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TECH 26 — Introduction to Data Visualization with Python and AI for Business

Quarter: Winter
Instructor(s): Anja Lee
Duration: 5 weeks
Location: Online
Date(s): Jan 29—Feb 26
Class Recording Available: Yes
Class Meeting Day: Thursdays
Grade Restriction: No letter grade
Class Meeting Time: 6:00—7:50 pm (PT)
Tuition: $430
   
Refund Deadline: Jan 31
 
Unit(s): 1
   
Enrollment Limit: 30
  
Status: Open
 
Quarter: Winter
Day: Thursdays
Duration: 5 weeks
Time: 6:00—7:50 pm (PT)
Date(s): Jan 29—Feb 26
Unit(s): 1
Location: Online
 
Tuition: $430
 
Refund Deadline: Jan 31
 
Instructor(s): Anja Lee
 
Grade Restriction: No letter grade
 
Enrollment Limit: 30
 
Recording Available: Yes
 
Status: Open
 
Data visualization is evolving beyond static charts into dynamic storytelling that drives insight and action. This course introduces the fundamentals of data visualization using Python and applied AI tools to help professionals think critically and communicate clearly in an AI-shaped world.

Students will learn to use Pandas for data preparation and Matplotlib/Seaborn/Plotly for clear, publication-ready visuals, while exploring how AI tools such as ChatGPT, Gemini, and Claude can support data exploration, bias detection, and narrative refinement. Through hands-on exercises, learners will practice using AI as a creative collaborator and develop the judgment to know when human reasoning should lead.

By the end of the course, students will have built a portfolio of Python notebooks that transform real-world data into visual stories that inform, persuade, and inspire.

Basic coding experience is preferred but not required, as students will be editing existing code. This course relies on the use of an external, third-party tool that is not managed or supported by Stanford. Students must purchase their own tool subscriptions and can expect to spend $25-$100 per month. Please see the course syllabus for more details.

ANJA LEE
Data Product Professional and Executive Coach

Anja Lee is a product strategist and educator with over 20 years of experience transforming data into impactful products and insights. She has led analytics, machine learning, and AI initiatives at Fortune 500 firms and startups in gaming, finance, and ad tech and previously developed software for neuroscience research. She received an MS in computer science from NYU’s Courant Institute and is an ICF-credentialed coach.

Textbooks for this course:

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