📜 Autonomous Systems for Discovery

📜 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

  • Develop, defend, and execute a project proposal for self-driving labs at an in-person training facility

List of Microcourses#

Course Title

Learning Outcome

Link

Students

Completions

💡

Introduction to AI for Discovery using Self-driving Labs

Recreate a color-matching SDL from scratch using LEDs and a light sensor

Register

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📈

AI and Materials Databases for Self-driving Labs

Write Python scripts to iteratively optimize materials and log results to a database

Register

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🦾

Autonomous Systems for Self-driving Labs

Write Python scripts to control robots and orchestrate workflows

Waitlist

N/A

N/A

🧑‍💻

Software Development for Self-driving Labs

Leverage software development tools and implement best practices

Waitlist

N/A

N/A

🏢

AC Training Lab Design Project

Develop, defend, and execute a project proposal

Waitlist

N/A

N/A

Course Flowchart#

Note

If you have questions about these courses, feel free to reach out to sterling.baird@utoronto.ca.

_images/course-flowchart-light.svg

The microcourses progress in three stages—introduction, deeper dives, and capstone—as shown. Courses #1-#4 are fully remote and asychronous, and the final capstone course will be conducted in-person at the AC Training Lab, where participants will have access to both educational and research-grade equipment.#

_images/course-flowchart-dark.svg

The microcourses progress in three stages—introduction, deeper dives, and capstone—as shown. Courses #1-#4 are fully remote and asychronous, and the final capstone course will be conducted in-person at the AC Training Lab, where participants will have access to both educational and research-grade equipment.#

Table of Contents#

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