• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • А
  • А
  • А
  • А
  • А
Обычная версия сайта

Магистерская программа «Сравнительная политика Евразии»

Data Science

2018/2019
Учебный год
ENG
Обучение ведется на английском языке
3
Кредиты
Статус:
Курс по выбору
Когда читается:
1-й курс, 3 модуль

Преподаватель


Гилев Алексей Владимирович

Course Syllabus

Abstract

The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
Learning Objectives

Learning Objectives

  • This course get an introduction to the main tools and ideas in the data scientist's toolbox.
Expected Learning Outcomes

Expected Learning Outcomes

  • Student is introduced to the main tools and ideas in the data scientist's toolbox
  • Student is introduced to programming in R
Course Contents

Course Contents

  • Introduction
  • Installing the Toolbox
  • Conceptual Issues
  • Course Project Submission & Evaluation
  • Introduction to R
  • Programming with R
  • Loop Functions and Debugging
  • Simulation & Profiling
Assessment Elements

Assessment Elements

  • non-blocking Tests
  • non-blocking Exam
Interim Assessment

Interim Assessment

  • Interim assessment (3 module)
    0.35 * Exam + 0.65 * Tests
Bibliography

Bibliography

Recommended Core Bibliography

  • Grimmer, J., & Stewart, B. M. (2013). Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.BC6A6457
  • Rob Kitchin. (2014). Big Data, new epistemologies and paradigm shifts. https://doi.org/10.1177/2053951714528481
  • Walker, S. J. (2014). Big Data: A Revolution That Will Transform How We Live, Work, and Think. International Journal of Advertising, 33(1), 181–183. https://doi.org/10.2501/IJA-33-1-181-183

Recommended Additional Bibliography

  • Approaches and methodologies in the social sciences : a pluralist perspective / ed. by Donatella della Porta . (2008). Cambridge [u.a.]: Cambridge University Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.283822104
  • King, G. (DE-588)135604311, (DE-576)166299405. (1994). Designing social inquiry : scientific inference in qualitative research / Gary King; Robert O. Keohane; Sidney Verba. Princeton, NJ: Princeton Univ. Press. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edswao&AN=edswao.039730549