Engineering and Artificial Intelligence Course
Master AI for engineering workflows—from backlog prioritization and CI/CD to incident response and secure AI adoption. Learn practical tools, metrics, and guardrails to boost delivery speed, code quality, and reliability across your engineering teams.

from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This short, practical course shows you how to apply AI to backlog prioritization, sprint planning, incident response, and code review while keeping quality, security, and compliance in focus. Learn to integrate AI tools into existing workflows, measure impact with clear metrics, manage risk and bias, and design a safe, scalable rollout that boosts delivery speed and reliability across your organization.
Elevify advantages
Develop skills
- AI backlog planning: use ML to prioritize tickets by impact, effort, and risk.
- AI-driven incident response: detect, summarize, and resolve issues faster.
- AI-assisted code review: integrate copilots to boost quality and review speed.
- Secure AI integration: design compliant, auditable workflows across dev tooling.
- AI rollout leadership: run pilots, track KPIs, and scale adoption in engineering.
Suggested summary
Before starting, you can change the chapters and 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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