decision-making computing course
Dive into building robust decision-making computing systems from start to finish. Master architectures, hybrid rules and ML logic, efficient data pipelines, performance monitoring, and governance practices to create secure, scalable, low-latency engines that drive cutting-edge tech products in real-world applications.
4 to 360 hours flexible workload
valid certificate in your country
What will I learn?
This course teaches you to design, deploy, and manage end-to-end decision-making systems. You'll define objectives, structure data inputs, integrate stores and features, merge rules with machine learning, optimise for latency, scalability, and security, plus handle monitoring, retraining, explainability, and governance for reliable automated decisions.
Elevify advantages
Develop skills
- Design decision architectures: create APIs, feature stores, and event-driven workflows.
- Implement hybrid decision logic: integrate rules, ML models, and scoring for rapid deployment.
- Configure data pipelines: validate, normalise, and stream inputs for minimal latency.
- Monitor decision quality: track model drift, meet SLAs, and enable rollbacks with key metrics.
- Build explainable decisions: provide clear reasons, full 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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