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Developments in large scale computing environments have led to design of workflows that rely on containers and analytics platform that are well supported by the commercial cloud. The National Science Foundation also envisions a future in science and engineering that includes commercial cloud service providers (CSPs) such as Amazon Web Services, Azure and Google Cloud. These twin forces have made researchers consider the commercial cloud as an alternative option to current high performance computing (HPC) environments. Training and knowledge on how to migrate workflows, cost control, data management, and system administration remain some of the commonly listed concerns with adoption of cloud computing. In an effort to ameliorate this situation, CSPs have developed online and in-person training platforms to help address this problem. Scalability, ability to impart knowledge, evaluating knowledge gain, and accreditation are the core concepts that have driven this approach. Here, we present a review of our experience using Google’s Qwiklabs online platform for remote and in-person training from the perspective of a HPC user. For this study, we completed over 50 online courses, earned five badges and attended a one-day session. We identify the strengths of the approach, identify avenues to refine them, and consider means to further community engagement. We further evaluate the readiness of these resources for a cloud-curious researcher who is familiar with HPC. Finally, we present recommendations on how the large scale computing community can leverage these opportunities to work with CSPs to assist researchers nationally and at their home institutions.