From Department of Mathematics at UTSA
Jump to navigation Jump to search

Sociocultural Foundations of Mathematics, Data Science, and Computing- MDC1213

Catalog entry

Prerequisite: None.

Content: This introductory survey course for freshmen aims to explore the connections between mathematics, data science, and artificial intelligence, with an emphasis on their roles in shaping and understanding human culture and experience. Students will be guided through a series of 30 lessons that delve into the ways these fields intersect with ideas, values, beliefs, and other cultural aspects, fostering aesthetic and intellectual creation. Throughout the course, students will have access to the GPT-4 language model to assist with content generation and idea exploration.

This course is intended to be part of the core curriculum in the area “Language, Philosophy and Culture (040)” (3 semester credit hours). Courses in this category focus on how ideas, values, beliefs, and other aspects of culture express and affect human experience. This requirement involves the exploration of ideas that foster aesthetic and intellectual creation in order to understand the human condition across cultures.

Lesson Overview

Through these lessons, students will gain a foundational understanding of the intersections between mathematics, data science, and artificial intelligence, as well as their impact on the human experience across cultures. By leveraging GPT-4 for content generation and idea exploration, students will develop the skills necessary to engage with these fields in a culturally sensitive and ethically responsible manner.

  1. Introduction to Mathematics, Data Science, and Artificial Intelligence
  2. The Historical Evolution of Mathematics in Cultural Context
  3. How Data Science Has Shaped Society and Culture
  4. The Role of Artificial Intelligence in Understanding Human Behavior
  5. The Language of Mathematics: Symbols, Expressions, and Equations
  6. The Art of Problem Solving: Creativity in Mathematics
  7. Statistics and Probability: Interpreting Data and Predicting Outcomes
  8. Cultural Bias in Data Collection and Interpretation
  9. Machine Learning and Pattern Recognition in AI
  10. Ethical Considerations in Data Science and AI
  11. Mathematics and Art: Geometry, Proportion, and Symmetry
  12. The Golden Ratio and Fibonacci Sequence in Nature and Culture
  13. Information Theory: Quantifying Cultural Transmission
  14. Graph Theory and Social Network Analysis
  15. AI in Language and Communication: NLP and GPT-4
  16. The Impact of AI on Employment and the Future of Work
  17. Game Theory: Strategic Decision Making in Cultural Context
  18. Fractals, Chaos Theory, and Cultural Complexity
  19. Music, Mathematics, and AI: A Harmonious Intersection
  20. AI and Literature: Text Analysis, Generation, and Critique
  21. Mathematical Models in Economics and Social Sciences
  22. Big Data and Privacy: Balancing Utility and Ethics
  23. AI in Healthcare: Improving Outcomes and Reducing Disparities
  24. Climate Change, Sustainability, and Mathematical Modeling
  25. The Mathematics of Democracy: Voting Systems and Fair Representation
  26. Bias and Fairness in AI: Challenges and Solutions
  27. The Role of AI in Mental Health and Emotional Well-being
  28. AI and the Creative Arts: Exploring New Frontiers
  29. The Future of AI: Possibilities, Pitfalls, and Predictions
  30. Final Project: Applying Mathematics, Data Science, and AI to Cultural Analysis