Learn AI in Four Weeks

Nova AI Fundamentals for Middle School Students

The Nova AI Fundamentals course is a 10-hour course designed for middle school students. Through small-group online classes, students will work with our expert instructors from top universities.

Why is it important to learn about AI?

Having a foundational knowlege of AI is an essential skill

The earlier you develop key skills in AI, the better positioned you'll be to create meaningful projects that make a difference in the world.

AI allows you to tackle Real-World Challenges

AI is transforming how we address major global issues like healthcare and climate change. Through your project, you can contribute to innovative and impactful solutions

Learning AI can help you Stand Out in College Applications

Colleges value individuals who are passionate about helping communities. Technology often plays a key role in creating impactful solutions, so start exploring the many ways you can contribute.

How Nova AI Fundamentals works

Learn for ten hours over one month

Students can join our 2.5-hour small-group online classes. Classes typically meet once a week.

Small group classes with Stanford Instructors

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

12 cohort options and no prerequisites!

Our curriculum is frequently updated to include the latest tech advancements.

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

Taught by former Stanford instructors

All our instructors are BS, MS, or PhD candidates or graduates at Stanford with extensive teaching experience in computer science.

Beyond that, 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.

Twelve start date options every year

We have a new program start date every month: January, February, March, April, May, June, July, August, September, October, November, December. We want to provide students with the ability to join when they have the capacity to participate. No programming or computer science experience needed. We simply ask for a genuine interest in learning about computer science and artificial intelligence!

Sample Session Breakdown

Session 1: Introduction to AI and ML and Exploratory Data Analysis

This session provides a foundational understanding of Artificial Intelligence (AI) and Machine Learning (ML), covering key concepts, applications, and real-world impact. Participants will explore the role of data in AI and learn how to conduct Exploratory Data Analysis (EDA) to uncover patterns, trends, and insights essential for building effective models.

Session 2: Data, Regression Problems, Linear Regression

This session introduces regression techniques used for predictive modeling, with a focus on Linear Regression. Participants will learn how to handle datasets, identify regression problems, and apply statistical methods to model relationships between variables. Hands-on exercises will reinforce key concepts through practical applications.

Session 3: Classification Problems, Logistic Regression

This session delves into classification problems and explores Logistic Regression as a powerful tool for decision-making. Through case studies spanning healthcare, law, and business, participants will gain insight into how classification models are used to analyze and predict categorical outcomes.

Session 4: Neural Networks and Convolutional Neural Networks (CNNs)

This session explores the fundamentals of Neural Networks and Convolutional Neural Networks (CNNs), emphasizing their role in modern AI applications. Participants will learn how CNNs power image recognition, medical diagnostics, and automation, gaining hands-on experience with deep learning architectures and real-world case studies.

What does a session look like

Students will engage with mentors through lectures, projects, and discussions truly grasp concept and how it applies to them.

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."

Nova Research Mentor

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 students

Richard

Nova AI Fundamentals

Phoenix, USA

Through Nova Research, I learned how to design experiments and interpret results in ways that actually matter. I’m proud of the skills I’ve developed to tackle real-world challenges.

Anna

Nova AI Fundamentals

California, USA

Maya was amazing - she knew a lot about AI and convinced me that electrical engineering was the path I wanted to explore next!

Keshav

Nova AI Fundamentals

California, USA

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

Sia

Nova AI Fundamentals

Texas, USA

All the hands-on projects made learning computer science and AI fun and exciting

Taylor

Nova Research

Arizona, USA

The mentorship at Nova Research is unmatched. My mentor took the time to challenge my ideas, refine my methodology, and help me develop as both a thinker and a scientist.

Priya

Nova AI Fundamentals

Arizona, USA

I'm glad I did something productive over break! I also liked my cohort

Elena

Nova Research

Texas, USA

I’ve always loved problem-solving, and AI opened up a whole new way to approach challenges.

Jessica

Nova Research

New Jersey, USA

My mentor at Nova Research was more than just a guide—they were a true collaborator. Their expertise and encouragement pushed me to think deeper, work smarter, and grow as a researcher.

Brianna

Nova AI Fundamentals

Illinois, USA

Learning AI at Nova helped me see how it connects with my passion for healthcare. I now understand how AI can be used for medical diagnostics and research.

Kate

Nova AI Fundamentals

Washington, USA

Learning AI at Nova helped me see connections to fields I never expected—like environmental science, policy, and social impact.

Raj

Nova AI Fundamentals

Texas, USA

I really liked it - I learned so much! I'm excited to do research next

Cassie

Nova AI Fundamentals

New York, USA

AI is changing the world, and Nova helped me understand how I can be part of that change. Now, I want to explore AI in environmental science!

Divya

Nova AI Fundamentals

New York, USA

I used to think AI was just for engineers, but Nova showed me how AI intersects with business, law, and even social justice.

Bella

Nova Research

Rhode Island, USA

My mentor went above and beyond, providing personalized feedback, thoughtful discussions, and invaluable career advice. Their passion for research was contagious.

Druv

Nova Patent

New York, USA

Despite not having a programming background, Nova Patent provided enough instruction, support, and an incredible team to help me succeed. I loved working on the app design and I felt that I was truly contributing to something meaningful.

Jess

Nova AI Fundamentals

Washington, USA

I thought I needed a strong programming background to understand AI, but Nova’s structured approach made it easy to learn, no matter my starting point.

Grace

Nova Patent

Washington, USA

I never imagined I’d be working on an app that people might actually want and even pay for as a student. Thanks to my team and mentor, I learned how to refine my ideas and transform them into something truly impactful