Course Syllabus

MIDAS-acronym.png

Winter 2021 EECS 498-009/598-014

Data Science Projects: Reducing Emissions through Applied Data Science

Course Overview

This course will provide opportunities for students to apply advanced data science techniques to real-world problems. This semester, the focus will be to reduce the environmental impact of personal mobility systems through the use of connected and autonomous vehicles (CAVs). Students will work in a team throughout the semester as part of a collaboration between the Michigan Institute for Data Science (MIDAS) and the U.S. Environmental Protection Agency’s National Vehicle and Fuel Emissions Laboratory (NVFEL).

 

Credits

              3 credit hours. This course is an approved Data Science Capstone for undergraduates in the Data Science-Engineering program.

 

Prerequisites

Students must have received credit for either EECS 445 – Introduction to Machine Learning or STATS 415 – Data Mining and Machine Learning. Student should be comfortable in coding in either Python or MATLAB.

 

Graduate Student Requirements

Graduate students who register for EECS 598-014 should expect to take on additional responsibilities related to the class project and be subject to more stringent grading criteria as befitting the rigor of a graduate-level course.

 

Instructors

Jonathan Gryak

H.V. Jagadish

 

Required Textbook

None. Slides and other course materials will be distributed through Canvas.

 

Learning Outcomes

  1. Learn how to leverage fundamental design principles in the application of data science to a real-world dataset.
  2. Understand the issues of applying data science techniques to real-world datasets and how to mitigate them.
  3. Learn to assess and manage project risks, deliverables, and schedules.
  4. Communicate research results with both domain experts and a general audience.

 

Course Schedule (Tentative)

All meetings will be held virtually via Zoom from 2:30-4:00 PM unless otherwise noted.

  • Thursday, January 21 – Course Introduction, Design Principles, and Introduction to the Class Project
  • Thursday, January 28 – Project Discussion and Overview of Relevant Data Science Techniques
  • Wednesday, February 3 – Draft Problem Statement due at 4 PM
  • Thursday, February 4 – Review of Draft Problem Statement
  • Wednesday, February 10 - Final Problem Statement due at 4 PM
  • Wednesday, February 10 and every Wednesday until April 14 - Meeting Agendas due at 4 PM
  • Thursday, February 11 and every Thursday until April 15 – Weekly Progress Meeting - Summaries due by 4 PM Friday
  • Wednesday, February 17 – Preliminary Design Proposal due at 4 PM
  • Wednesday, February 24 – Revised Design Proposal due at 4 PM
  • Wednesday, March 3 – Final Design Proposal due at 4 PM
  • Friday, March 26Midterm report due at 4 PM
  • Friday, April 23Final report, prototype, and presentation slides due at 4 PM
  • Tuesday, April 27Final presentation

 

No Classes:

  • April 1 – No meeting agenda due; just the weekly summary on April 2
  • April 22

 

Grading

10% Participation in Weekly Meetings, 10% Problem Statement, 20% Design Proposal, 10% Midterm Report, 20% Prototype, 20% Final Report, and 10% Final Presentation.

  • Weekly Meetings – Every week all students will participate in a progress meeting with the course instructor and NVFEL staff. The team will be required to set a meeting agenda in advance for discussion. They will produce a weekly summary of the meeting that will include a description of each team member’s activities, meeting minutes, intermediary results, and action items for the following week. Team members will rotate the responsibility of setting the agenda and leading the discussion.
  • Problem Statement – The team will produce a written statement that details the project design requirements and includes an assessment of the feasibility of the project based on data availability and any performed exploratory data analysis.
  • Design Proposal – The proposal will provide a detailed overview of the solution design, its specifications, and the testing and validation methods necessary to achieve said specifications. The proposal should also identify the technical roles and associated tasks for each team member, the resources required for the project, and include a schedule for the completion of each task.
  • Midterm Report - The team will be required to submit for evaluation a midterm progress report. The progress report must detail a) steps taken to build, test, and validate their design with both positive and negative findings, b) the current state of their prototype, c) a timeline outlining their remaining work, and d) anticipated challenges and how to address them.
  • Prototype – The team is expected to produce a working prototype of their proposed design and all attendant documentation. The prototype will be evaluated with respect to the design proposal and the extent to which it satisfies the original problem statement.
  • Final Report - The team will be required to submit for evaluation a final progress report. The final report must detail a) positive and negative findings, b) the final state and performance metrics of their prototype, c) how the prototype meets the stated NVFEL goals of the project, and d) how the solution fits into the overall NVFEL goal of reducing emissions.
  • Final Presentation – Each team will prepare a presentation for an end of semester event that will be held virtually and attended by NVFEL staff and MIDAS affiliated faculty and students. NVFEL staff will have the opportunity to provide public feedback to the participating teams during this event.

Course Policies

  • Attendance – All students are expected to attend all requisite meetings throughout the semester. In the case of scheduled absences, the instructor must be notified in advanced.
  • Academic Integrity – Students will perform their work in accordance with their schools’ respective academic integrity or honor code policies (e.g., LSA, College of Engineering)
  • Late Assignments – Late assignments will not be accepted without prior written consent by the instructor.

Please note that given the ongoing COVID-19 pandemic it is understood that students may be face additional challenges in completing their coursework. Please notify the instructor of your needs and reasonable accommodations will be made for these policies.

Student Resources