https://www.inspiritai.com/inperson
The 10-session program exposes students to fundamental AI concepts, and guides them to build a socially impactful AI project. The curriculum, designed and taught by Stanford PhD and Masters students, encourages experiential, project-based learning. Students attend case discussions and interactive demos to learn about real-world considerations in deploying AI models.
To learn more about our live online program click here.
APPLY NOW
Curriculum.jpeg
PREREQUISITES
No prior programming or CS background required.
Students with prior programming or CS experience may join the advanced cohort.
ADMISSIONS
Applications now open for Live Online Winter Break 2020/2021 and Spring Semester 2021!
Applications are processed on a rolling basis. Students will hear back within 7 days of applying.
PROGRAM FEES
Click on the respective locations below for information on program fees and deadlines. (Coming soon in Summer 2021)
If AI Scholars is not offered in your location, consider applying to our live online program!
Palo Alto • San Francisco • Boston • Chicago • New York • India • Singapore • Dubai
Program Outline
PRE-CAMP PREPARATION
Students will receive preparation materials in advance to help them get the most out of the camp once they arrive. This will include a Python and AI basics video series, and other readings.
PROGRAM STRUCTURE
In the first week, we will focus on building up foundational AI knowledge and skills that students will implement on a group project in the second week.
BEGINNER AND ADVANCED COHORT
Separate cohorts will be offered for students with no programming experience and those with prior experience. The advanced cohort will move at a faster pace and be more coding-intensive.
WEEK 1
In week 1 students will explore applications, foundational AI concepts, and develop AI programming skills.
Frame 7 (1).png
APPLICATIONS
We will start each day with a session on applications. E.g. “How does Alexa work?”, “How can AI be applied at Hospitals?”, “How can AI improve the environment?”

CONCEPTUAL INTUITION
We will cover the conceptual intuition and some math behind important Machine Learning algorithms. Examples include Neural Networks, Decision Trees, Logistic Regression
Frame 9 (3).png
AI PROGRAMMING SKILLS
We will guide students to implement mini-projects using Python. E.g. Classifying cells as cancerous or health, classifying restaurant reviews as positive or negative