Books and Compilations

Textbooks and Recommended References

There is no single textbook for CDS. The following books and compiled lecture notes treat, quite comprehensively, the topics that CDS broadly tries to cover -- highly recommended.

  • Chambers

    Software for Data Analysis: Programming with R

    John Chambers Springer (Second Printing), 2009
  • CormenEtal

    Introduction to Algorithms

    Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein The MIT Press (Third Edition), 2009
  • Solomon

    Numerical Algorithms

    Justin Solomon Available online at this link
  • TrefethenBau

    Numerical Linear Algebra

    Lloyd N. Trefethen and David Bau III SIAM (June 1997)
  • Foundations

    Foundations of Data Science

    Avrim Blum, John Hopcroft and Ravindran Kannan Available online at this link
  • ISL

    An Introduction to Statistical Learning

    Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani Available online at this link
  • ESL

    The Elements of Statistical Learning

    Trevor Hastie, Robert Tibshirani and Jerome Friedman Available online at this link
  • MMD

    Mining of Massive Datasets

    Jure Leskovec, Anand Rajaraman and Jeff Ullman Available online at this link

The books listed above are the basic references for CDS. During the course, we will refer back to these books from time-to-time, as and when requried, but we may not see through any of these books cover-to-cover.

  Lecture Videos and Notes

Adds a completely new dimension to Reading

There are several lecture notes and video lectures that perfectly complement the material that CDS plans to cover. The students are encouraged to follow these amazing resources.

  Programming Resources

If you take CDS, you must get your hands dirty

The main tools for computing used in CDS are R and Python. The following resources may help you in getting yourself acquainted with the basics of both the languages. Get comfortable!

  Ideas for Term Projects

Start thinking about Projects, from the very start

The students are encouraged to choose their own projects, inspired by online competitions, theoretical research problems, or practical problems from the Industry. The following list of ideas is just a starting point. Talk to the instructor, if you have any doubt about the project.

Under construction -- some initial ideas for the Term Project to be posted shortly.