EXIN BCS ML Award case studies
EXIN BCS ML Award · Put your knowledge to work in context.
The EXIN BCS Machine Learning Award is a foundation-level certification from EXIN that gives a structured introduction to machine learning: key algorithms, data processing, model training, and real-world applications. The source positions it for people who are new to AI as well as for practising technologists, naming software developers, IT professionals, data analysts, data scientists, business leaders and AI strategists, project and product managers, engineers and technical consultants among the intended audience, alongside anyone with a background in science, engineering, knowledge engineering, finance, education or IT services. The EXIN BCS ML Award case studies are 5 cases and about 3,200 words.
1Routing Repair Tickets at a Regional Water Utility
Northvale Water, a regional utility, handles about 52,000 repair tickets a year across six depots. Dispatchers currently route each ticket with a keyword list and customer-type rules.
674 words, about 3 min2A Churn Model with a Suspicious 96% Accuracy
FitLoop is a subscription fitness app with 220,000 active customers and a monthly churn rate of 4.1%. A junior data scientist has built a churn model in Python with scikit-learn.
651 words, about 3 min3Choosing a Classifier for Rare Machine Failures
Atlas Components runs a CNC machining line with 14 vibration, temperature and pressure sensors. Maintenance engineers have labelled 1,800 run-to-failure windows over three years; 6.8% of windows end in failure within 24 hours.
602 words, about 3 min4Demand Forecast Drift After a Promotion System Change
FreshCart operates 340 grocery stores and uses a daily SKU-level demand forecast to drive replenishment. The model was deployed 14 months ago and initially achieved 10.8% weighted MAPE.
641 words, about 3 min5Credit Limit Increases and the Explainability Requirement
Meridian Bank wants to replace its rule-based credit-limit increase programme for 1.2 million card customers. Today 6% of eligible customers receive an increase, with a 2.1% bad rate.
632 words, about 3 min