About TransferAI Professor Ratings

How it works

We gather professor ratings, difficulty metrics, and grade distributions from trusted, verifiable sources. Then, we run AI-based quality checks to remove noise and suspicious patterns so that what you see is transparent and dependable.

• Aggregate data across multiple sources for broader coverage and cross-validation
• Normalize scales and categories to enable apples-to-apples comparisons
• Use AI to detect anomalies and exclude untrustworthy signals

Data sources

Our input data comes from well-known, credible sites and disclosures, including but not limited to:

• RateMyProfessors (RMP)
• De Anza grade datasets (e.g., de-identified grade distributions)
• Official organization or department-level public disclosures
• Community platforms (e.g., Reddit) for additional cross-checking

AI quality filters

Not all online reviews are equal. Our models identify and remove signals that are likely unreliable:

• Astroturfing/brigading patterns (e.g., mass upvotes/downvotes or coordinated posting)
• Heavily downvoted praise or copy-paste spam flagged as suspicious
• Reviewer behavior anomalies (e.g., overly repetitive timing, bot-like cadence)
• Inconsistent metadata or unverifiable claims

Example: If a professor shows extremely high praise, but those comments receive heavy downvotes or appear coordinated, our filters will mark them as unreliable and exclude them from aggregate scoring.

Interpretation & transparency

• Ratings reflect a blend of public feedback and curated signals after quality filtering
• Grade distributions are aggregated from public, de-identified datasets where available
• We continually retrain filters to adapt to new manipulation tactics

Disclaimer: TransferAI is not affiliated with or endorsed by De Anza College or RateMyProfessors. Use at your own discretion.