Embodied AI & Robot Learning Certification

The Embodied AI & Robot Learning Certification is a free advanced-level, 25-minute skill test from Science of Apps. It tests embodied AI and robot learning — imitation learning and behaviour cloning, reinforcement learning for control, sim-to-real transfer and domain randomisation, vision-language-action models and robot foundation models, diffusion and transformer policies, world models, and the safety standards for deploying learned robots — written to the research behind RT-2, Diffusion Policy, ACT, Open X-Embodiment and DreamerV3, plus ROS 2 and ISO 10218, for 2026 and 2027. Score 70% or more on its 25 questions to earn a verifiable Embodied AI & Robot Learning certificate (SOA-EARL). Every question is based on published standards and research — including Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World (Tobin et al., 2017) (arXiv), Reinforcement Learning: An Introduction (2nd ed.) (Sutton and Barto, MIT Press (2018)), RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control (Brohan et al. (arXiv 2023)) — and each answer is explained with its source.

Science of Apps offers a free Embodied AI & Robot Learning Certification, written for 2026 and 2027. It tests imitation learning, reinforcement learning for control, sim-to-real and world models, foundation models for robotics and systems, safety and deployment 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 Embodied AI & Robot Learning 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: Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World (Tobin et al., 2017) (arXiv); Reinforcement Learning: An Introduction (2nd ed.) (Sutton and Barto, MIT Press (2018)); RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control (Brohan et al. (arXiv 2023)); Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware (ACT / ALOHA, Zhao et al., 2023) (arXiv); ISO 10218-1: Robotics — Safety requirements (ISO); Diffusion Policy: Visuomotor Policy Learning via Action Diffusion (Chi et al. (arXiv 2023)). 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: Imitation Learning (Behaviour cloning, Demonstration data and Interactive correction); Reinforcement Learning for Control (Rewards and exploration, Policy optimisation and Sample efficiency); Sim-to-Real and World Models (Domain randomisation, System identification and Learned simulators); Foundation Models for Robotics (Vision-language-action models, Cross-embodiment data and Language grounding); Systems, Safety and Deployment (ROS 2 integration, Safety standards and Monitoring). Every question is an original scenario written to the 2026–2027 standard, with the published source named under it.

Robotics ML engineer, Robot learning researcher, Autonomy or controls engineer, Humanoid or manipulation startup engineer and Graduate student in robotics. It suits students at leading universities, career switchers and experienced professionals who want quick, verifiable proof of Embodied AI & Robot Learning 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.

A VLA model takes camera images and a natural-language instruction and outputs robot actions directly. RT-2 showed that co-training a vision-language model on web data and robot trajectories, with actions represented as tokens, improves generalisation to new objects and instructions.

Simulators differ from reality in physics, sensing, latency and appearance. Policies can exploit simulator quirks, so engineers use domain randomisation, system identification, realistic sensor models and real-world fine-tuning to close the gap.

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.