Practical AI for Scientists
FutureHouse provides a free, self-paced tutorial series for researchers who want to integrate AI into their work — no advanced computational background required.
Who This Is For
This series is built for scientists from non-computational backgrounds. If you've been hearing about the roles AI can play in biology research — protein structure prediction, single-cell analysis, agent-based research workflows — and you're looking for an introductory course that doesn't require a computer science degree, this is for you.
In this tutorial, we treat AI not as a black box, but as a set of statistical tools built on assumptions and data. With a basic understanding, you can evaluate AI methods, question their outputs, and apply them thoughtfully in your own work.
The only prerequisite is a curious mindset.
About
What You'll Learn
By the end of the series, you'll be able to:
- Recognize the basic ideas behind modern AI and machine learning
- Read AI-heavy scientific publications without getting lost
- Identify clear opportunities to integrate AI into your own research workflow
- Implement AI tools and agents on your own
Start Here
Course Overview
The first edition of our tutorial series introduces the concepts a scientist needs to start using AI productively — from how modern AI models actually work to deploying your first AI agent. It's structured for people who want to move beyond reading about AI to actually using it.
What's Inside:
Chapter 1 — Introduction
- 1.1 Evolution of AI
- 1.2 An Overview of AI Models
- 1.3 Large Language Models in Biology
Chapter 2 — Applications of AI in Biology
- 2.1 Overview
- 2.2 Extracting Information from Literature
- 2.3 Integrating External Databases
Chapter 3 — LLM Agents
- 3.1 Theoretical Background
- 3.2 Building Custom Python Agents
- 3.3 Deploying Agents with Anthropic’s Native Tool Use
- 3.4 Implement an Agent using Claude Agent SDK
Resources
- AI Glossary
- Introduction to Python
- Submit Your Work
Get Feedback
Submit Your Work
This tutorial series was created to help grow the scientific community’s engagement with AI and agentic workflows.
If you enjoyed the series and built an agent, workflow, or related project, we’d love to see what you created.
Project submissions are completely optional, but we welcome examples of experiments, tools, workflows, or extensions inspired by the tutorials.
You can submit your work using this Google Form.
Acknowledgements
About the Authors
Our learning materials are developed by FutureHouse's research and engineering team, drawing on the AI tools and methods they use in their own work every day. The first edition tutorial was written and developed by Geemi Wellawatte, PhD, AI Technical Lead.
What's Next
We're working on more. Future editions will go deeper into the methods and workflows scientists are asking about most.
Is there a topic you'd like to see covered, or do you have feedback? Reach out to us at tutorials@futurehouse.org.
If you're interested in supporting this work, or want to know when new updates are released, sign up for updates, and we'll keep you in the loop.
