Recommender Systems Engineering
Build recommenders as the two-stage systems they actually are: cheap candidate generation feeding an expensive ranker inside a fixed latency budget. Learners implement collaborative filtering and a two-tower retrieval model on the same interaction data, then confront cold start, popularity bias and the feedback loops that make a model look better offline than it performs live. The course closes with an A/B design that ties offline metrics to online lift.
What this course covers.
6 modules, 42 named skill atoms. Expand any module to see them.
1Two-Stage Architecture7 skill atoms
2Collaborative Filtering and Factorisation7 skill atoms
3Two-Tower Retrieval7 skill atoms
4Features, Freshness and Cold Start7 skill atoms
5Bias and Feedback Loops7 skill atoms
6Offline Metrics versus Online Lift7 skill atoms
AI-217 in the role journeys.
This course appears in 2 of our 45 role journeys. Here is what a learner takes immediately before and after it in each.
Roles this course serves
This course is authored to band B4.
Every course we run is written to one rung of the CASI ladder, so a plan can be assembled to take a team from where they are to where they need to be.
What do B1–B6 mean?The CASI Capability Ladder — click to expand
Every course targets a band on the CASI Capability Ladder — our six-band proficiency scale, anchored to open standards (O*NET, ESCO, NICE, NIST AI RMF, Bloom's). A band tells you how deep a course goes, and what evidence proves it.
A note on B6. Courses in this catalog target B1–B5. B6 is not taught — it is recognised, through a portfolio and a panel, once someone is setting direction for others. Every journey here is built to land a learner at B5.
Other AI courses at this level.
Departmental AI Adoption & Automation Design
Transformers from First Principles
Fine-Tuning with Hugging Face
Distributed Training Foundations
Synthetic Data Generation & Evaluation
Vector Databases & Hybrid Search
Run AI-217 for your team.
This course runs at several lengths depending on how deep you need to go and how much of it your people already have. Tell us who is being trained and we will scope it.