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Student Ranking

TodoEconometria

Big Data with Python course leaderboard

Last updated: 2026-03-25 18:13 | Ranking updated weekly

Course Statistics

19
Students
8
Delivered
6.5
Average
2
Outstanding

Leaderboard

#2 17wk
@aurorafezu
@aurorafezu
8.2
D
7.0
C
10.0
✓ On Time
clusteringk-means
#1 17wk
@katitto
@katitto
8.7
D
9.5
C
10.0
✓ On Time
pcatime series
#3 17wk
@luuuuru
@luuuuru
7.0
D
0.0
C
10.0
✓ On Time

Challengers

#4
13wk
@CarlosRivasplata
@CarlosRivasplata⏳ -25%
D
7.0
C
10.0
#5
13wk
@fernandoramostrevi-ctrl
@fernandoramostrevi-ctrl⏳ -25%
D
9.5
C
10.0
#6
@camilogrey
@camilogrey⏳ -25%
D
3.0
C
10.0
#7
@alxz0212
@alxz0212
D
8.5
C
10.0
#8
@jaaafarr
@jaaafarr
D
8.5
C
10.0

Full Ranking

Pos Student Grade Status Project Fork
#1 (17wk) @katitto 8.7 ✓ ★ Outstanding almache_katherine See Dashboard
#2 (17wk) @aurorafezu 8.2 ✓ ★ Outstanding fernandez_aurora See Dashboard
#3 (17wk) @luuuuru 7.0 ✓ ✓ Approved camacho-lucia See
#4 (13wk) @CarlosRivasplata 5.5 ⏳-25% ✓ Approved rivasplata_carlos See
#5 (13wk) @fernandoramostrevi-ctrl 5.1 ⏳-25% ✓ Approved ramos_fernando See Dashboard
#6 @camilogrey 4.3 ⏳-25% ⋯ Under Review [raiz:camilogrey] See
#7 @alxz0212 0.0 ⋯ Under Review Alexis_Mendoza See Dashboard
#8 @jaaafarr 0.0 ⋯ Under Review Bousaid_Jaafar See

Grade Distribution

9-10 Excellent
7-8 Good
3
5-6 Passing
2
<5 Below
1

λ Reading guide

D
D (Doc) — Documentation grade (PROMPTS.md): quality, authenticity and structure of the submitted prompts.
C
C (Cod) — Code grade: Python files, notebooks, SQL, configs and project structure.
8.7
Nota — The final grade combines Doc (60%) and Cod (40%). Missing PROMPTS.md results in an additional -30%.
✓ On Time
On-time submission: the work was submitted before the ranking was published. No penalty applied.
⏳ -X%
Late submission: the work was submitted after the ranking was published. A proportional penalty is applied:
0-24h: -15% | 1-3 days: -25% | 3-7 days: -40% | >7 days: -50%

⚙ Ranking Rules

Δ Class of 2026 (18 students)

Submission window: Feb 13 - Mar 31, 2026. On-time submissions (before Feb 13) keep their grade intact. Late submissions receive progressive penalty: 0-24h (-15%), 1-3 days (-25%), 3-7 days (-40%), 7+ days (-50%). After March 31, grades are permanently frozen.

∞ Community (annual ranking)

Anyone can complete the course and appear in their year's ranking (2026, 2027...). Requirements: fork at least 30 days old with real submissions. Separate from Class of 2026. Same evaluation criteria.

Σ Evaluation Criteria

D (Doc, 60%): quality, authenticity and structure of PROMPTS.md. C (Cod, 40%): Python files, notebooks, SQL and project structure. Missing PROMPTS.md incurs an additional 30% penalty. Final grade may be affected by similarity to the professor's example.

Community Ranking

∞

No community participants yet. Fork the repository, complete the course and appear here!

The ranking updates automatically with each evaluation. Submit your work to appear!
Generated by: QUASAR (Quality Unified Automated Student Assessment & Ranking) | 2026-03-25 18:13

Course: Big Data with Python - From Zero to Production Professor: Juan Marcelo Gutierrez Miranda | @TodoEconometria Hash ID: 4e8d9b1a5f6e7c3d2b1a0f9e8d7c6b5a4f3e2d1c0b9a8f7e6d5c4b3a2f1e0d9c Methodology: Progressive exercises with real data and professional tools

Academic references: - Downey, A. (2015). Think Python: How to Think Like a Computer Scientist. O'Reilly Media. - McKinney, W. (2022). Python for Data Analysis, 3rd Ed. O'Reilly Media. - Kleppmann, M. (2017). Designing Data-Intensive Applications. O'Reilly Media.