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Cisco · AI & Machine Learning · Associate

Cisco AI and Networking Credentials exam guide

Exam AI

Cisco's AI and networking credentials cover how AI is used in network operations and how to build networks for AI workloads, from entry-level practitioner knowledge to expert AI infrastructure design (CCDE - AI Infrastructure). They help network engineers move into AI data center and AIOps roles in 2026.

QuestionsSee official page
Time limitSee official page
Passing scoreSee official page
Exam feeSee official page
Valid forSee official page
DeliveryPearson VUE test center or online proctored (CCDE practical at Pearson VUE professional centers)

Format: Varies by credential: multiple choice for associate/specialist exams; design practical for CCDE. Fee note: Varies by credential; see Cisco Learning Network.

Who it's for

Network and data center engineers who want to design or operate infrastructure for AI/ML workloads, and IT staff who want to use AI tools in network operations.

What the exam covers

The vendor does not publish a domain breakdown for this exam. Check the official exam page for the current objectives.

Eligibility & prerequisites

Required: Varies by credential; none formally for entry-level and CCDE (CCDE requires passing the 400-007 written before the practical).

Recommended: Networking fundamentals (CCNA level) for entry credentials; 5-7+ years design experience for CCDE - AI Infrastructure.

Keeping it active

Cisco certifications are generally valid 3 years and renew via Continuing Education credits or exams; check each credential.

Skills & careers

Skills it validates

  • Networking for AI/ML clusters (lossless Ethernet, RoCE)
  • GPU cluster fabric design
  • Using AI assistants for network operations
  • Data center automation and observability
  • Security and governance for AI workloads

Job roles

AI Infrastructure EngineerData Center Network EngineerAIOps EngineerNetwork ArchitectCloud Infrastructure Engineer

Where it fits in your path

Planning a degree too? See how this cert earns college credit in the College Credit Navigator.

Build my study plan

  1. Step 1: Confirm which Cisco AI credential matches your role on the Cisco Learning Network.
  2. Step 2: Refresh data center networking (VXLAN EVPN, QoS, RoCEv2 and PFC/ECN).
  3. Step 3: Study GPU cluster architectures and storage networking for AI.
  4. Step 4: Lab Nexus fabrics or use Cisco dCloud/Modeling Labs for AI fabric scenarios.
  5. Step 5: Take the relevant exam; plan CCDE - AI Infrastructure if you are a senior designer.

Make it yours: pick your exam date and weekly hours. We'll split your time by domain weight and give you a printable plan.

Exam-day tips

  • Know lossless Ethernet mechanisms (PFC, ECN, DCQCN) cold for AI fabric questions.
  • Understand training vs inference traffic patterns and their design implications.
  • For CCDE, practice design trade-off reasoning, not CLI.
  • Check exam topics on the Cisco Learning Network for the latest version.

Key terms for this exam

All 3 terms Study with thinQcards™

Frequently asked questions

Is there a CCNA AI?

Cisco does not brand an exam as CCNA AI; its AI credentials span an entry-level practitioner level, data center AI specialist exams and CCDE - AI Infrastructure.

What is CCDE - AI Infrastructure?

An expert-level design certification focused on infrastructure for AI workloads, using the CCDE written and practical model.

Do I need CCNA first?

Not formally, but networking fundamentals are assumed.

Cisco AI vs NVIDIA networking certs?

NVIDIA focuses on its InfiniBand/Spectrum-X stack; Cisco covers Ethernet AI fabrics on Nexus. Many AI infrastructure engineers pursue both.

Are they worth it?

AI data center buildouts are driving demand for engineers who can design lossless, high-bandwidth fabrics.

Official page: www.cisco.com. Reviewed November 2026. Vendors change fees and objectives, so confirm with the vendor before you book. Spot something out of date? Tell us.