📜 Autonomous Systems for Discovery#
AC Microcourses are short-form courses to learn about AI and automation for scientific discovery
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Advanced materials hold the potential to improve our lives and our world, but traditional methods of discovery are slow and expensive. “Self-driving” laboratories (SDLs) have the power to fast-track materials discovery by using AI and robotics to run lab experiments autonomously. State-of-the-art SDLs require interdisciplinary teams and skillsets that traditional degree-based programs do not provide. To reduce this barrier-to-entry, the Acceleration Consortium @ University of Toronto presents the Autonomous Systems for Discovery certificate containing short, hands-on courses that will provide familiarity with the terminology, principles, and tools of SDLs.
Certificate Outcomes#
Design and build basic self-driving lab prototypes using physical hardware and Python programming
Acquire multidisciplinary skills in data science, robotics, and software development
Develop advanced technical proficiencies in AI, database management, and workflow orchestration
Implement software development best practices through state-of-the-art software development tools
List of Microcourses#
Course Title |
Learning Outcome |
Link |
Students |
Completions |
|
|---|---|---|---|---|---|
💡 |
Recreate a color-matching SDL from scratch using LEDs and a light sensor |
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📈 |
Write Python scripts to iteratively optimize materials and log results to a database |
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🦾 |
Write Python scripts to control robots and orchestrate workflows |
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🧑💻 |
Leverage software development tools and implement best practices |
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Table of Contents#
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