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TECH 192 — A Crash Course in Artificial Intelligence (AI): Part II

Quarter: Winter
Instructor(s): Ronjon Nag
Duration: 5 weeks
Location: Online
Date(s): Feb 18—Mar 18
Class Recording Available: Yes
Class Meeting Day: Tuesdays
 
Class Meeting Time: 6:30—8:30 pm (PT)
Tuition: $410
   
Refund Deadline: Feb 20
 
Unit(s): 1
   
Status: Registration opens Dec 2, 8:30 am (PT)
 
Quarter: Winter
Day: Tuesdays
Duration: 5 weeks
Time: 6:30—8:30 pm (PT)
Date(s): Feb 18—Mar 18
Unit(s): 1
Location: Online
 
Tuition: $410
 
Refund Deadline: Feb 20
 
Instructor(s): Ronjon Nag
 
Recording Available: Yes
 
Status: Registration opens Dec 2, 8:30 am (PT)
 
You can leverage the power of AI in biology, business, and beyond—without needing to code. This advanced course is a continuation of TECH 152: "A Crash Course in Artificial Intelligence (AI): Part I," focusing on practical applications that anyone can master. Students will start with prompt engineering, where you'll learn to design and refine effective commands in plain English. Next, we'll explore specialized platforms for creating AI applications, including custom AI personas tailored to your needs. As the course progresses, you'll gain hands-on experience training and fine-tuning large language models (LLMs), navigating the complexities of model selection and utilization. Expert guest speakers will provide real-world insights into building and deploying AI systems. While some code exploration is included, the focus remains on accessible drag-and-drop tools.

By the end of this course, students will have:

  • Learned essential AI tools
  • Gained the skills to train and fine-tune AI models on accessible platforms
  • Enhanced their personal and professional productivity with AI-driven solutions

This is the second course in a two-part sequence. Students may enroll in Part II without having enrolled in Part I. A brief review of concepts covered in "A Crash Course in Artificial Intelligence (AI): Part I" will be offered at the beginning of the course to ensure all students are up to speed. Familiarity with AI concepts like neural networks is helpful but not required.

RONJON NAG
Adjunct Professor in Genetics, Stanford Medicine

Ronjon Nag has been building AI systems for 40 years and co-founded or advised companies sold to Motorola, RIM/BlackBerry, and Apple. He is a venture capitalist and president of the R42 Group, which invests in and creates AI and longevity companies. He teaches AI, genes, ethics, and venture capital at Stanford Medicine and is a visiting fellow at the Stanford Center for the Study of Language and Information. He became a Stanford Interdisciplinary Distinguished Careers Institute Fellow in 2016. He received a PhD from Cambridge, an MS from MIT, and a BSc from Birmingham, United Kingdom. He has also received the MIT Great Dome Award, the IET Mountbatten Medal, the $1 million Verizon Powerful Answers Award, the 2021 IEEE-SCV Outstanding Engineer Award, and the 2023 CogX AI Lifetime Achievement Award and is the 2024 inductee in the Silicon Valley Engineering Hall of Fame. He is part owner of some 100 AI and biotech startups.

Textbooks for this course:

There are no required textbooks; however, some fee-based online readings may be assigned.