DS 4420 — Advanced Machine Learning
4 semester hoursUndergraduateLectureNUpath ADNUpath CENUpath WIusually offered: fall, springtypical days: WBostonTraditional
Covers advanced supervised and unsupervised machine learning concepts. Focuses on mathematical and computational foundations of learning algorithms. Topics may include kernel methods and models appropriate for structured data, including time-series and other sequences. Covers parameter estimation techniques (including Bayesian learning); generative models; and sampling strategies like Markov Chain Monte Carlo methods. May include mathematical proofs and empirical analysis as methods to assess the validity and performance of algorithms. Applies concepts to common problem domains.
Prerequisites
- DS 4400 (min D-)
Offering history
| Term | Sections | Enrolled | Capacity | Full | Open seats/section |
|---|---|---|---|---|---|
| Fall 2023 | 1 | 58 | 70 | 83% | 12.0 |
| Spring 2024 | 1 | 93 | 87 | 107% | 0.0 |
| Fall 2024 | 2 | 53 | 149 | 36% | 48.0 |
| Spring 2025 | 2 | 166 | 169 | 98% | 1.5 |
| Fall 2025 | 3 | 84 | 144 | 58% | 20.0 |
| Spring 2026 | 2 | 222 | 224 | 99% | 1.0 |
Snapshots from scheduled scrapes — not live seat availability. "Full" can exceed 100% when sections over-enroll.
Meeting times
Share of recent sections by weekday: M 49% · T 21% · W 79% · Th 49% · F 8%
Common patterns: MWR (49% of sections), W (30% of sections), T (13% of sections), TF (8% of sections) — in patterns, R means Thursday
Professors
Fall
- Eric Gerber (43% of students) · reviews
- Virgil Pavlu (30% of students) · reviews
- Deahan Yu (27% of students) · reviews
Spring
- Eric Gerber (81% of students) · reviews
- Chieh Wu (19% of students) · reviews
Percentages are each professor's average share of the season's enrolled students in recent terms.
Links
Official catalog (DS course descriptions) · Student reviews on RateMyHusky · All DS courses · Plan it at numap.app