Program Overview

Program Overview

The program "SAS og AI i praksis" (Practical SAS and AI) is a course offered by the University of Copenhagen, focusing on advanced programming possibilities in SAS, including data step, conversion of datasets from other formats, and handling of format libraries. Special topics covered include handling of text variables, do-loops, arrays, and SAS macros, applied to Monte Carlo and bootstrap analyses.

Program Details

• The program is a revision of the course "Programmering og statistik med SAS" and overlaps approximately 50% with this course.
• It is not possible to take both courses.
• The program is open to:
  • Students from Danish universities
  • Students from the Open University
  • Exchange and guest students from abroad
• The program is offered in Danish.

Program Objectives

After completing the course, the student is expected to be able to:

• Describe and understand the database structure in SAS
• Explain the many possibilities for data preparation with SAS
• Describe the construction of SAS procedures
• Understand complex SAS programs
• Understand the integration between SAS and open-source tools
• Describe the application of generative AI to SAS code
• Perform practical data handling in SAS with a view to preparing data for subsequent statistical and econometric analyses
• Apply SAS procedures
• Obtain information from generative AI and SAS's help facilities to quickly apply unknown SAS procedures to statistical analyses
• Integrate open-source tools with SAS for (statistical) analyses
• Produce statistical results using unknown SAS procedures
• Generate and understand statistical models and machine learning models in SAS
• Effectively use SAS together with generative AI

Teaching Methods

The methods are covered through online SAS sessions. During the lectures, some exercise tasks are calculated, where students test SAS.

Teaching Materials

• Lecture notes in the form of distributed SAS programs
• Online SAS manual

Recommended Prerequisites

• The course "Sandsynlighedsregning og Statistik" and Økonometri I, where Økonometri I should at least be followed in parallel with "SAS og AI i praksis"
• For participants from other studies, a introductory statistics course is required
• Prior knowledge of SAS is not a prerequisite

Assessment

• The exam is a 6-hour home assignment, where each examinee receives an individually set dataset, which must be answered and submitted individually
• The use of AI tools is allowed, but the student must explain how they have been used
• When text is exclusively or primarily generated by an AI tool, the tool must be cited as a source

Examination Criteria

The assessment criteria are based on the content of the course description.

• To achieve the highest grade "12", the student must demonstrate with a superior presentation and with no or few insignificant errors that they meet the course's objectives and the listed points for knowledge, skills, and competencies
• To achieve the grade "02", the student must demonstrate a sufficient performance, showing a minimally acceptable degree of fulfillment of the course's objectives and the listed points for knowledge, skills, and competencies

Course Type

• Single subject, daytime (empty space arrangement)

Workload

• Category:
  • Lectures: 42 hours
  • Preparation (estimated): 158 hours
  • Exam: 6 hours
  • Total: 206 hours

Course Information

• Teaching language: Danish
• Course number: AØKA08246U
• ECTS: 7.5 ECTS
• Level: Master's and Bachelor's
• Duration: 1 semester
• Placement: Spring
• Price: Information on prices, etc. for single subjects and further education can be found on the website of the Department of Economics

Responsible Institute

• Department of Economics

Responsible Faculty

• Faculty of Social Sciences

Course Responsible

• Sara Armandi

Teacher

See "Course Responsible"

Timetable

• 26F-; Lecture;; SAS and Artificial Intelligence in Practice

Are you a BA or KA student?

If you are a bachelor or kandidat student, find the course in the course catalog for students: Course information for students

University of Copenhagen

• Address: Nørregade 10, 1165 København K
• Note: The provided contact information has been removed as per the instructions.