decision-making computing course
Master end-to-end decision-making systems in this course. Explore architectures, hybrid logic using machine learning and rules, data pipelines, monitoring tools, and governance practices. Build secure, scalable, low-latency decision engines that drive real-world technology products with precision and reliability.

4 to 360h flexible workload
certificate valid in your country
What will I learn?
This course teaches you to design and deploy complete decision-making systems. You will define objectives, structure inputs, integrate data and features, combine rules with machine learning, and optimize for latency, scalability, and security. Additionally, you will learn 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 workflows.
- Implement hybrid decision logic: integrate rules, ML models, and scoring layers efficiently.
- Configure data pipelines: validate, normalize, and route inputs for low-latency processing.
- Monitor decision quality: track model drift, SLAs, and enable rollbacks using key KPIs.
- Build explainable decisions: provide human-readable reasons, audits, and safe deployment strategies.
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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