11-785 Introduction to Deep Learning

Projects Page

Course Project Guidelines

Graduate versions of IDL include a significant weightage on a course project. In 11-785, you are expected to come up with your own project, or use some of the suggested topics below as a starting point. In 11-685, you are expected to work on a guided project, which is a pre-configured project with a set of organized milestones. TAs will help you with both projects:

11-785: Open Course Project

A primarily student-driven open research project. You may choose your own topic and work in teams of up to 4.

  • Core Deliverables: Midterm Report (20%), Piazza Discussion & Q&A Response (5%), Video Presentation (35%), and Final Report (40%).
  • Structure: Aligned with industry research. Requires periodic self-guided planning, experimentation, writing, and finally peer reviews.
  • Theme: Open-ended topics covering (but not limited to): Vision, NLP, RL, Generative AI, or Computational Biology.

11-685: Guided Course Project

A mentored and structured project pathway. Ideal for students seeking a more hands-on guidance on executing an end-to-end deep learning project.

  • Core Deliverables: Midterm Report (20%), Piazza Discussion & Q&A Response (5%), Video Presentation (35%), and Final Report (40%).
  • Structure: TAs release pre-configured guided projects with milestone benchmarks and technical constraints.
  • Mentorship: Includes closer, dedicated review sessions and tailored support with starter notebooks, datasets and other resources.
IMPORTANT NOTE ON COMPUTE RESOURCES: All project related computations MUST be performed on dedicated resources (AWS/GCP/PSC/personal) for model training, testing and inference. You MUST NOT use any resources from the IDL homework allocation on PSC. Guidelines for requesting compute resources for your project can be found in Recitation 0.13 or Piazza.

Potential Project Ideas

We encourage you to propose a project of your own. But if you need assistance, the project ideas below are intended to provide a starting point. Select the project topic(s) that interests you and your team, and let us know by filling out the form with your preferred project(s).

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Project Interest Form

Submit Project Interest Form

Use this form to show interest in any project(s) for 11-785 or 11-685. This is just for book-keeping, and not a formal selection process

What You Will Need:

  • Student Details: Full names and Andrew IDs of all team members (up to 4 per team).
  • Registered Section: Specify the section that you are registered for, 11-785 (Open) or 11-685 (Guided).
  • Project Interest Statement: A brief paragraph expresing why you are interested in the project, and what you plan to achieve.
  • Core Technical Area: Select your project's theme (e.g. Vision, NLP, Generative AI, RL, or something else).
  • Any Additional Links/Documents (optional): Relevant GitHub repositories, pre-existing research references, or personal portfolios.
  • Compute Requests (optional): Details if you are requesting additional AWS, GCP, or PSC resources.

Legacy Projects

Explore a curated list of student projects from previous semesters of IDL. They serve as a benchmark of the expected scope, quality, and scientific rigor.

Spring 2020

Spring 2020 Project Archive

Browse the archived top 25 projects and their submitted reports.

Fall 2020

Fall 2020 Project Archive

Browse the complete Fall 2020 collection of projects and reports.

Spring 2024

Spring 2024 Project Archive

Browse all Spring 2024 project submissions and reports.

Fall 2024

Fall 2024 Project Archive

Browse all Fall 2024 project submissions and reports.

Spring 2025

Spring 2025 Project Archive

Browse all Spring 2025 project submissions and reports.

Fall 2025

Fall 2025 Project Archive

Browse all Fall 2025 project submissions and reports.

Spring 2026

Spring 2026 Project Archive

Browse all Spring 2026 project submissions and reports.

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