ECON4170 – Data science for economists
Course description
Course content
This course is equivalent with ECON3170- Data Science for Economists
Knowledge of computers and programming is becoming more important, also for economists. This course is aimed at introducing programming and computational tools useful for future careers as economists.
The first part of the course is an introduction to programming and common programming structures. The course goes on to cover manipulation of data, data analysis including an introduction to machine learning techniques, and basic numerical methods useful in economics.
Learning outcome
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
Admission to the course
Students admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.
Students not admitted to the Master’s programme in Economics or the Master’s programme in Economic Theory and Econometrics (Samfunns?konomisk analyse), can apply for admission to one of our study programmes, or apply for guest student status.
Recommended previous knowledge
- The course is based on prior knowledge in statistics and mathematics corresponding to ECON2130 – Statistikk for ?konomer and ECON1100 – Matematikk I.
- Students who do not have ECON2130 – Statistikk for ?konomer or equivalent, are advised not to take this course.
Overlapping courses
- 10 credits overlap with ECON3170 – Data science for economists.
Teaching
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.
Examination
?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.
Exam papers with comments from examiner
Examination support material
Resources allowed for the group assignment: All exam support materials are allowed during this exam. Generating all or part of the exam answer using AI tools such as Chat GPT or similar is not allowed.?
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.
Language of examination
The examination text is given in English. You may submit your response in Norwegian, Swedish, Danish or English.
Grading scale
Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.
Resit an examination
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.
More about examinations at UiO
- Use of sources and citations
- How to use AI as a student
- Special exam arrangements due to individual needs
- Withdrawal from an exam
- Illness at exams / postponed exams
- Explanation of grades and appeals
- Resitting an exam
- Cheating/attempted cheating
You will find further guides and resources at the web page on examinations at UiO.