2nd-5th grade

AI Adventurers Level 1: Storytelling

The AI Adventurers program is made for students age 7-11, or any elementary school student with an interest in learning the fundamentals of coding – no programming experience required!

Bright minds come together to explore the foundational logic of artificial intelligence. Through a medley of affirming growth mindset exercises, creative paper-based coding, fun block-based programming, and project-based team hack-a-thons, we cultivate the computational and algorithmic thinking kids need to create confidently. We embed concepts like events, loops, conditionals, variables, and functions within a variety of puzzles, riddles, and activities to make coding fun!

Real World

Course Features

 

Learning Outcomes

Coding Fundamentals

Artificial Intelligence

Design

Social-Emotional Learning

Students

Who Is It For?

The AI Adventurers program is made for students age 7-11, or any elementary school student with an interest in learning the fundamentals of coding – no programming experience required!

Has your student already completed AI Adventurers 1, and is looking for their next challenge? Check out the AI Adventurers, Level 2: Game Design program!

“I’m always amazed and delighted at the creativity and imagination elementary-age kids bring to coding.

Their unconventional way of thinking is exactly the kind of energy that makes computer science fun for everyone.”

– Emmy Li, Instructor & Curriculum Developer, Stanford Alum

Featured Projects

Learn More About Course Projects

Education

Squash pesky problems in buggy malfunctioning code during an immersive garden bug hunt!

Bug Hunt

Education

Left, right, accelerate, brake…customize your own hot keys to race to the finish line.

Racing Mechanics

Education

Using conditionals, weave together a story that relies on your expert decision-making skills.

Choose Your Own Adventure

Education

Collect boosts, avoid enemies, and beat the clock in a world that you code up.

Platform Jump!

Course Syllabus

The 10-session program is divided into the following modules:

Day 1: Algorithm Rhythms

Get into an algorithmic groove on your first day by taking an abstract action, breaking it down into steps, and teach your friends new moves! On this day, we learn about how computers think, deconstruct our morning routines, and “program” the teacher to make a sandwich.

Day 2: Talk It Out

On dialogue day, we harness the art of banter to communicate with humans and bots alike. Students will discover how virtual assistants understand speech, practice communicating with each other in creative ways, and code up a conversation on Scratch.

Day 3: If/Then

Our words have power, and we explore conditionals through mapping out decision trees. We will then use our knowledge of cause and effect to program an AI plant to grow when it hears words of encouragement.

Day 4: Choose Your Own Adventure

On Day 4, we explore immersive artscapes that AI can generate. Within these scenarios, we’ll code situations and decision points that lead our adventurers toward promise and away from peril.

Day 5: Team Racing - Need for Speed

Play together through the use of cloud variables on Scratch. Students will customize race tracks and invite their friends to compete in their own virtual stadiums.

Day 6: Obstacle Course

How do self-driving cars sense road signs and pedestrians? In today’s exploration of advanced conditionals, young learners will write functions for an autonomous vehicle as it swerves its way around town.

Day 7: Bug Hunt!

Making mistakes is key to learning which is why Day 7 allows students to embrace failure. In this garden adventure, find bugs and help them fix their buggy features through programming.

Day 8: Hero Origin Stories

Now that we’ve seen lots of different scenes and plots, we get connected with our roots and imagine ourselves as heroes with our own origin stories. Then, we’ll see how AI can help us dream settings and characters to colorize our vision.

Day 9: World Building

What’s a world without music? Today, we craft soundscapes to implement into a class-wide platform game, and each one of us will produce our own AI song!

Day 10: Team Hack-A-Thon

During the team hackathon, each student takes ownership of a portion of the platform game to customize as we tweak the rewards, penalties, sounds, and motion of this interactive adventure.

Team

Instructors

Education

MIT, Master’s in Computer Science (HCI)
MIT, Bachelor’s in Computer Engineering

Teaching

Erica focuses on Human-Computer Interaction, computer vision, and image processing. She’s previously explored how we can use machine learning to enable creativity.

Erica Yuen

Instructor MS, MIT

Education

Stanford, Bachelor’s in Computational Physics and Data Science

Research

Designed sustainable lab materials and curriculum as an educational fellow in partnership with the Ghanian Educational Service; astrophysics research assistant at SLAC, Caltech, and NASA’s Jet Propulsion Laboratory developing precise image resolution for ground-based telescopes

Emmy Li

Instructor

Education

MIT, Master’s in Computer Science
MIT, Bachelor’s in Computer Science and Electrical Engineering,
Minor in Mechanical Engineering

Research

Kayla’s expertise lies in Robotics—she previously worked on autonomous driving at Cruise and robotics software at Vecna Robotics. She also researched methods for factory line operators to effectively work alongside robots.

Teaching

Kayla’s expertise lies in Robotics—she previously worked on autonomous driving at Cruise and robotics software at Vecna Robotics. She also researched methods for factory line operators to effectively work alongside robots.

Kayla Holman

Curriculum Developer, Instructor

Education

I am a rising senior at Yale studying Physics and CS.

Research

I am currently working at a lab researching Quantum Neural Networks, searching for biological applications. I currently live between New Haven, New York, and Ireland travel permitting. I have recently gotten into guitar and have been trying to learn John Mayer's new song Last Train Home.

Aidan Donaghey

Instructor

Education

I'm a master's student at Brown University studying Data Science. I'm from Geneva, Switzerland.

Research

I am interested in how data science and AI can be used to tackle global problems like poverty and climate change. I'm also interested in ethical challenges of AI and how they can be mitigated. I love listening to music, trying new foods, and hanging out with friends. Excited to meet you!

Drew Solomon

Instructor

Education

MIT, Master’s in Computer Science (AI)
MIT, Bachelor's in Computer Science and Math
MIT, Teaching License

Research

Studying economic disparities in online education, diagnosing dementia with machine learning, creating AI-generated images, and improving recommendation engines.

Teaching

Daniela created and taught an Artificial Intelligence and Society course at an international school in Rome. She’s taught math + computer science to students from kindergarten through college around the world. 

DANIELA GANELIN

Director of Curriculum MS, MIT

Education

I studied math and CS at Stanford and just graduated this past winter!

Research

I love thinking about mathematical and algorithmic puzzles. My studies and research are centered around the theoretical side of Computer Science. In particular, I like complexity theory which is the study of how hard certain problems are, and algorithmic game theory which is the study of how to play all sorts of games optimally. I also really enjoy learning about AI systems, and especially their applications to solving real world problems (and also playing useless games). In my spare time I like to run, cook, read and listen to / play / compose music.

Harry Sha

Instructor

Education

I graduated from Brown University with a Bachelor’s of Science in Computer Science in May 2021.

Research

I'm excited about the wide applications of AI to all sorts of fields, from finance to healthcare/biology. In particular, my senior project back in college was training a deep learning model to predict antibiotic resistance based on bacterial genetic information! Outside of school and work, I also like to bake, sew, play video games, and go for runs! I'm currently training for my first 10k sometime in the late summer or early fall.

Giselle Garcia

Instructor

Education

I'm a rising junior at Columbia studying Electrical Engineering.

Research

I'm passionate about applying machine learning to solve biomedical problems and exposing students to computer science concepts. This summer I'm doing research in a biophotonics lab working on deep learning models to identify images with suspicious features for breast cancer application. Outside of the lab, I like to try Margherita pizzas and explore New York City!

Margherita Firenze

Instructor

Education

I just graduated from MIT with degrees in Mathematics and Music.

Research

I'm interested in the intersection between music and technology, and have been using computational and AI/ML methods for analyzing medieval music. Outside of academics, I am an avid jazz composer and musician, and enjoy listening to all sorts of music! I also enjoy reading, running, chess, and Rubik's Cube solving.

Kevin Costello

Instructor

Education

I'm a graduate student at UCLA doing a PhD in Bioinformatics. Before that, I did my undergrad at UC Berkeley where I studied Computer Science and Cognitive Science.

Research

My current project is on making a new method which uses machine learning to take really large genetic data and reduce it to a smaller dimension to be analyzed. Existing methods introduce a lot of distortion during this process, so I am working to minimize that. In my free time, I like to bake, hike, and play board games with friends. I'm also learning to make boba at home!

Serena Hughes

Instructor

Education

I'm a PhD Student at Stanford studying Bioengineering.

Research

I work on 3D printing technologies, especially on how to develop strategies to enhance the function and scale of bioprinted cardiac and vascular tissues to accelerate on-demand organ printing. I use AI to solve and control robotics (planning paths, point distribution, and kinematics) that are developed for new manufacturing methods of 3D printing. I have lived in 3 different countries (India, US, Belgium) on all different continents, and attended 11 schools. I also weightlift, swim, and play guitar, and write short blog posts (You can find me at https://1sohamsinha.wixsite.com/sohamsinha).

Soham Sinha

Instructor

Testimonials

What Our Students Say

Ally Bush

Seattle, Washington

“The Inspirit AI camp was incredible! I not only learned about coding, but also formed connections with three project teammates from around the world. Attending this camp helped me realize my passion for STEM and AI, and my teachers happily supplied resources for me to pursue it further!”

Amanya Sahney

Mumbai. India

“In this program, I was intrigued by all the applications AI has to offer. I searched up more on these particular topics and am considering pursuing computer science further.”

Jeremy Lu

Saratoga, CA

“I was lucky enough to participate in one of Insipirit’s AI camps and learn concepts such as reinforcement learning, neural networks, and more in workshops and everyday lessons. I later applied these concepts in my own project.”

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