4010 - Introduction to AI for Discovery Using Self-Driving Labs

Course Description

Self-driving laboratories (SDLs) incorporate AI and automation into scientific laboratories to speed up the discovery of new materials for applications such as clean energy and cancer drugs. Discover the essential principles of SDLs by building a ‘Hello World’ SDL from scratch. In this asynchronous, remote course, you will build a self-driving colour matcher using dimmable LEDs and a light sensor. This introduction will help you implement hardware/software communication, database integration, microcontroller programming, and Bayesian optimization. Each of these are important components of an SDL, and you will get a taste of these in the course modules that will prepare you for deeper dives in future courses.

This course is presented in partnership with the Acceleration Consortium at the University of Toronto.

This is an online, self-directed course, and you can work through the modules at your own pace. You can expect to complete the course in a month, but have up to 1 year to complete it.

Within 4-6 weeks of successfully completing this course, you will receive your micro-credential indicating achievement of the outlined learning outcomes and competencies/skills. Micro-credentials are tamper-proof, verifiable, blockchain-based, and 100% digital. They can be shared on social media, including LinkedIn and Facebook, embedded in websites or downloaded as PDFs.

Learning Outcomes

By the end of this course, you'll be able to:

• Define and explain key terms and principles of self-driving labs to demonstrate understanding
• Apply MQTT or similar frameworks to send commands and receive sensor data over WiFi
• Demonstrate the ability to use MongoDB to store and retrieve experiment configurations and results effectively
• Develop and implement software on a Raspberry Pi Pico W microcontroller to control device power and read sensor data accurately
• Modify a Bayesian optimization script using the Ax Platform to iteratively propose new experimental configurations
• Integrate the individual SDL components to orchestrate the full ‘Hello World’ workflow

Competencies/skills developed in this micro course include:

• Basic self-driving lab literacy
• Microcontrollers and sensors
• Bayesian optimization
• Hardware/software communication
• Database management
• Workflow orchestration

Notes

This course requires physical hardware and a 2.4 GHz WPA-2 wireless network. If you do not have the hardware, you will need to purchase the required components, replacing the USB power adapter with the correct style for your country (e.g., European type C), if necessary. You may also refer to "Before you Begin". If you do not have the required wireless network, you can use a mobile hotspot in extended compatibility mode or a SIM-enabled router (see recommendations for more information).

No withdrawals are permitted after enrolment.

Eligible learners may apply to the Ontario Student Assistance Program (OSAP) for this micro-credential. You can find more information on our Financial Aid page.

Registration in this course gives you 12 months (one year) access to the course materials and assessments. 

• Should you be unable to complete the course in the allotted time, we can provide a one-time extended access period of 6 months for a $75+HST fee. 
• The extended access fee will be non-refundable, and non-transferrable.

To request the extension, please email scs.business@utoronto.ca

This course may be applied towards the SCS Certificate(s) in

• Autonomous Systems for Discovery : Required courses