Aptivio

Find your next skill.

Describe what you know and where you're headed. Aptivio retrieves the courses whose reviews actually match your intent — ranked by similarity, not by what's popular.

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Coverage

80

Courses indexed

109,776

Reviews scored

12

Categories

7,815

TF-IDF terms

Real numbers from the indexed dataset, not marketing copy.

How it works

Retrieval, not a black box.

  1. 01

    Describe your intent

    Type what you already know and where you want to go, in plain language — no keyword search syntax.

  2. 02

    Vectorize the query

    The same TF-IDF vectorizer used at training time turns your sentence into a weighted term vector.

  3. 03

    Compare against every review

    Cosine similarity scores your query against all 109,776 course reviews in the corpus, not a cached subset.

  4. 04

    Rank by best match per course

    Each course keeps only its single best-scoring review, then courses are ranked by that score — no popularity weighting.

Why retrieval

No LLM in the loop

Deterministic, not generative

Same query, same vectors, same ranking — every time. Nothing is hallucinated or paraphrased by a language model.

Full-corpus scoring

Every review, every time

No pre-filtered shortlist. Your query is scored against the entire dataset, so a course can't be missed just because it's less common.

Transparent ranking

Scores you can inspect

Match percentage is relative similarity, shown plainly — not a hidden relevance algorithm tuned for engagement.

From the review corpus

Real excerpts from the same dataset the matching engine searches — not marketing testimonials.

Python for Data Science exceeded my expectations from the very first module. Working with NumPy arrays and Pandas DataFrames was the highlight of this course.

Python for Data Science

I want to share my detailed thoughts on Machine Learning Fundamentals after completing the full program. Training and evaluating models using scikit-learn was practical.

Machine Learning Fundamentals

I recently completed JavaScript Full Stack Development and it was a fantastic learning experience. Connecting a React frontend to a Node backend finally clicked.

JavaScript Full Stack Development

FAQ

Is this powered by an LLM?+

No. Matching is TF-IDF vectorization plus cosine similarity — a retrieval method, not a generative model. Nothing here is written by an AI at request time.

What does the match percentage actually mean?+

It's relative similarity within a single search: the best result is set to 100% and everything else is scored against it. It reflects closeness to what you typed, not a verified accuracy figure.

How many courses are indexed?+

80 courses, drawn from 109,776 individual course reviews used to build the similarity index.

Can I save or bookmark a course?+

Yes — create a free account and bookmark courses from Dashboard or Discover Paths. Your skills profile also generates a personalized Roadmap.

Where does the review data come from?+

A training corpus built for this project, used to construct and evaluate the retrieval index.

Accounts, saved paths, and a skills profile are live.

Create an account to bookmark courses and get a roadmap generated from your own skills.

Create your account