Data science for economists

Knowledge

• Know how to use computers to analyze data
• Basic knowledge of how computers work and what it implies for computation
• Common components of computer algorithms such as conditionals, loops, and functions
• How data can be visualized and some characteristics of good visualizations
• Knowledge of how numerical problems can be solved using computers

Skills

• Write a program in R to undertake analysis of data or numerical problems
• Import data from various sources and in different formats and transform them into an analyzable format
• Use the basic tools used in machine learning such as cross-validation as well as basic algorithms such as LASSO and random forests
• Implement algorithms for solving numerical problems such as taking derivatives, solving equations, and maximizing functions

Competence

• Knowledge of how computers and data science can be used to study economic and social phenomena
• The limitations of data science approaches to studying human behavior

• The course is based on prior knowledge in statistics and mathematics corresponding to ECON2130 and ECON1100.
• Students who do not have ECON2130 or equivalent, are advised not to take this course.

Students at UiO must apply for courses in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.

You can not attend this course if you have already passed specific ECON-courses at a higher level.

This course is not available for single course students.

Lectures and seminars.

You must bring your own laptop to be able to attend the teaching and seminars.

Course responsible can at the beginning of the semester update the syllabus list by changing no more than three articles, though in a way that it will not change the overall scope or thematic content of the course.

The syllabus also includes any lecture notes that will be made available for the students in Canvas.

Assessment is based on

• a group assignment (counting 40% of the total grade)
• a 3-hour written school exam (counting 60% of the total grade)

The topic for the group assignment is selected within some given categories, and must be approved by the course coordinator early in the semester. Deadline for submission will be before the written examination, at the end of the semester.

Both exams must be passed the same semester in order to receive a valid final grade.

Previous exams and examiner guidelines

Exam papers with comments from examiner

Resources allowed for the group assignment: All support material is allowed. When using AI, you must explain and be transparent about its use: read more about the guidelines for AI and exams at How to use AI as a student - University of Oslo

Resources allowed for the written school exam: Open book examination where all printed and written resources are allowed. Some material will be available in Inspera. Further notice will be given.

If you are sick or have another valid reason for not attending the regular exam, we offer a postponed exam later in the same semester.

See also our information about resitting an exam.

Students who wish to retake the exam in a later semester are not guaranteed that the course will be given with the same content and syllabus, or that the examination scheme will be the same.