AI Accelerators & ML Hardware Certification

The AI Accelerators & ML Hardware Certification is a free advanced-level, 25-minute skill test from Science of Apps. It tests AI accelerators and ML hardware — GPU architecture with tensor cores and the CUDA execution model, systolic arrays and TPUs, memory hierarchies and HBM, the roofline model and arithmetic intensity, low-precision formats such as BF16, FP8 and INT4, interconnects and scale-out networking, inference serving trade-offs, power, cooling and total cost of ownership, and the supply chain and export controls that shape AI compute — written to the CUDA guide, TPU paper, roofline model, FP8 and MLPerf references for 2026 and 2027. Score 70% or more on its 25 questions to earn a verifiable AI Accelerators & ML Hardware certificate (SOA-AAMH). Every question is based on published standards and research — including CUDA C++ Programming Guide (NVIDIA), MLPerf benchmarks (MLCommons), Roofline: An Insightful Visual Performance Model for Multicore Architectures (Williams, Waterman and Patterson, CACM (2009)) — and each answer is explained with its source.

Science of Apps offers a free AI Accelerators & ML Hardware Certification, written for 2026 and 2027. It tests accelerator architecture, memory and performance analysis, numerics and low precision, scale-out systems and data centres and software stacks, supply chain and strategy with 25 original scenario questions in all, each naming its published source; you get an instant score and a verifiable certificate with a credential ID you can add to LinkedIn.

Read the five skill areas on this page, then take the 25-minute test online — no fee, course or sign-up. You see every answer explained when you finish. Score 70% or more and you get a AI Accelerators & ML Hardware certificate straight away, on screen, as a PDF and by email, with a credential ID anyone can verify.

Yes. The questions are original scenarios written by Science of Apps, and each one is based on a public source you can read: CUDA C++ Programming Guide (NVIDIA); MLPerf benchmarks (MLCommons); Roofline: An Insightful Visual Performance Model for Multicore Architectures (Williams, Waterman and Patterson, CACM (2009)); FP8 Formats for Deep Learning (Micikevicius et al., 2022) (arXiv); GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers (2022) (arXiv); In-Datacenter Performance Analysis of a Tensor Processing Unit (Jouppi et al. (arXiv 2017)). The source is shown under each question and linked in the answer review. Science of Apps doesn't copy questions from other tests.

Five skill areas with five questions each, drawn from a bank of 10 per area so a retake brings new questions: Accelerator Architecture (GPU execution model, Tensor cores and Systolic arrays and TPUs); Memory and Performance Analysis (Memory hierarchy and HBM, Roofline model and Profiling); Numerics and Low Precision (BF16 and FP8, Quantisation and Accuracy trade-offs); Scale-Out Systems and Data Centres (Interconnects, Power and cooling and Total cost of ownership); Software Stacks, Supply Chain and Strategy (Compilers and kernels, Supply chain and Policy). Every question is an original scenario written to the 2026–2027 standard, with the published source named under it.

ML systems or performance engineer, Hardware or chip architect, AI infrastructure or data centre engineer, Inference optimisation engineer and Technical strategy or investment analyst covering AI compute. It suits students at leading universities, career switchers and experienced professionals who want quick, verifiable proof of AI Accelerators & ML Hardware knowledge in 2026 and 2027.

CS and AI students at MIT, Stanford, CMU, Berkeley, IITs, Tsinghua and ETH are hired on depth beyond tool use: model internals, systems and hardware. Passing earns a founder-signed Science of Apps certificate with a credential ID and QR code that recruiters can verify.

Deep learning is dominated by large matrix multiplications that can be computed in parallel. GPUs have thousands of cores and specialised tensor cores that perform dense matrix maths at very high throughput, along with high-bandwidth memory to feed them.

Often memory bandwidth rather than raw compute. The roofline model shows that kernels with low arithmetic intensity (few operations per byte moved) are memory-bound, which is why LLM decoding, for example, depends heavily on HBM bandwidth and batching.

Yes. The test is online, in English and free everywhere — people take it from India, the US, the UK, Europe, Africa, Latin America and Asia-Pacific. Your certificate is dated with your own local date and can be verified from anywhere at scienceofapps.com/certification/verify/.

25 questions — 5 from each of 5 skill areas — with a 25-minute limit. You need 70% (18 of 25) to pass and 90% for distinction.

We rate it Advanced: assumes years in the role or deep specialist knowledge. It has 25 scenario questions — 5 from each of 5 skill areas — and a 25-minute limit. You need 70% (18 of 25) to pass and 90% for distinction.

Nothing. There is no fee to take a test, to receive the certificate, to have it emailed or to verify it, and no sign-up.

On our server, not in your browser. The answers never reach the page until you submit, so a certificate can only be earned by passing. Each certificate gets a unique credential ID stored by Science of Apps.

You see your score for each area and every question with the correct answer and why, with the published source behind it. You can retake after 30 minutes, and the retake draws questions you haven't seen yet.

No. Every certificate is dated, so it always shows when you passed. Retake a test any time for a newer date or a higher score.

Yes. After you pass, Add to LinkedIn opens the Licenses & certifications form with the certificate name, Science of Apps as the issuer, the issue date, your credential ID and the verification link filled in. You can also download it as a PDF or PNG, and it's emailed to you as a PDF.

Every certificate has a credential ID and a QR code. Scanning it, or entering the ID at scienceofapps.com/certification/verify/, shows the holder's name, the certification, the score and the issue date from our records.

No. They are Science of Apps' own assessments of applied skill. They aren't issued by a university or standards body, and they work best alongside a portfolio that shows the skills in real work.