Space Exploration

External: Coursera Courses ↗ · Coursera

Open Course on External: Coursera

Free to audit · Opens on External: Coursera

Space Exploration

Coursera · Beginner ·📄 Research Papers Explained ·3mo ago

Key Takeaways

Explores European astronautical and robotic exploration of the Moon and Mars

Original Description

The course provides an overview of European activities in the field of astronautical and robotic exploration. In the context of ESA's exploration strategy "Terrae Novae", scientific goals for the exploration of the Moon and Mars, technological challenges, potential commercial opportunities in the field of exploration, as well as physiological aspects of long-term astronautical missions in low Earth orbit and beyond will be considered. The modules of the course cover the following topics: • Introduction to Space Exploration • European Exploration Strategy: TERRAE NOVAE • Earth-Moon Transportation Architectures • ISRU – Enabling sustainable space exploration • Earth`s Moon: the “planet next door” • Current Status of Mars Missions and Research • Commercialisation: ESA approach for stimulating the growth of an in-space economy • Medical Aspects of Long-term Spaceflight
Watch on External: Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

I Spent Weeks Looking for a Research Gap Before I Realized I Was Searching the Wrong Way
Learn how to effectively find research gaps by changing your approach, a crucial skill for AI researchers and academics
Medium · AI
ICMI 2026 Reviews [D]
Learn how to interpret ICMI 2026 reviews and improve your paper's acceptance chances
Reddit r/MachineLearning
Workshop submission for main conference paper under review [D]
Learn how to navigate submitting a paper to a non-archival workshop before the final decision of a main conference like ECCV
Reddit r/MachineLearning
Kept context-switching between arxiv, OpenReview, GitHub, and HuggingFace for every paper, so I built this. Chrome extension + website with everything inline, plus citation graph + SPECTER2 neighbors. 3M papers, free, feedback welcome [P]
Streamline your research with a new Chrome extension and website that integrates 3M papers from arxiv, OpenReview, GitHub, and HuggingFace, including citation graphs and SPECTER2 neighbors, and provide feedback to improve it
Reddit r/MachineLearning
Up next
Beyond Big Vendors: ERP Systems Explained #shorts
Digital Transformation with Eric Kimberling
Watch →