, modeling, deployment, and UX.
    • If applicable, a diagram is included to illustrate the interplay between system components. Excalidraw is pretty awesome for sketches.
    • This section explains and justifies central design decisions, including that of which technologies the team chose to use to support their system.
  • Machine learning component (300 words)
    • For those you requires ML, explain the model that powers the application, the data it’s trained on, and the iterative development of that model.
  • System evaluation (500 words)
    • Describe your efforts to validate and evaluate their system performance as well as its limitations.
    • The results are included and presented in a clear and informative manner.
  • Application demonstration (300 words)
    • Includes some visuals (screenshot, embedded video link) showcasing the main feature set of the application.
    • Includes brief justifications of core interface decisions (e.g. why did you feel that a Web Application interface would be superior to an API interface given the context of their problem?).
    • Provide instructions on how to use the application.
  • Reflection (400 words)
    • Provides a comprehensive post-mortem on the project, including - but not limited to - answering the following:
      • What worked? (In terms of technology, design decisions, team dynamics, etc.).
      • What didn’t work? What would you improve next time?
      • If given unlimited time and resources, what would you add to your application?
      • If you have plans to move forward with this application, what are they? (We’re excited to see how you use the tools you’ve learned in this class to pursue topics they’re excited about!)
  • Broader Impacts (250 words)
    • This section discusses intended uses of your application and possible unintended uses, and the associated harms. This section reflects upon the design decisions that the team undertook to mitigate harms associated with unintended use of the system.
  • References

Peer Evaluation

After completing the report, discuss how you distribute the given points within the team. You will be asked to submit a 1 page PDF file on your peer evaluation results.

(Must write student ID, name, with points, and the detailed reason)

  • Team of size five: Share 10 points in total (e.g., 4, 3.5, 3, 2.5, 2 points)
  • Team of size four: Share 8 points in total
  • In average, student will receive 2 points, each student can get no more than 4 points.
  • Should be determined by overall contribution: e.g., Data curation, Methodology, MLOps, Front-end, Backend, Paper writing, Visualization, Presentation, Conceptualization, Formal analysis, Funding acquisition, Project Administration, Legal review support, etc