Artificial intelligence (AI) is rapidly transforming science and laboratory automation. With all the development (and hype) surrounding AI, many scientists and managers have fundamental questions about the technology: What is AI? How does it work? Can it solve my problem?

This workshop offers a gentle introduction to the field of AI. The course will cover the three main branches of AI and machine learning: supervised, unsupervised, and reinforcement learning. Each topic will include a case study to illustrate how AI is used to solve data-intensive problems.

Who Should Attend
The workshop is designed for scientists, technicians and managers and requires only a background in introductory statistics and basic biology/chemistry.

Workshop Benefits
By the end of this workshop, participants will be able to:

• Describe the capabilities and limitations of common AI techniques.
• Understand the types of data and problems amenable to AI algorithms.
• Partner with AI practitioners to solve problems.

Workshop Topics
The workshop will cover the three main branches of artificial intelligence and machine learning (AI/ML):

• Supervised learning
• Unsupervised learning
• Reinforcement learning

Each section will include a case study selected from presentations at the previous year’s SLAS Annual Meeting. Examples include:
Supervised learning:

• Predicting chemical reactivity with artificial neural networks

Unsupervised learning:

• Identifying biomarkers with Principal Component Analysis

Reinforcement learning:

• Optimizing chemical synthesis through automation

The case study model aims to:

• Introduce the most common AI methods for each type of learning
• Connect the AI methods to a real-world example of interest to the SLAS community

Trying to Access Training? Click PURCHASE below. You will see the Member/Non-Member rate once you sign in.

$49 for SLAS Members
$99 for Non-members
Free for SLAS2021 Digital Workshop Registrants