Data Science 6400

School of Data Science
University of Virginia

Course Overview
Course Calendar
Course Policies

View the Project on GitHub thomasgstewart/machine-learning-1-fall-2023

Course Policies



There are 9 project deliverables. Each deliverable will be graded on a pass/fail basis. Students will have opportunities to resubmit deliverables within 2 weeks of initial feedback.

Final project

Students will plan, execute, and present a data analysis on a question of your their own choosing, preferably a question from their own research. Students will answer the research question using regression. Students are encouraged to

  1. Choose a research question for which the development of a predictive model makes sense.
  2. Select a dataset that includes predictors of various types (both continuous and categorical).
  3. Incorporate methods discussed in the course. (For example, transformations, splines, missing data methods, bootstrap, etc.)
  4. Address model selection and fit.
  5. Use graphical displays in both the report and the presentation.

During the final exam period, students will present their analysis to the class, giving particular emphasis to the strengths and weaknesses of the approach.

Students will be graded on both the clarity with which they explain course concepts and their approach in the data analysis.

Additional details will be provided in early November.

Final grades

Final grades will be assigned as follows.

Grade Requirement
A A on the final project & successful completion of all 9 deliverables
B B on the final project & successful completion of all 9 deliverables
C C on the final project & successful completion of all 9 deliverables
F Otherwise


The instructor may alter the course content and grading policies during the semester.

Collaborative learning

Students are encouraged to study together. The instructions for each deliverable will indicate if and how students may work together on the deliverable. Students should not collaborate on the final project. Students that violate the collaborative-work policy on an deliverable will fail the deliverable in question and forfeit the opportunity to retake or resubmit. Students that violate the collaborative-work policy on the final exam will fail the final exam. Students may be refered to UVA Honor Committee.


UVA is committed to creating a learning environment that meets the needs of its diverse student body. If you anticipate or experience any barriers to learning in this course, please feel welcome to discuss your concerns with me. If you have a disability, or think you may have a disability, you may also want to meet with the Student Disability Access Center (SDAC), to request an official accommodation. You can find more information about SDAC, including how to apply online, through their website at If you have already been approved for accommodations through SDAC, please make sure to send me your accommodation letter and meet with me so we can develop an implementation plan together.