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Programming for Analytics (2017 Autumn)

Organisation: UTU / Faculty of Social Sciences, Business and Economics

Credit Points: 5

Responsible Person: Anssi Öörni

Course code: 457611.0

Learning outcomes:
In this course the student will learn the basics of programming in Python programming language in the context of processing data into suitable input for data analytics. The focus of the course is on learning the basics of programming such as data types, control structures, and algorithms and data structures useful for the data analyst. The student will also learn to use Python programming language and the Python data analysis libraries (pandas and NumPy).

Contents:
The aim of this course is to give the student programming skills needed for data validation and data cleansing. Data validation and data cleansing is a major part of data analysts work. As the amount of data grows, so does need for automation, and it becomes increasingly critical that the analyst has sufficient programming skills to be able to create tools to manage large data sets efficiently. These include ability to write code for strict or fuzzy data validation, i.e. removal or repair of records of data, and for harmonization, standardization and enhancement of data.

30.10.–19.12.2017

Lectures:

  1. Mon 30.10.–18.12. weekly at 10–12, B329, Asa
  2. Tue 31.10.–19.12. weekly at 10–12, B121, Asa