11-785 Introduction to Deep Learning

Projects Page

Project Types & Guidelines

Graduate versions of the Deep Learning course include a substantial hands-on project element. In 11-785, you are welcome to propose your own project; the suggested initiatives below are starting points. Depending on the course code you are registered for, your project requirements and format vary:

11-785: Open Course Project

A fully student-defined open research project. You may choose your own topic and form teams of up to 4 to design, implement, and benchmark an original deep learning system or perform a thorough, state-of-the-art reproduction study.

  • Core Deliverables: Midterm Report (20%), Video Presentation (35%), Piazza Discussion & Q&A Response (5%), and Final Scientific Report (40%).
  • Schedules: Aligned with industry research. Requires weekly self-guided checkpoints and peer reviews.
  • Topics: Highly open-ended, covering Vision, Speech, NLP, RL, Generative AI, or Medical AI.

11-685: Guided Project Version

A highly mentored, structured project pathway. Ideal for students seeking closer guidance on constructing end-to-end deep learning pipelines.

  • Structure: TAs release pre-configured guided projects with milestone benchmarks and technical constraints.
  • Mentorship: Includes closer, dedicated review sessions and tailored computing support.
  • Flexibility: 11-685 students may explicitly choose to pivot and complete an open 11-785 style project instead, if proposed early.
Important compute support: All project teams will receive computational credits (AWS/GCP/PSC) to support model training. Guidelines for requesting compute resources will be published over Piazza.

Potential Project Initiatives

Looking for a course project idea? These initiatives are starting points for deep learning research. You are free to propose a project of your own. Browse the initiatives below if helpful, then use the application form to register your chosen project.

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Project Applications

Submit Project Application

Use this form to register your project, team members, and project category for 11-785 or 11-685. For 11-785, your project can be a student-proposed idea or one of the optional initiatives listed above.

What You Need for Application:

  • Student Details: Full names and Andrew IDs of all team members (up to 4 per team).
  • Registered Course: Specify whether you are registered in 11-785 (Open) or 11-685 (Guided).
  • Core Technical Area: Select your project's main focus (Speech & Audio, Vision, NLP, Generative AI, RL, or Custom).
  • Project Application Statement: A comprehensive paragraph detailing your target model, datasets, and scientific objectives.
  • Supporting Links: Relevant GitHub repositories, pre-existing research references, or personal portfolios.
  • Compute Requests: Details if requesting additional AWS, GCP, or PSC credits.

Legacy Projects

Explore a curated list of exceptionally successful, high-impact student projects from previous semesters of 11-785. These serve as benchmark representations of 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.