Homework 1: Introduction to Machine Learning
- Submissions
- 969
- Completion
- 31.3%
- Median score
- 7
- Lecture time
- 3h
- Homework time
- 1.2h
- Total time
- 5h
Machine Learning Zoomcamp 2026
Machine Learning Zoomcamp 2026 Dashboard
Course-level participation, homework, and project statistics.
Course overview
- Total enrollments
- 3091
- Project submissions
- 103
- Project completion rate
- 3.3%
- Average total score
- 6.9
- Overall completion rate
- 19.0%
Project outcomes
- Score to pass
- 7
- Passed
- 0
- Failed
- 103
- Median project score
- -
Homework statistics
Median time and score by homework. Hover values on desktop for interquartile ranges.
| Homework | Submissions | Completion | Lecture time | Homework time | Total time | Median score |
|---|---|---|---|---|---|---|
| Homework 1: Introduction to Machine Learning | 969 | 31.3% | 3h | 1.2h | 5h | 7 |
| Homework 2: Machine Learning for Regression | 666 | 21.5% | 4h | 3h | 7h | 6 |
| Homework 3: Machine Learning for Classification | 579 | 18.7% | 5h | 3h | 8h | 6 |
| Homework 4: Evaluation Metrics for Classification | 553 | 17.9% | 4h | 3h | 7h | 6 |
| Homework 5: Deploying Machine Learning Models | 416 | 13.5% | 4h | 2h | 6h | 6 |
| Homework 6: Decision Trees and Ensemble Learning | 348 | 11.3% | 4h | 2h | 6h | 5 |
Homework 2: Machine Learning for Regression
- Submissions
- 666
- Completion
- 21.5%
- Median score
- 6
- Lecture time
- 4h
- Homework time
- 3h
- Total time
- 7h
Homework 3: Machine Learning for Classification
- Submissions
- 579
- Completion
- 18.7%
- Median score
- 6
- Lecture time
- 5h
- Homework time
- 3h
- Total time
- 8h
Homework 4: Evaluation Metrics for Classification
- Submissions
- 553
- Completion
- 17.9%
- Median score
- 6
- Lecture time
- 4h
- Homework time
- 3h
- Total time
- 7h
Homework 5: Deploying Machine Learning Models
- Submissions
- 416
- Completion
- 13.5%
- Median score
- 6
- Lecture time
- 4h
- Homework time
- 2h
- Total time
- 6h
Homework 6: Decision Trees and Ensemble Learning
- Submissions
- 348
- Completion
- 11.3%
- Median score
- 5
- Lecture time
- 4h
- Homework time
- 2h
- Total time
- 6h
Assignment difficulty
Ranked by lowest median question score relative to the maximum achievable. Normalizing by question count makes homeworks of different lengths comparable; a lower percentage indicates a harder assignment.
| Rank | Homework | Median score | Score % | Completion |
|---|---|---|---|---|
| 1 | Homework 6: Decision Trees and Ensemble Learning | 5 / 6 | 83.3% | 11.3% |
| 2 | Homework 1: Introduction to Machine Learning | 7 / 7 | 100.0% | 31.3% |
| 3 | Homework 2: Machine Learning for Regression | 6 / 6 | 100.0% | 21.5% |
| 4 | Homework 3: Machine Learning for Classification | 6 / 6 | 100.0% | 18.7% |
| 5 | Homework 4: Evaluation Metrics for Classification | 6 / 6 | 100.0% | 17.9% |
| 6 | Homework 5: Deploying Machine Learning Models | 6 / 6 | 100.0% | 13.5% |
Question difficulty
Share of submitted answers that were correct, per question. A lower percentage points to a harder or more confusing question. Participation-only questions are excluded.
| Homework | Question | Correct | Answers | % correct |
|---|---|---|---|---|
| Homework 1: Introduction to Machine Learning | Records count | 947 | 969 | 97.7% |
| Fuel types | 918 | 969 | 94.7% | |
| Missing values | 889 | 969 | 91.7% | |
| Max fuel efficiency | 921 | 969 | 95.0% | |
| Median value of horsepower | 678 | 969 | 70.0% | |
| Sum of weights | 883 | 969 | 91.1% | |
| Homework 2: Machine Learning for Regression | Missing values | 657 | 666 | 98.6% |
| Median for horsepower | 638 | 666 | 95.8% | |
| Filling NAs | 505 | 666 | 75.8% | |
| Best regularization | 545 | 666 | 81.8% | |
| RMSE standard deviation | 563 | 666 | 84.5% | |
| Evaluation on test | 590 | 666 | 88.6% | |
| Homework 3: Machine Learning for Classification | Mode for industry | 556 | 579 | 96.0% |
| Biggest correlation | 549 | 579 | 94.8% | |
| Biggest MI | 553 | 579 | 95.5% | |
| Accuracy | 546 | 579 | 94.3% | |
| Feature selection | 456 | 579 | 78.8% | |
| Parameter tuning | 529 | 579 | 91.4% | |
| Homework 4: Evaluation Metrics for Classification | ROC AUC feature importance | 523 | 553 | 94.6% |
| Model AUC | 509 | 553 | 92.0% | |
| Precision and recall | 510 | 553 | 92.2% | |
| F1 score | 500 | 553 | 90.4% | |
| 5-Fold CV standard deviation | 502 | 553 | 90.8% | |
| Best C | 472 | 553 | 85.4% | |
| Homework 5: Deploying Machine Learning Models | Scikit-Learn version | 396 | 416 | 95.2% |
| Conversion probability (loaded model) | 366 | 416 | 88.0% | |
| Conversion probability (API) | 347 | 416 | 83.4% | |
| Python base image | 403 | 416 | 96.9% | |
| Conversion probability (container) | 359 | 416 | 86.3% | |
| Homework 6: Decision Trees and Ensemble Learning | Original splitting feature | 332 | 348 | 95.4% |
| RMSE on validation | 332 | 348 | 95.4% | |
| Number of estimators | 149 | 348 | 42.8% | |
| Best max depth | 323 | 348 | 92.8% | |
| Most important feature | 333 | 348 | 95.7% | |
| XGBoost eta | 314 | 348 | 90.2% |
Submission timing
When homework submissions arrive relative to the deadline, across all assignments.
- A week or more early
- 617 (17.1%)
- 3-7 days early
- 391 (10.9%)
- 1-3 days early
- 486 (13.5%)
- Final day
- 1368 (38.0%)
- After the deadline
- 740 (20.5%)
Engagement over time
Homework submissions per week, across all assignments. Bars are scaled to the busiest week.
- Sep 14, 2026
- 229
- Sep 21, 2026
- 409
- Sep 28, 2026
- 703
- Oct 05, 2026
- 591
- Oct 12, 2026
- 561
- Oct 19, 2026
- 461
- Oct 26, 2026
- 384
- Nov 02, 2026
- 255
- Nov 09, 2026
- 9