Assessment Methods

This course utilizes several methods for assessment:

Homework Assignments (40% Total)

  • Individual Assignments: HW1-HW4, 10% each.

Final Team Project (30% Total)

  • Milestone 1: Project Proposal (2%)
  • Milestone 2: Project Progress/Presentation (5%)
  • Milestone 3: Project Final Deliverable (23%)

Technical Interview (20%)

  • Individual, synchronous (20-30 minutes, 1:1 with Professor/TAs)

In-Class Activities (8%)

  • In-person section: Requires attendance (best 8 out of 9)
  • Online section: Asynchronous activities or quizzes (best 8 out of 9)

Course Reflections (2% Total)

  • 2 Individual Reflections, each 1%.

Note: Most assignments and deliverables are due on Fridays at 5 PM (PT) / 8 PM (ET).

Assessment Description

  • Homework Assignments (40%): These assignments consist of multi-part questions based on key concepts and techniques introduced during class. All assignments are to be completed individually and may include programming tasks that reinforce generative AI concepts such as fine-tuning models or implementing foundational AI techniques.

  • Course Reflections (2%): There will be two course reflection surveys and essays, each combo worth 1%.

  • Technical Interview (20%): You will be required to participate in a 20-30 minute, 1:1 synchronous interview with the Professor/TAs. This interview will assess your overall understanding of the course concepts and your final project.

  • In-Class Activities (8%): Most lectures will feature interactive activities and/or polls that support the material being presented. You must be present in class to complete the activity or take the poll. Only your top 8 out of 9 scores count.

  • Final Team Project (30%):

  • Milestone 1 (2%): Project Proposal – Submit a detailed plan outlining the project objectives, methodology, and expected outcomes.
  • Milestone 2 (5%): Project Presentation – Present your project progress and findings.
  • Milestone 3 (23%): Project Final Deliverable – Submit a comprehensive report detailing your project results, methodology, and conclusions.

Late/Makeup Policy

All tasks and assignments have specific due dates and times. Your work is late if it is not turned in by the deadline.

Built-in Flexibility: The course already includes substantial flexibility: - Weekly activities: Only your top 8 out of 9 scores count - Homework assignments: Given ~2 weeks to complete, providing ample time for planning

Late Penalties: - In-class activities and final project: Not accepted late (no exceptions) - Homework assignments: Will be accepted up to 48 hours late with 5% penalty every 6 hours (rounded up). For example, an assignment due for 90 points, submitted 7 hours late, would receive 81 points (90 × 0.90). Submissions beyond 48 hours receive zero.

No Make-ups or Extensions: Extensions create cascading delays, disadvantage students who submit on time, and complicate solution releases and grading. Given the built-in flexibility above, make-up assignments and extensions will not be granted. The dropped activities and extended homework deadlines are designed to accommodate typical challenges (short-term illness, job interviews, other coursework, travel, technical difficulties, overlapping deadlines, family visits).

Extraordinary Circumstances Only: True emergencies (hospitalization, family crisis) will be handled individually and require documentation. You must notify the instructor as soon as reasonably possible—it is your responsibility to ensure your situation is communicated and acknowledged.

What Doesn’t Qualify: Poor time management, overlapping deadlines, job interviews, travel, or minor illness are already accommodated by the course’s flexible grading structure. Do not request extensions for these situations.