ECON 3389
Machine Learning for Economics · 7 instructors on record · 20 sections
That is the class itself, averaged across everyone who taught it. Who taught it, and how each of them scored, is the board below — that is what a student picking a section is actually choosing between.
Boston College's own “intellectually challenging” question for this class only — students answer it positively about courses that stretched them, so it measures intellectual challenge and NOT grading, workload or quality. Almost every BC class scores high on it, which is why it is shown as a rank rather than a score.
Boston College reports workload for this class only as one of five bands, not as a number of hours, and it does not publish what the bands mean — so this site will not translate it into hours. Higher means more work, which is not the same as worse.
Large scale datasets, both in length (number of observations) and width (number of variables) have become ubiquitous across many applied areas. The goal of this course is to provide an introduction to methods that allow us to use these datasets for forecasting and classification, as well as for simplifying these very wide datasets with dimensionality reduction methods. The course will also examine how to explore network connectivity with such long and wide datasets. The course will make use of computational libraries from Python, Julia, or Matlab, but students are free to make use of other coding methods, such as R or Stata.
Scores are real averages. The order also accounts for how many records back each one — the count is under every score — so one perfect review does not outrank a semester of them. 1 of the 7 rows carry a mark saying so.
| Rank | Instructor | Overall | Workload | Challenge | RMP overall |
|---|---|---|---|---|---|
| 1 | Yunus Semih CoskunEconomics | 923 records | 78th | 63rd | —no page |
| 2 | Shane McmikenEconomics Provisional | 842 records | 78th | 55th | —no page |
| 3 | Haydar EvrenEconomics Provisional | 782 records | 78th | 30th | —no page |
| 4 | Arnab PalitEconomics | 774 records | 78th | 51st | 401 rating · all classes |
| 5 | Anshuman BhakriEconomics Provisional fewer records | 711 record | 78th | 29th | —no page |
| 6 | Anatoly ArlashinAdvancing Studies | 734 records | 81st | 48th | 1002 ratings · all classes |
| 7 | Pietro VisaggioEconomics | 734 records | 39th | 34th | —no page |
How this board is orderedPositions account for how many records stand behind each number, so one perfect review does not outrank a semester of them. Every score shown is the real average — only the ordering is adjusted. The comparison here is the class itself: a thin record is read against how this class was rated overall, not against the university.
Every instructor with an evaluation record for this class is on this board — it is not a top ten, and nothing is hidden behind a “show more”. Overall is the instructor's blended score for THIS class only, and its one contributing source is Boston College's evaluations for the sections in the row's record count — nothing on this board is an average across the other things they teach. Workload and Challenge are RANKS against every class we hold, not scores: BC's questions all sit near the top of the 1-5 scale, so a raw number would put almost every row in the high eighties and tell you nothing. Challenge is BC's “intellectually challenging” item, which students answer positively about courses that stretched them — it is not a measure of difficulty or grading. Neither column is ever marked better or worse. 3 of 7 rows are marked provisional: fewer than 3 records stand behind the number. That is thin evidence, not a bad instructor — the record count is in every row. The RateMyProfessors column is an instructor's overall figure across everything they teach; that site has no course dimension, so it is shown for information and kept out of the ranking.
The line
All 13 items · means across 20 recordsBar length is the rank against every comparable record we hold, not the raw score: BC's questions all have a median around 4.5, so a raw-scale bar would be nearly full on every row and would tell you nothing. Every bar is one ink colour — nothing here is graded green or red. The hatched bars are not ratings at all: a higher number on either describes a different course, not a better one.
Game log
20 sections · newest first| Instructor | Term | Sec | Instr | Course | Work |
|---|---|---|---|---|---|
| Pietro Visaggio | Spring 2026 | 02 | 70 | 63 | 40 |
| Pietro Visaggio | Spring 2026 | 03 | 80 | 73 | 60 |
| Pietro Visaggio | Fall 2025 | 01 | 63 | 58 | 40 |
| Pietro Visaggio | Fall 2025 | 02 | 77 | 74 | 60 |
| Shane Mcmiken | Spring 2025 | 02 | 86 | 84 | 60 |
| Shane Mcmiken | Spring 2025 | 03 | 82 | 72 | 60 |
| Anshuman Bhakri | Fall 2024 | 02 | 71 | 77 | 60 |
| Yunus Semih Coskun | Summer 2024 | 01 | 100 | 100 | — |
| Yunus Semih Coskun | Summer 2024 | 03 | 75 | 65 | 60 |
| Arnab Palit | Spring 2024 | 01 | 81 | 74 | 60 |
| Arnab Palit | Fall 2023 | 01 | 78 | 75 | — |
| Arnab Palit | Fall 2023 | 02 | 83 | 75 | — |
| Arnab Palit | Summer 2023 | 01 | 64 | 60 | — |
| Yunus Semih Coskun | Summer 2023 | 03 | 100 | 100 | — |
| Anatoly Arlashin | Summer 2022 | 01 | 80 | 80 | 80 |
| Anatoly Arlashin | Summer 2022 | 02 | 73 | 67 | — |
| Haydar Evren | Spring 2022 | 01 | 77 | 78 | 60 |
| Haydar Evren | Spring 2022 | 03 | 78 | 69 | 60 |
| Anatoly Arlashin | Fall 2021 | 01 | 70 | 67 | 60 |
| Anatoly Arlashin | Fall 2021 | 02 | 69 | 68 | 60 |
How to read this boardInstructors are ranked on their record in this class only, never on their average across everything they teach. Scores are out of 100 — Boston College's 1–5 agreement scale, ×20, the way these numbers were printed for years. Workload is BC's own five-band figure, not a number of hours, and is shown as a rank. A dash means the question was not reported, and is never a zero.