This course benefits from DataCamp for the Classroom program. See details here.

Conclusions (Jan 10-15, 2018)

Final (Jan 6-9, 2018)

Final! Read the instructions inside carefully, submit on time. (html | pdf).

Week 7 (Dec 19, 2017)

Presentations! See the presentation guidelines (html | pdf).

Week 6 (Dec 5, 2017)

This is the last week of the lectures. Aside from the remaining CART part, you are going to create your first R packages. R packages are very useful to bring the codes together for projects. Also, you can upload your package to GitHub and share your work with others (or just reach your project easily from basically anywhere with internet connection). We are going to follow these two tutorials.

You are going to see only the essentials. I am not going to cover the aspects of crafting an R package in detail. We are going to write a simple function inside a package, write documentation inside with roxygen2 and call it from the package. You can also upload it to a GitHub repo and try to call from there (optional).

Week 5 (Nov 21, 2017)

Your R links from the first assignment are put together into a single file by Özgur Hoca. You can find it here or download the Excel file from here.

Assignments (Due Date Nov. 30)

You have 3 individual assigments. You may do all of them but choose one to report. Add the assignment to your individual Progress Journals. If you add more than one assignment to your PJ, state the one you want to be graded. (p.s. Those data sets are popular on internet. If you find an inspiration, please state it in a references section with links.)

Lecture Notes

Please check the Machine Learning tutorials and install the necessary packages. It is recommended for you to come next lecture with your own laptops. We are not going to wait for installation problems as some packages might have many dependencies that might be problematic (Meaning: It took me 3 hours to find the solution to install rattle on Mac, we don’t have that luxury during lecture hours).

Also download the data folder in (given below) for the necessary data files.

Note: For Mac OS >10.11 (El Capitan and above) users, it might cause trouble to install rattle package. Refer to this tutorial.

Also if rmarkdown is giving you any trouble, update it from github.

Week 4 (Nov 7, 2017)

Week 3 (Oct 24, 2017)

Project Examples from Last Year’s Course

Check out these projects to be an example for your projects. Though, better work is expected from you for this year :) (MEF Trivia fact: One of the students of MEF BDA program from last year is now your instructor.)

Week 2 (Oct 10, 2017)

Extra Materials

For audiovisual learners, some webinars here.






Week 1 (Sep 26, 2017)

Supplementary Documents

External Good Resources About R and Data Science

Data Sets for Prospective Projects,6552/sureli-yayinlar.html