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Career learning maps

AI roadmaps for IT roles

What to learn about AI for a specific profession: from a shared AI Core to role-specific workflows, risks, practicums, and milestones.

8 interactive maps are currently available with complete evidence routes.

Core profession6–12 months

AI Engineer

From programming foundations to production AI systems

6 stagesBackend and Python developersEvidence mapped
Open roadmap →
AI upskilling10–16 weeks

Backend Developer + AI

AI capabilities in reliable backend systems

3 stagesBackend developersEvidence mapped
Open roadmap →
AI upskilling10–16 weeks

DevOps / SRE + AI

Reliable operation of AI workloads

3 stagesDevOps engineersEvidence mapped
Open roadmap →
AI upskilling8–14 weeks

Data Analyst + AI

Verified analytics with AI, SQL, and spreadsheets

3 stagesData analystsEvidence mapped
Open roadmap →
AI upskilling8–14 weeks

Frontend Developer + AI

AI interfaces, streaming UX, approvals, and generative UI

3 stagesFrontend developersEvidence mapped
Open roadmap →
AI upskilling7–12 weeks

Business Analyst + AI

Requirements, process analysis, and AI use-case discovery

3 stagesBusiness analystsEvidence mapped
Open roadmap →
AI upskilling8–14 weeks

Product Manager + AI

AI product discovery, metrics, economics, and lifecycle

3 stagesProduct managersEvidence mapped
Open roadmap →
AI upskilling10–16 weeks

Cybersecurity Specialist + AI

Threat modeling, red teaming, and AI system protection

3 stagesSecurity engineersEvidence mapped
Open roadmap →

One model without duplication

Each professional map reuses shared articles, glossary entries, topics, and evaluation materials. Role-specific branches add only the workflows, risks, tools, practicums, and readiness criteria unique to that profession. Course mode projects the same data into sequential modules and preserves progress.