Course Essentials

Syllabus (download)
Progress Journals

Extra week (Dec 25, 2019)

Machine Learning Part I (html | pdf)
Bonus: Introduction to Cloud Computing. Make sure you get the GitHub Student Developer Pack. Participation is completely voluntary.
- Create an account in Digital Ocean
- Check this old tutorial
- Magic command: docker run -e USER=rstudio -e PASSWORD=rstudio2 -d -p 8787:8787 rocker/tidyverse
Machine Learning Part II (html | pdf)
Machine Learning Parts Exercises (ps. not assignments)
- Exercise 1: Esoph and Youth Survey (html | pdf)
- Exercise 2: Spam Data (html | pdf)
- Exercise 3: Diamonds Data (html | pdf)

Week 7 (Dec 11, 2019)

Presentations!

Week 6 (Nov 27, 2019)

Main topic: Data joins with dplyr
Exercise data: ATP World Tour 2017 Tennis data (RData) (Source)
Joins tutorial
Guests
- Melis Bilgiç Aksarı from MTX Commodities
- Burak Gökçe from Engie

Week 5 (Nov 13, 2019)

Postponed to Dec 25, 2019

Week 4 (Oct 30, 2019)

This week we will see shiny to create interactive dashboards on web browsers (official tutorial). Also see the Shiny Cheatsheet from RStudio. (Bonus: Check to deploy your shiny apps)
Check lubridate for a date-time library. You will love parse_date_time, as_date, as_datetime functions. It will not be taught in the classroom but it is great to know.
Project Guidelines
Guests
- Taner Doğuç from QNB Finansbank
- Elif Tokatlı from QNB Finansbank

Collaboration on assignments is endorsed but all assignments will be on a first come first graded basis. It means if you found a good idea and submitted an analysis before all other teams any team with not novel ideas will not get extra points (i.e. please do not copy-paste). With too much similarity, the early team (by GitHub submission time) will get all the credit and points. Same principle also applies for previous years’ assignments, they are earlier.

ODD Assignment (Group) (Deadline Nov. 5)
- Gather car sales data from ODD website from 2016 until September 2019. You can check example code to gather ODD data and refer to course archive for similar analysis.
- Do 3 different analyses and draw at least one plot using dplyr and ggplot2 in an RMarkdown file.
- Upload the file in your Group Progress Journal.
EGM Assignment (Group) (Deadline Nov. 8)
- Gather BES (Bireysel Emeklilik Sistemi) fundamentals data (BES Temel Göstergeler) from EGM website until 31 July 2019 (use excel link given below the table). Use at least two years past data.
- Do 3 different analyses and draw at least one plot using dplyr and ggplot2 in an RMarkdown file.
- Upload the file in your Group Progress Journal.
BKM Assignment (Individual) (Deadline Nov. 11)
- Gather data from BKM Sektörel Gelişim reports (tip: use rvest as we did in class) and analyze progression of different sectors. Put at least two analyses and one plot using dplyr and ggplot2 in an RMarkdown file.
- Upload the file in your Progress Journal.

Week 3 (Oct 16, 2019)

Revision week
ggplot2 (html)
ggplot2 Extra Material (html | pdf)
(Extra) Lubridate (Link)

Week 2 (Oct 2, 2019)

Tidyverse Introduction: dplyr (html)
Alternative Tutorial (previous year’s) (html |pdf)
dplyr join operations 1, 2
Bonus Material (Program coordinator’s recommendation): EdX - The Analytics Edge
Guest: Zeynep Küçükçavdar from LC Waikiki

Week 1 (Sep 18, 2019)

Cheat Sheet Heaven
Introduction to R (html | pdf)
Some base R exercises (html) (Solutions!)
RMarkdown
Datacamp Homework (Don’t forget to accept your invitations)
RMarkdown Homework: Prepare an RMarkdown document. Introduce yourself in one paragraph (Your name surname, your work, your data interests and how you (plan to) use data science skills in your current/future work). Watch some UseR-2019 videos (Link) and write one of them down on your RMarkdown document. Find 3 R posts relevant to your work and describe them. Get the html output and put it in your progress journal repository. Provide link from your Progress Journal page. (Click for example)
Form teams of 4-5 and prepare for major projects (we will discuss in week 2).