Introduction to Artificial Intelligence
SAT Score Range
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6 sessions
•
MA
RB
AB
+12
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🔥 5 spots left!
About
Learn how AI actually works under the hood! This series breaks down the mechanics of artificial intelligence - from how neural networks process information to how machine learning algorithms make decisions. We'll explore different AI architectures, understand training processes, and see how data flows through AI systems. Through interactive demos and visual examples, you'll gain a deep understanding of what's really happening when AI 'thinks' and learns.
Tutored by
I am a high schooler in Arizona as a junior certified in AI and AWS Cloud Computing and A student in AP CS Courses. I love computers and want to help others. I am also AWS AI Practionier certified and Cloud Practionier Certified, I enjoy vibe coding project, experimenting with linux distro's and AI projects.
✋ ATTENDANCE POLICY
You are free to attend/skip whichever sessions you want.
SESSION 4
16
Nov
SESSION 4
Artificial Intelligence
Artificial Intelligence
Sun 12:00 AM - 1:00 AM UTCNov 16, 12:00 AM - 1:00 AM UTC
AI for Coding & Problem Solving: Use AI as a coding assistant with tools like GitHub Copilot, ChatGPT, and Claude. Learn code generation, debugging techniques, error interpretation, and algorithm explanations. Discusses the balance between AI as a tutor vs doing homework for you. Includes live coding demos and hands-on practice with debugging exercises.
SESSION 5
23
Nov
SESSION 5
Artificial Intelligence
Artificial Intelligence
Sun 12:00 AM - 1:00 AM UTCNov 23, 12:00 AM - 1:00 AM UTC
How AI Models Are Built (Condensed): Understand the training process, fine-tuning, and transfer learning at a high level. Focus on why these concepts matter for users: how ChatGPT becomes specialized chatbots, why AI sometimes makes mistakes, and how bias enters AI systems. Less technical depth, more practical implications.
SESSION 6
30
Nov
SESSION 6
Artificial Intelligence
Artificial Intelligence
Sun 12:00 AM - 1:00 AM UTCNov 30, 12:00 AM - 1:00 AM UTC
AI Ethics, Future & AI Lab: Explore ethical considerations including privacy, deepfakes, misinformation, and AI safety. Discuss realistic views on job displacement and future developments (multimodal AI, agents, AGI basics). Hands-on AI Lab where students experiment with different AI tools and applications in class. Course wrap-up with key takeaways, continued learning resources, and Q&A.