Artificial Intelligence (AI) technology is becoming increasingly important in the modern world. AI has the potential to transform various fields and revolutionize several industries, ranging from healthcare, transportation, finance, education, marketing and entertainment.

Today, understanding AI isn’t just for programmers - it’s for anyone who wants to be prepared for tomorrow. 

San Jose State University’s one-week summer program will focus on the basic concepts of AI, machine learning, and deep learning. The participants will have the unique opportunity:

• To learn and apply the fundamental techniques to train a deep learning model;
• To gain hands-on experience to use the NVIDIA online labs (Jupyter notebooks); and 
• To earn a NVIDIA certificate, upon successfully passing the final assessment

Spend a week in summer to explore interests and opportunities in advancing technology, boost college applications, and connect with like-minded peers. Don’t miss the chance to dive into AI and gain a competitive edge!

Program Date: 6/23/25 (Monday)- 6/27/25 (Friday)
Time: 09:00 a.m.- 12:00 p.m.
Location: Los Altos High School, 201 Almond Avenue, Los Altos, CA 94022
Instructor: Ann Marie Kenitzer,  Bricolagrow LLC Founder & CEO

Ann Marie is a proven growth strategist, business transformer, and technology innovation leader with deep roots in the technology sector, from corporate to early-stage ventures.  As a NVIDIA-certified instructor in the NVIDIA Educator Program, she brings a unique blend of deep industry knowledge, real-world tech leadership plus strategic insight to her role as an instructor, with an emphasis to help the next generation of innovators understand and apply the fundamentals of AI/ML.    

Ann Marie founded Bricolagrow LLC, providing transformation and operations expertise and serving as an advisor and mentor to over 25 startups across diverse industries—including AI, Technology, EdTech, HealthTech, ClimateTech, and consumer products. She guides founders to root out growth roadblocks, refine business models, align financials and elevate storytelling for investor readiness. Previously in the corporate arena, Ann Marie was a Business GM and VP/Director of Strategy and Operations at Intel Corporation and Flex Ltd. with extensive expertise across product management, engineering, marketing, strategic planning, business operations, and supply chain. She has incubated a Fortune 100 internal startup for customizable IoT products, led growth strategy for a billion-dollar datacenter business unit, executed global business and IT transformation, led strategic transitions in the semiconductor ecosystem, and built groundbreaking technology partnerships.

Learning Outcomes

• Understand history of AI and various AI applications;
• Acquire fundamental concepts of AI, machine learning, deep learning, and generative AI;
• Understand the differences between supervised learning, unsupervised learning, and reinforcement learning;
• Acquire the fundamental techniques and tools required to train a deep learning model (regression line, loss curve, activation functions, classification, convolutional neural networks, natural language processing);
• Gain experience with common deep learning data types and model architectures;
• Enhance datasets through data augmentation to improve model accuracy;
• Leverage transfer learning between models to achieve efficient results with less data and computation; and
• Gain an opportunity to earn a potential NVIDIA certificate upon passing the assessment exam criteria.

Program Content

Prerequisites

9th - 12th Graders 

An understanding of fundamental programming concepts in Python 3, such as functions, loops, dictionaries, and arrays; familiarity with Pandas data structures; and an understanding of how to compute a regression line.

Suggested materials to satisfy prerequisites: Python Beginner’s Guide, or take a free online Python beginner class per your preference.  You will have trouble following the class or taking full advantage of the class without Python knowledge. Statistics background is preferred.  Understanding of regression model evaluation metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE) will enhance your learning experience.

Technologies: PyTorch, Pandas

Assessment Type: Skills-based coding assessments evaluate students’ ability to train a deep learning model to high accuracy.

SJSU Completion Certificate: Students attending classes (80% attendance) and completing online homework assignments will receive a San Jose State University completion certificate.   

NVIDIA Certificate: Upon satisfying the assessment exam passing criteria, participants will receive an NVIDIA Deep Learning Institute (DLI) certificate to recognize their subject matter competency.

Hardware Requirements: Desktop or laptop computer capable of running the latest version of Chrome or Firefox. 

Registration and Payment

• Registration deadline: June 16, 2025 or when the class reaches capacity. If the class is full, you will be put on the waitlist.
• A final email confirmation will be sent to participants on June 20, 2025. Please check your email on that day for detailed information about the arrangements. 
• The camp fee is $999. Please submit this registration form and you will receive an email notification with a payment link.
• Camp fees are non-refundable. However, if the camp is cancelled, the fees will be fully refunded. 

Contact info

Email: pace@sjsu.edu