Build a Topic-Modeling Pipeline for Citizen Feedback
Overview
What this challenge is about.
Build a BERTopic pipeline for citizen feedback in three languages, tune topics by department, and create a dashboard. Earn a verifiable certificate.
The Brief
What you'll do, and what you'll demonstrate.
Build a multilingual topic-modeling pipeline that surfaces actionable themes from 60,000 citizen comments and a dashboard officials actually read.
Earning criteria — what you'll demonstrate
- Apply transformer-based topic modeling to a real multilingual corpus
- Tune topic count using both automated and manual criteria
- Visualize topic trends in a stakeholder-readable dashboard
- Communicate qualitative themes from quantitative analysis
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Natural Language Processing
Master · Ai Ml
Fit score: 1
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
Career paths this builds toward
Canonical rolesData Scientist
Topic-modeling free-text feedback and turning it into a stakeholder dashboard is bread-and-butter data-scientist work at government, NGO, and product-research teams.
This challenge sharpens
- topic-modeling
- multilingual-nlp
- dashboarding
NLP Engineer
Working with multilingual sentence embeddings and tuning topic-modeling pipelines is the NLP-engineer skill set behind any text-analytics product.
This challenge sharpens
- bertopic
- sentence-embeddings
- multilingual-nlp
Applied AI Scientist
Translating quantitative topic models into qualitative briefs that influence decisions is exactly the applied-AI work civic-tech and public-sector consultancies hire for.
This challenge sharpens
- topic-modeling
- python
- dashboarding