Difference between revisions of "MDC1213"
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| − | = Foundations of Mathematics, Data Science, and | + | == 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 == | == Lesson Overview == | ||
| Line 7: | Line 13: | ||
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. | 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. | ||
| − | # Introduction to Mathematics, Data Science, and Artificial Intelligence | + | # [[Introduction to Mathematics, Data Science, and Artificial Intelligence]] |
| − | # The Historical Evolution of Mathematics in Cultural Context | + | # [[The Historical Evolution of Mathematics in Cultural Context]] |
| − | # How Data Science Has Shaped Society and Culture | + | # [[How Data Science Has Shaped Society and Culture]] |
| − | # The Role of Artificial Intelligence in Understanding Human Behavior | + | # [[The Role of Artificial Intelligence in Understanding Human Behavior]] |
| − | # The Language of Mathematics: Symbols, Expressions, and Equations | + | # [[The Language of Mathematics: Symbols, Expressions, and Equations]] |
| − | # The Art of Problem Solving: Creativity in Mathematics | + | # [[The Art of Problem Solving: Creativity in Mathematics]] |
| − | # Statistics and Probability: Interpreting Data and Predicting Outcomes | + | # [[Statistics and Probability: Interpreting Data and Predicting Outcomes]] |
| − | # Cultural Bias in Data Collection and Interpretation | + | # [[Cultural Bias in Data Collection and Interpretation]] |
| − | # Machine Learning and Pattern Recognition in AI | + | # [[Machine Learning and Pattern Recognition in AI]] |
| − | # Ethical Considerations in Data Science and AI | + | # [[Ethical Considerations in Data Science and AI]] |
| − | # Mathematics and Art: Geometry, Proportion, and Symmetry | + | # [[Mathematics and Art: Geometry, Proportion, and Symmetry]] |
| − | # The Golden Ratio and Fibonacci Sequence in Nature and Culture | + | # [[The Golden Ratio and Fibonacci Sequence in Nature and Culture]] |
| − | # Information Theory: Quantifying Cultural Transmission | + | # [[Information Theory: Quantifying Cultural Transmission]] |
| − | # Graph Theory and Social Network Analysis | + | # [[Graph Theory and Social Network Analysis]] |
| − | # | + | # [[AI in Language and Communication: NLP and GPT-4]] |
| − | # The Impact of AI on Employment and the Future of Work | + | # [[The Impact of AI on Employment and the Future of Work]] |
| − | # Game Theory: Strategic Decision Making in Cultural Context | + | # [[Game Theory: Strategic Decision Making in Cultural Context]] |
| − | # Fractals, Chaos Theory, and Cultural Complexity | + | # [[Fractals, Chaos Theory, and Cultural Complexity]] |
| − | # Music, Mathematics, and AI: A Harmonious Intersection | + | # [[Music, Mathematics, and AI: A Harmonious Intersection]] |
| − | # AI and Literature: Text Analysis, Generation, and Critique | + | # [[AI and Literature: Text Analysis, Generation, and Critique]] |
| − | # Mathematical Models in Economics and Social Sciences | + | # [[Mathematical Models in Economics and Social Sciences]] |
| − | # Big Data and Privacy: Balancing Utility and Ethics | + | # [[Big Data and Privacy: Balancing Utility and Ethics]] |
| − | # AI in Healthcare: Improving Outcomes and Reducing Disparities | + | # [[AI in Healthcare: Improving Outcomes and Reducing Disparities]] |
| − | # Climate Change, Sustainability, and Mathematical Modeling | + | # [[Climate Change, Sustainability, and Mathematical Modeling]] |
| − | # The Mathematics of Democracy: Voting Systems and Fair Representation | + | # [[The Mathematics of Democracy: Voting Systems and Fair Representation]] |
| − | # Bias and Fairness in AI: Challenges and Solutions | + | # [[Bias and Fairness in AI: Challenges and Solutions]] |
| − | # The Role of AI in Mental Health and Emotional Well-being | + | # [[The Role of AI in Mental Health and Emotional Well-being]] |
| − | # AI and the Creative Arts: Exploring New Frontiers | + | # [[AI and the Creative Arts: Exploring New Frontiers]] |
| − | # The Future of AI: Possibilities, Pitfalls, and Predictions | + | # [[The Future of AI: Possibilities, Pitfalls, and Predictions]] |
| − | # Final Project: Applying Mathematics, Data Science, and AI to Cultural Analysis | + | # [[Final Project: Applying Mathematics, Data Science, and AI to Cultural Analysis]] |
Latest revision as of 15:22, 26 April 2023
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.
- Introduction to Mathematics, Data Science, and Artificial Intelligence
- The Historical Evolution of Mathematics in Cultural Context
- How Data Science Has Shaped Society and Culture
- The Role of Artificial Intelligence in Understanding Human Behavior
- The Language of Mathematics: Symbols, Expressions, and Equations
- The Art of Problem Solving: Creativity in Mathematics
- Statistics and Probability: Interpreting Data and Predicting Outcomes
- Cultural Bias in Data Collection and Interpretation
- Machine Learning and Pattern Recognition in AI
- Ethical Considerations in Data Science and AI
- Mathematics and Art: Geometry, Proportion, and Symmetry
- The Golden Ratio and Fibonacci Sequence in Nature and Culture
- Information Theory: Quantifying Cultural Transmission
- Graph Theory and Social Network Analysis
- AI in Language and Communication: NLP and GPT-4
- The Impact of AI on Employment and the Future of Work
- Game Theory: Strategic Decision Making in Cultural Context
- Fractals, Chaos Theory, and Cultural Complexity
- Music, Mathematics, and AI: A Harmonious Intersection
- AI and Literature: Text Analysis, Generation, and Critique
- Mathematical Models in Economics and Social Sciences
- Big Data and Privacy: Balancing Utility and Ethics
- AI in Healthcare: Improving Outcomes and Reducing Disparities
- Climate Change, Sustainability, and Mathematical Modeling
- The Mathematics of Democracy: Voting Systems and Fair Representation
- Bias and Fairness in AI: Challenges and Solutions
- The Role of AI in Mental Health and Emotional Well-being
- AI and the Creative Arts: Exploring New Frontiers
- The Future of AI: Possibilities, Pitfalls, and Predictions
- Final Project: Applying Mathematics, Data Science, and AI to Cultural Analysis
