decision-making computing course
Master end-to-end decision-making systems. Explore architectures, machine learning-driven logic, data pipelines, monitoring, and governance to create secure, scalable, low-latency decision engines for real-world tech products. Build skills in hybrid decision design, data handling, quality tracking, and explainable AI to power robust automated decisions.

4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This course teaches you to design and deploy end-to-end decision services. You'll define objectives, structure inputs, integrate data and features, blend rules with machine learning, and optimise for latency, scalability, and security. Gain expertise in monitoring, retraining, explainability, and governance to ensure decisions remain accurate, compliant, and improvable.
Elevify advantages
Develop skills
- Design decision architectures: create APIs, feature stores, and event-driven pipelines.
- Implement hybrid decision logic: integrate rules, ML models, and scoring efficiently.
- Configure data pipelines: validate, normalise, and stream inputs for low latency.
- Monitor decision quality: track model drift, SLAs, and enable rollbacks with KPIs.
- Build explainable decisions: provide readable reasons, audits, and controlled rollouts.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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