Build the internal skills to operate advanced feature engineering without permanent vendor dependency.
Advanced Feature Engineering for Machine Learning Models
Turn advanced feature engineering from a stated policy into a practice your organisation can evidence.
📍 Abu Dhabi🗓️ 5 training days📚 4 modules🎓 Accredited certificate
5intensive training days
4scientific modules
8training sessions
32detailed points
Course Overview
Most organisations now hold more data about advanced feature engineering than they can actually act on. Vendors sell this part of digital and data-driven work as a product; it behaves in practice as a change programme. Benchmarking exercises repeatedly place this area of digital and data-driven work among the areas with the widest performance spread. The course gives participants a defensible structure for advanced feature engineering and the judgement to adapt it. Sessions alternate between guided analysis of the digital and data-driven work discipline and supervised application. The content is relevant to those who own the digital and data-driven work capability and to those who are held accountable for its results. Moving advanced feature engineering from written policy into daily practice is not achieved by a single decision. Participants finish able to explain this area of digital and data-driven work to a non-specialist audience without losing precision. It ends with a prioritised list of changes to this aspect of digital and data-driven work that the participant is prepared to defend internally.
Expected Learning Outcomes
Present the case for investment in advanced feature engineering in terms that a finance function will accept.
Set retention, lineage and deletion rules for the data flowing through advanced feature engineering.
Reduce avoidable variation in how advanced feature engineering is carried out across teams.
Select indicators that show whether advanced feature engineering is improving, and reject those that only look useful.
Define escalation and fallback for advanced feature engineering when the automated path fails.
Evaluate the bias, fairness and explainability obligations attaching to advanced feature engineering.
Who Should Attend
Information security officers reviewing the exposure created by advanced feature engineering.
Those responsible for briefing external stakeholders on advanced feature engineering.
Technology and digital transformation managers leading advanced feature engineering.
Programme managers coordinating delivery of advanced feature engineering across teams.
Chief information officers accountable for the investment in advanced feature engineering.
Training and development staff building internal capability in advanced feature engineering.
Course Modules
Advanced feature engineering: measuring benefit and retiring what it replaces
2 sessions · 8 pointsSession 1The data question everyone skips at the start of advanced feature engineering
- Test advanced feature engineering against edge cases drawn from real historical records.
- Confirm the retention and deletion rules applied to data inside advanced feature engineering.
- Define acceptance criteria for advanced feature engineering in advance.
- Define the service level advanced feature engineering must meet and what happens when it is missed.
Session 2The governance advanced feature engineering needs and the governance it does not
- Agree what will be standardised in advanced feature engineering and what will not.
- Remove steps in advanced feature engineering that add effort without adding assurance.
- Record what was learned when advanced feature engineering did not go as planned.
- Benchmark the organisation's advanced feature engineering against comparable operations.
Advanced feature engineering: architecture, integration and the existing estate
2 sessions · 8 pointsSession 1Reading the current state of advanced feature engineering honestly
- Set out how exceptions to advanced feature engineering are requested and approved.
- Identify the skills the team lacks to operate advanced feature engineering independently.
- List the data sources advanced feature engineering consumes and confirm each has a named owner.
- Plan the sequence in which improvements to advanced feature engineering will be introduced.
Session 2Escalation and decision rights in advanced feature engineering
- Close out actions on advanced feature engineering rather than leaving them open indefinitely.
- Establish the boundary of advanced feature engineering and record what sits outside it.
- Verify that advanced feature engineering still performs when input volume doubles unexpectedly.
- Build the user briefing that explains what advanced feature engineering does and does not decide.
Advanced feature engineering: from pilot to production
2 sessions · 8 pointsSession 1Sizing advanced feature engineering honestly before committing budget
- Agree the smallest change to advanced feature engineering that would be visibly useful.
- Define the exit route from the supplier supporting advanced feature engineering.
- Assess the regulatory obligations advanced feature engineering triggers in each jurisdiction.
- Measure the current quality of the data feeding advanced feature engineering before assuming it is usable.
Session 2Choosing a supplier for advanced feature engineering without being captured
- Test the procedure for advanced feature engineering against a realistic scenario.
- Agree who is on call for advanced feature engineering outside working hours.
- Design the pilot for advanced feature engineering so that a negative result is still useful.
- Reduce the variation in how advanced feature engineering is carried out between teams.
Advanced feature engineering: cost, licensing and total running expense
2 sessions · 8 pointsSession 1Getting other functions to support advanced feature engineering
- Identify the data already collected that bears on advanced feature engineering.
- Check that advanced feature engineering still works when volumes rise unexpectedly.
- Identify every system advanced feature engineering must read from or write to.
- Set out the decisions in advanced feature engineering that require sign-off and by whom.
Session 2The pilot that actually settles the argument about advanced feature engineering
- Plan how advanced feature engineering is versioned and how a bad release is rolled back.
- Estimate compute and licensing cost for advanced feature engineering at expected and at peak load.
- Anticipate the objections advanced feature engineering will raise and prepare the answers.
- Specify the fallback path when advanced feature engineering is unavailable.
Choose the package that suits you
Silver Package
At least 3 people
USD1,250
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Gold Package
At least 3 people
USD1,850
- 5-night stay in a 5-star hotel
- Workshop or Program Participation
- Airport Transfers
- Customized Badge
- Expert Mentorship (Private Sessions)
- Supervision & Secretarial Services
- Accredited Certificate of Participation
- Complete Training Kit
- Coffee Break
- Closing Ceremony
Complete your registration
We will contact you within one business day to confirm.