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Starts 4 July 2025 03:54

Ends 4 July 2025

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AI for Mathematics - From Digitization to Intelligentization

Explore the evolving relationship between AI and mathematics, from historical interactions to cutting-edge research at Peking University, focusing on dataset formalization and future intelligent applications.
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Harvard CMSA

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Overview

Explore the evolving relationship between AI and mathematics, from historical interactions to cutting-edge research at Peking University, focusing on dataset formalization and future intelligent applications.

Syllabus

  • Introduction to AI and Mathematics
  • Overview of AI in historical and modern contexts
    The role of mathematics in AI development
    Introduction to key concepts and terminology
  • Historical Interactions Between AI and Mathematics
  • Early developments and pioneers
    Coursework and research trends over decades
    Notable case studies
  • Dataset Formalization in Mathematics
  • Introduction to dataset creation and annotation
    Challenges in mathematical data representation
    Tools and techniques for digitization and data preprocessing
  • AI Applications in Mathematical Problem Solving
  • Overview of algorithms in mathematical computations
    AI models for theorem proving and conjecture generation
    Case studies of AI systems in mathematical research
  • Cutting-edge Research at Peking University
  • Current projects and innovations in AI and mathematics
    Key research papers and their contributions
    Collaborations and interdisciplinary approaches
  • Future Intelligent Applications
  • Emerging trends in AI-enabled mathematical tools
    Predictive modeling in mathematics using AI
    Opportunities and challenges in future developments
  • Practical Applications and Case Studies
  • Real-world applications of AI in mathematics
    Success stories and lessons learned
    Hands-on exercises with AI tools and platforms
  • Ethical Considerations and Impact
  • Ethical implications of AI in mathematical research
    Societal impact and responsibility
    Discussion on AI governance and policy-making
  • Conclusion and Future Directions
  • Recap of key topics and learnings
    Opportunities for further exploration and research
    Final thoughts on the evolving relationship between AI and mathematics

Subjects

Data Science