AIF-C01, MLA-C01, and AIP-C01 are not a difficulty ladder — they are three different job surfaces: AIF tests whether you can talk about it, MLA tests putting ML into production, AIP tests integrating someone else's foundation models into a system. But in August 2026 the choice is gated by time: the official certification page announces that the last day to take MLA-C01 in English is September 28, 2026 — 40 days from today — while MLA-C02 registration does not open until September 1 and its exam guide is unpublished. Non-English candidates (Japanese, Korean, Simplified Chinese) have a materially longer window. The same page also carries two codes, MLA-C02 and ME1-C02, with no stated relationship. And the renewal graph works backwards on ordering: passing AIP-C01 renews AIF-C01, MLA-C01, and Data Engineer – Associate for three years each.
The AIF-C01 exam guide moved to v1.1 on April 30, 2026, adding seven objectives at once — MCP, multi-agent patterns, context engineering, token-based pricing, and hallucination detection all became testable, and Bedrock AgentCore, Kiro, and Strands Agents joined the in-scope services. Almost every summary in circulation describes the older version. This guide builds a four-week path on the official five-domain weighting (20/24/28/14/14). Official specs: $100, 90 minutes, 65 questions (50 scored), pass at 700, valid 3 years — and it is the only exam in this series offered in Traditional Chinese.
AIP-C01 is AWS's only professional-level certification dedicated to GenAI application development, and it explicitly excludes model development, advanced ML, and feature engineering — it tests integrating someone else's foundation model into a production system. Domain weights are 31/26/20/12/11, and nearly half the skills in the heaviest domain sit in vector stores and RAG. A March 2026 refresh added Bedrock AgentCore and the beta ended March 31, so anything older is stale. Official specs: $300, 180 minutes, 75 questions (65 scored), pass at 750, valid 3 years — and passing it renews AIF-C01, MLA-C01, and Data Engineer – Associate at the same time.
AI-103 replaces AI-102, retired June 30, 2026, and the objectives were rewritten around Microsoft Foundry — prompt flow, Azure AI Studio, Azure OpenAI Service, and Azure AI Agent Service appear nowhere in them. The five skill areas weigh 25-30 / 30-35 / 10-15 / 10-15 / 10-15, with generative AI and agents the largest. Official specs: $165, 120 minutes, pass at 700, offered in Traditional Chinese, may include interactive components — and it is valid for only one year, though renewal is a free, open-book, unproctored online assessment.
NCA-GENL is usually what a job posting means by 'NVIDIA Generative AI / LLM certification.' But the official blueprint diverges sharply from the name — Core Machine Learning and AI Knowledge 30%, Software Development 24%, Experimentation 22%, Data Analysis 14%, Trustworthy AI 10% — with LLM and RAG content scattered at bullet level rather than forming a domain, alongside spaCy, NumPy, Keras, and cross validation. The other thing to know first: NVIDIA's official preparation courses all cost money ($30–$500), making it the only vendor in this series without a free official learning path. Official specs: $125, 1 hour, 50–60 items, two-year validity, English only, pass/fail with no score reported.
NCA-GENM matches NCA-GENL on price, length, and level but not on emphasis: Experimentation rises to 25% (the heaviest), Core ML drops from 30% to 20%, and two new areas appear — Multimodal Data 15% and Performance Optimization 10%. The content covers U-Net, CLIP, diffusion models, multimodal loss functions, attention maps, and NVIDIA's Riva / NeMo / Triton / ACE SDKs. Watch the cost structure: two of the five recommended courses exist only as $500 workshops with no self-paced option, so a self-study path cannot cover the official set. Official specs: $125, 1 hour, 50–60 items, two-year validity, English only.