Practical Applications of AI Technology

Artificial Intelligence is a rapidly evolving field that integrates mathematics, computer science, and engineering to create systems capable of learning, reasoning, and decision-making. This course introduces high school students to the foundations, implementation and applications of AI, from the algorithms behind TikTok recommendations and ChatGPT to innovations in self-driving cars, finance, robotics, and healthcare. Emphasizing both conceptual understanding and practical experimentation, the program covers supervised and unsupervised learning, natural language processing, deep learning and large Language models (ChatGPT). Students will engage in guided assignments, Hackathons, interactive demonstrations, and project-based learning, gaining the skills to design creative AI solutions while critically examining the ethical questions surrounding this transformative technology.

Learning Outcomes

1. Proficiency in Python for AI: Gain hands-on experience in Python programming with a focus on artificial intelligence and machine learning, including practice with core libraries such as Pandas, PyTorch, TensorFlow, and Hugging Face.
2. Foundations of Artificial Intelligence: Understand key AI concepts including supervised and unsupervised learning, computer vision, natural language processing, and deep learning.
3. Hands-On AI Applications: Build and deploy AI-driven web applications such as object detection tools, financial prediction models, and AI agents (like ChatGPT5 Agent mode) for tasks like email automation.
4. AI Across Industries: Explore real-world case studies highlighting how AI transforms healthcare, finance, robotics, and social media, and connect theory with practice through interactive examples.
5. Experiential Learning and Collaboration: Participate in an ethics-focused hackathon, engage in case study challenges, and learn from guest lectures by industry experts (e.g., Google, Toast, Amazon). Work in teams to design, present, and defend an innovative AI project that demonstrates technical understanding and creativity.

Tangible Outcomes

• Team Project Demo: A fully functional AI web-based application, such as an object detection tool, financial prediction dashboard, or chatbot/AI agent.
• Coding Portfolio: Python notebooks and scripts showcasing proficiency with libraries such as Pandas, PyTorch, TensorFlow, and Hugging Face, organized and shared through GitHub and Kaggle.
• Case Study Competition: Written analyses and presentations on real-world AI applications in healthcare, finance, robotics, and social media.
• Hackathon Prototype: A rapid AI prototype designed and presented during the in-class hackathon, emphasizing creativity and teamwork.
• Certificates & Badges: Official recognition of course completion, along with optional digital badges such as GitHub project contributions, Kaggle profiles, and IBM Data Science certification.

Hands-on Activities

• Hands-On Labs: Guided coding sessions where students build AI models and Deploy them on Kaggle platform
• Simulations & Demos: Live demonstrations of AI in action (e.g., self-driving car simulations, financial prediction models, and real-time image recognition).
• Case Study Challenges: Team-based analysis of AI applications in healthcare, finance, robotics, and social media, culminating in short presentations.
• AI Hackathon: A fast-paced group challenge where students prototype an AI solution to a real-world problem.
• Guest Lectures: Talks from industry professionals and researchers (e.g., experts from Google, Toast, and Dartmouth CPHAI)

Guest Speakers

• Hareeshwar Karthikeyan, AI Engineer at Toast
• Ganesh Rohit N. , Software Engineer at Google
• Ansh Gupta , Founding AI Engineer at Anything

Field Trip

DALI Lab at Dartmouth College

Information is subject to change as instructors finalize course content and syllabi.