*Motivation:* The Massive Open Online Course (MOOC) "Cubes and Clouds" teaches the concepts of data cubes, cloud platforms, and open science in the context of Earth Observation (EO). The course is designed to bridge the gap between relevant technological advancements and best practices and existing educational material. Successful participants will have acquired the necessary skills to work and engage themselves in a community adhering to the latest developments in the geospatial and EO world. *Target group:* The target group are earth science students, researchers, and data scientists who want to dive into the newest standards in EO cloud computing and open science. The course is designed as a MOOC that explains the concepts of cloud native EO and open science by applying them to a typical EO workflow from data discovery, data processing up to sharing the results in an open and FAIR way. *Content:* This MOOC is an open learning experience relying on a mixture of animated lecture content and hands-on coding exercises created together with community renowned experts. The course is structured into three main chapters Concepts, Discovery and Process and Share. The degree of interaction (e.g. hands-on coding exercises) is gradually increasing throughout the course. The theoretical basics are taught in the first chapter Concepts, comprising cloud platforms, data cubes and open science practices. In the second chapter the focus is on discovery of data and processes and the role of metadata in EO. In the final chapter the participants carry out complete processing workflows on cloud infrastructure and apply open science practices to the produced results. Every lesson is concluded with a quiz, ensuring that the content has been understood. The course contains 13 written lectures that convey the basic knowledge and theoretical concepts, 13 videos which have been created with a professional communication team and in collaboration with a leading expert on the topic and shines a light on a real world example (e.g. The role of GDAL in the geospatial and EO), 16 pieces of animated interactive content which engage the participants to actively interact with the content (e.g. Sentinel 2 Data Volume Calculator) and 11 hands-on coding exercises in the form of curated jupyter notebooks that access European EO cloud platforms (e.g. CDSE) and carry out analysis there using standardized API's like openEO (e.g. full EO workflow for snow cover mapping). *Infrastructure:* The EOCollege platform hosts the lectures and the animated content (e.g. videos, animations, interactive elements) of the course. The hands-on exercises are directly accessible from EOCollege via a dedicated JupyterHub environment, which accesses European EO cloud platforms, such as the Copernicus Data Space Ecosystem, using its open science tools like the Open Science Data Catalogue, openEO and STAC. Guaranteeing that the learned concepts are applied to real-world applications. In the final exercise the participants will map the snow cover of an area of interest they choose and make their results openly available according to the FAIR principles on an web viewer (STAC browser). This community mapping project actively lives the idea of open science, collaboration and community building. *Learning achievements:* After finishing the course, the participants will understand the concepts of cloud native EO, be capable of independently using cloud platforms to approach EO related research questions and be confident in how to share research by adhering to the concepts of open science. After the successful completion of the course the participants receive a certificate and diploma supplement and their personal map is persistently available in the web viewer as a proof of work. *Benefits for the open geospatial community:* The MOOC is valuable for the geospatial and EO community and open science as there is currently no learning resource available where the concepts of cloud native computing and open science in EO are taught jointly to bridge the gap towards the recent cloud native advancements. The course is open to everybody, thus serving as teaching material for a wide range of purposes including universities and industry, maximizing the outreach to potential participants. In this sense also the raw material of the course is created following open science practices (e.g. GitHub repository, Zenodo, STAC Browser for results) and can be reused and built upon. The "Cubes and Clouds" MOOC equips participants with essential skills in cloud native EO and open science, enhancing their ability to contribute meaningfully to the open geospatial community. By promoting transparency, reproducibility, and collaboration in research, graduates of the course strengthen the foundations of open science within the community. Access to cloud computing resources and European EO platforms empowers participants to undertake innovative research projects and share their findings openly, enriching the collective knowledge base. Ultimately, the MOOC fosters a culture of openness and collaboration, driving positive change and advancing the field of geospatial science for the benefit of all.