Accommodation

  1. For the registered participants, shared accommodation at CMI student's hostel will be provided.
  2. Please note that the student's hostel does not have AC in the room.
  3. Student's hostel does not have elevator. You may have to climb one or two floor.
  4. You can check-in on 2nd Dec 2018 and check-out on 14 Dec 2018. Our current semester will end on 30th Nov 2018 (Friday). The current students will start vacating their room on first and 2nd Dec (Saturday and Sunday). As soon as the current students vacate their room, our cleaning staff will clean the room and help you check-in. However, there may be a delay in check-in. We apologize for inconvenience ahead of time.
  5. The hostel and the lecture halls are on campus.
  6. If you decide to stay outside campus, you have to find your own commute to CMI. CMI would not be able to provide any shuttle services.
  7. If you are looking for economy hotel you might look for OYO Rooms near CMI
  8. Following are some business and executive hotels near CMI
    1. Sabari Hotel While booking with Sabari you can mention that you are a CMI guest. The Sabari hotel pick up and drop off at CMI at free of cost.
    2. Novotel
    3. Days Hotel
    4. ibis
    5. Taj Fisherman's Cove Resort
  9. We encourage all the participants to stay on campus. As our program is very intensive.

Come with your own Laptop

  1. Please note that the course will assume prior familiarity with R and Python. The course is primarily conceptual, and the laboratory exercises will heavily rely on R and Python. Given the course design and planned content, please prepare accordingly for the class.
  2. For R and python, there are multiple learning resources available, such as:
    1. Python Click Here
    2. R Cleck Here
  3. You should come with your laptop
  4. Familiarity with R and Python is require.
  5. Also, we firmly suggest that you should install R-Studio (after installing the base-R).
  6. Install R and R-Studio for Mac

  7. Install R and R-Studio for Windows

  8. Install Python for Windows

Prepare Yourself for the School

You can go through the following lecture series to prepare yourself for the winter school.
  1. Fundamentals of Statistics by Philippe Rigollet by MIT OpenCourseWare


  2. Introduction to Algorithm and Data Structure by Srini Devadas by MIT OpenCourseWare


  3. Review sessions on Linear Algebra given at Princeton University in Spring 2008 by Prof Adrian Banner.

  4. You can check the other lectures of the above three series on the YouTube.