TECH 17 — Demystifying Machine Learning and Generative AI
Quarter: Fall
Instructor(s): Gaurav Khanna
Date(s): Oct 1—Nov 19
Class Recording Available: Yes
Class Meeting Day: Thursdays
Grade Restriction: No letter grade
Class Meeting Time: 7:00—8:50 pm (PT)
Tuition: $650
Refund Deadline: Oct 3
Unit(s): 1
Status: Registration opens Aug 17, 8:30 am (PT)
Quarter: Fall
Day: Thursdays
Duration: 8 weeks
Time: 7:00—8:50 pm (PT)
Date(s): Oct 1—Nov 19
Unit(s): 1
Tuition: $650
Refund Deadline: Oct 3
Instructor(s): Gaurav Khanna
Grade Restriction: No letter grade
Recording Available: Yes
Status: Registration opens Aug 17, 8:30 am (PT)
Artificial Intelligence is filled with technical terms like “parameters,” “cost functions,” and “context window.” These words can seem like things only a machine would understand. Yet AI can be reduced to a handful of foundational principles and concepts that anyone can grasp. This course offers a comprehensive, non-technical introduction to machine learning, deep learning, and generative AI. Through lectures, interactive discussions, and real-world examples, students will explore the mechanics of AI systems without advanced math or coding. The course begins with regression algorithms—models that capture relationships between variables—and builds toward neural networks and deep learning, then concludes with the foundations of today’s generative AI platforms such as ChatGPT and Claude. We will also examine exciting new areas such as agentic AI and AI safety, providing a framework to understand where these technologies may be headed. By the end, students will be able to meaningfully collaborate with AI practitioners, evaluate the evolving AI landscape, and gain context for career exploration.
Knowledge of algebra is recommended; no coding experience is required. This course will demonstrate third-party AI tools that are not managed or supported by Stanford. Students can explore these tools on their own if they like, but use is optional. Many tools offer free versions or trials; paid subscriptions, if chosen, typically range from $25–$100 per month. See the syllabus for more details.
GAURAV KHANNA
AI Executive, Cisco Systems
Gaurav Khanna has more than 25 years of experience in technology and entrepreneurship. He has led efforts to automate business workflows using machine learning and deep learning techniques. His work has focused on using LLMs and generative AI to transform how users interact with sales acceleration platforms. He works with customers to shape their overall AI strategy and drive business transformation and is actively fostering strategic partnerships within Cisco and the broader industry. Khanna received a PhD in materials science and engineering from Stanford. Textbooks for this course:
There are no required textbooks; however, some fee-based online readings may be assigned.