Learn AI in Four Weeks

Nova AI Fundamentals for Middle School Students

Our course covers everything from AI fundamentals and algorithms to essential computer science skills, guiding middle school students in building their own AI projects. Through live, online classes led by Stanford, Harvard, and Yale alumni and students, participants gain hands-on experience and mentorship, creating a strong foundation in today’s most transformative technology.

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What's included?

The Nova AI Fundamentals course is an intensive course designed for advanced middle school students during the academic school year. Students go beyond the classroom to learn and apply the latest advancements in technology, guided by instructors at the forefront of innovation.

Five sessions, ten hours

Students can join our 2-hour small-group online classes and build AI projects. Classes typically meet once a week, with twice-weekly sessions in the final week, and maintain a 1:5 instructor-to-student ratio.

Stanford, Harvard, and Yale instructors

Our program has been developed by Stanford instructors with experience at leading companies like Facebook and OpenAI.

Project-based AI programming

Our curriculum is frequently updated to include the latest tech advancements (e.g., our curriculum includes a deep-dive in GenAI and AI agents )

Program costs are $490 USD, covering 10 hours of mentorship and all software expenses for hands-on activities.

Twelve start date options every year

We have a new program start date every month to provide students with the ability to join when they have the capacity to participate. Sessions are held twice a week, with the exact start time and meeting days depending on the batch. Here are some of our upcoming start dates for 2024 - 2025:

Nov 2, 2024

Dec 7, 2024

Jan 4, 2025

No programming or computer science experience needed. We simply ask for a genuine interest in learning to code!

Our mentors have experience at leading institutions and companies

We look beyond impressive work experience in our mentors—teaching expertise and a genuine passion for AI are essential. With an acceptance rate of around 10% for our AI Fundamentals course, only the most dedicated make the cut. Of course, experience at top-tier AI companies is always a plus.

Hear from some of your exceptional mentors

Meera

MS Computer Science, Stanford University
BS Computer Science, Stanford University

"Starting early opens up endless opportunities, giving students the foundational skills they need to navigate and innovate in the future. My time working on machine learning at Google and NVIDIA has given me a deep appreciation and expertise in machine learning and AI—what I believe to be the most transformative technology of our time. I'm passionate about teaching and have spent nearly five years mentoring secondary school students in this dynamic field, hoping they’ll continue to advance the frontiers of AI in their education and possibly their future careers."

Five session schedule

Over the course of one week, middle school students will learn the fundamentals of AI through small-group instruction and hands on projects.

Introduction to AI and Machine Learning

Session 1

1. Understanding AI: Overview of AI, machine learning, and deep learning.
2. How AI Learns: Introduction to training AI through data and pattern recognition.
3. AI in Daily Life: Exploration of AI applications, including NLP and computer vision.
4: Activity: Students text classification program that categorizes sentences (e.g., as “positive” or “negative” sentiment)t parameters such as the threshold for categorization, to set stricter or more lenient criteria for each category
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Teaching AI to Understand: Natural Language Processing

Session 2

1. Basics of NLP: Core NLP tasks like language translation and text generation.
2. How NLP Works: Tokenization and basic sentiment analysis.
3. Activity: Students will work enhance a chatbot framework and add a response function for specific keywords (e.g., triggering a greeting when “hello” is detected). Students will also adjust parameters, such as response delay or message length, to modify the chatbot's personality and response style
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Teaching AI to “See”: Computer Vision

Session 3

1. What is Computer Vision?: Introduction to image classification and object detection.
2. Understanding Images as Data: How computers analyze images through pixels.
3. Activity: Students will e image classifier that uses basic image data (such as color or shape). Students will add a function to include a new category (e.g., “red objects”) and adjust parameters like confidence level to control how certain the model needs to be before categorizing an image.

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The Brain Power Behind AI: Neural Networks

Session 4

1. Neural Network Basics: Explanation of layers and how data flows through them.
2. Applications of Neural Networks: How neural networks are used in NLP and computer vision.
3. Activity: Students will pre-builtetwork model, adding a simple activation function and tweaking learning rate parameters how slight adjustments impact the model’s training outcomes.
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Generative AI and the Future of AI Development

Session 5

1. Introduction to Generative AI: How AI can create new content, such as text, images, music, and even video. Overview of OpenAI’s Five Stages to AGI.
2. How Generative AI Works: Basics of how generative models learn patterns in data to produce new outputs. Introduction to key models (GANs, transformers).
3. Deep dive into AI Agents: Understand what AI agents are, how they operate autonomously, and their real-world applications.
4. Activity: Students will work with a text generation script, adding a function to introduce a new storyline or setting (e.g., “space adventure”). They will then adjust parameters like creativity an

Hear from our middle school students

Jess
"I loved this course! The classes were interactive and the my teacher was amazing"

Raj
"All the projects made learning computer science and AI fun and exciting!"

Anna
"I really liked it - I learned so much! I'm excited to do the month AI course next"

Brian
"I'm glad I did something productive over break. I also liked the other three students!"

Cassie
"I haven't programmed before so it was great to learn something so important"

Tom
"We learned really cool things - from coding to GenAI. I wanted to learn about AI so this was a great experience"

Priya
"I really loved my teacher Nancy - she was so good at explaining new concepts, and made her class fun"

Divya
I plan to apply the skills I've built here to do AI research and am excited to learn as much as I can about AI"

What's the difference between the Nova AI Fundamentals and the Accelerated program?

Nova AI Fundamentals has double the course time - 20 hours - as compared to Nova Accelerated AI Fundamentals 10 hours. Students in Nova Fundamentals have a more in-depth curriculum and build their own independent AI project at the end of the course. How do you know which one is the best for you?

Choose Nova AI Fundamentals if:

You can commit 4 hours of class time with ~1-2 hours of homework during the academic school year

You want to build an independent AI project from start to finish and grow your computer science skills.
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Choose Nova Accelerated AI Fundamentals if:

You can spend ~3 hours per day, including 2 hours of class time and 1 hour of homework, to the program over your break
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You want a intensive crash course on AI, with hands-on learning through coding daily AI projects
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What's next after this?

So much more- this is just the first small step in your CS and AI journey. We encourage students to keep building and exploring in the rapidly evolving field of AI. It's exciting to see how many students continue to expand on their projects after the program.

Based on performance and with instructor recommendation, a few students—typically in 8th grade and with previous computer science exposure— started conducting advanced AI research and began working on their own patentable projects through Nova Research and Nova Patent.

Still have questions?

Attend an Info Session