Full Course Syllabus

Course Resource List

The following materials are intended to support CSC 84040 and the study of advanced data mining, AI agents, large-scale data systems, and autonomous research workflows.

Free Textbooks and Open Resources

  1. Mining of Massive Datasets (3rd Edition) by Jure Leskovec, Anand Rajaraman, and Jeffrey D. Ullman
    Cambridge University Press
  2. Probability: Introduction to Probability for Computing by Mor Harchol-Balter
    PDF
  3. Mathematics for Machine Learning by Deisenroth, Faisal, and Ong
    Book
  4. An Introduction to Statistical Learning with Python
    Book
  5. JAX 101 Tutorial and JAX documentation
    JAX docs

Open-Source Tools and Frameworks

  1. Hugging Face
    https://huggingface.co/
  2. JAX and JAXMARL
    https://docs.jax.dev/en/latest/
    https://github.com/FLAIROx/JaxMARL
  3. PySpark and Python multiprocessing tools
    Apache Spark
  4. NetworkX and SNAP
    https://networkx.org/
    https://snap.stanford.edu/
  5. OpenAlex and Semantic Scholar Open Data
    https://openalex.org/

Writing and Evaluation Resources

  1. Overleaf LaTeX Editor
    https://www.overleaf.com/
  2. TeXstudio
    https://texstudio-org.github.io/getting_started.html
  3. Python unittest and pytest
    https://docs.python.org/3/library/unittest.html
    https://pytest.org/
  4. Google Colab
    https://colab.research.google.com/

Additional References

Students are expected to use instructor guidance, open-source literature, and project-specific research papers to support the design, evaluation, and reporting of their work in the course.