# EBA 1180 Mathematics for Data Science

## EBA 1180 Mathematics for Data Science

Course code:
EBA 1180
Department:
Economics
Credits:
7.5
Course coordinator:
Eivind Eriksen
Course name in Norwegian:
Mathematics for Data Science
Product category:
Bachelor
Portfolio:
Bachelor - Common Courses
Semester:
2022 Autumn
Active status:
Active
Level of study:
Bachelor
Teaching language:
English
Course type:
Associate course
Course codes for multi- or associated courses
Course codeSemester
EBA 1181 - høstsemester
2022 Autumn
EBA 1182 - vårsemester
2023 Spring
Introduction

This is a basic course in mathematics. The course is a compulsory part of the Bachelor of Data Science. The course will be taught during the first year over two semesters. It consists of an introductory part in the autumn semester, and an advanced part in the autumn and spring semester.

Learning outcomes - Knowledge

After completing the course, the student will have;

• Acquired a broad understanding of concepts, methods and theories in mathematics.
• A broad knowledge of algebra, functions in one or several variables, financial mathematics, derivation and integration, and linear algebra.
• Specialized knowledge of how mathematical models and methods can be used in economics and finance.
Learning outcomes - Skills

After completing the course, the student will be able to:

• Analyze quantitative problems using mathematical concepts, and be able to use mathematical methods to solve these problems.
• Assess solution strategies, and be able to carry out the necessary computations correctly and precisely.
• Give mathematical arguments to justify his conclusions, and be able to give written answers that explains the method used and the obtained results to the reader.
• See connections between mathematics and other subjects, especially economics and finance.
• Be able to translate mathematical problems into algorithms and Python code
General Competence

After completing the course, the student will be able to reflect upon central assumptions for the models and theories used. The student will be able to reflect upon the results obtained, and critically assess if they are reasonable.

Course content
• Elementary algebra
• Mathematics of finance and series
• Functions and graphs
• Exponential and logarithmic functions
• Derivation with applications
• Integration with applications
• Linear algebra and matrix algebra
• Functions of several variables
• Optimization in several variables
Teaching and learning activities

The course is lectured over one year and consists of an introductory part (36 hours) and an advanced part (48 hours).

For each week, there will be a work program consisting of a problem set and reading assignments. The student must learn the material presented in the reading assignments and work through the problem set. Some of the problems will be reviewed in plenary sessions.

By allocating some time in class to short assignment related to new topics, students will be activated and learning objectives achieved.

Wolfram Alpha is used in lecture to illustrate taught material. Problem sets will include problems the students should solve using python.

Software tools
Software defined under the section "Teaching and learning activities".

As of the academic year 2022/2023, the course code and course name will be changed from EBA 2910 Mathematics for Business Analytics to EBA 1180 Mathematics for Data Science.

Qualifications

Higher Education Entrance Qualification

### Disclaimer

Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.

Required prerequisite knowledge

Basic knowledge of mathematics equivalent to the admission requirement for the programme.

Assessments
Assessments
Exam category:
Submission
Form of assessment:
Written submission
Grouping:
Individual
Duration:
1 Week(s)
Comment:
Midterm exam in the autumn.
All exams must be passed to obtain a final grade in the course.
Exam code:
EBA11801
Pass/fail
Resit:
Examination every semester
Exam category:
Submission
Form of assessment:
Written submission
Invigilation
Weight:
20
Grouping:
Individual
Support materials:
• BI-approved exam calculator
• Simple calculator
• Bilingual dictionary
Duration:
3 Hour(s)
Comment:
Written exam at the end of the autumn term.
All exams must be passed to obtain a final grade in the course.
Exam code:
EBA11802
ECTS
Resit:
Examination every semester
Exam category:
Submission
Form of assessment:
Written submission
Grouping:
Individual
Duration:
1 Week(s)
Comment:
Midterm exam in the spring.
All exams must be passed to obtain a final grade in the course.
Exam code:
EBA11803
Pass/fail
Resit:
Examination every semester
Exam category:
Submission
Form of assessment:
Written submission
Invigilation
Weight:
80
Grouping:
Individual
Support materials:
• BI-approved exam calculator
• Simple calculator
• Bilingual dictionary
Duration:
5 Hour(s)
Comment:
Written exam at the end of the spring term.
All exams must be passed to obtain a final grade in the course.
Exam code:
EBA11804
ECTS
Resit:
Examination every semester
Type of Assessment:
Ordinary examination
All exams must be passed to get a grade in this course.
Total weight:
100
ActivityDurationComment
Teaching
84 Hour(s)
Lectures
Group work / Assignments
60 Hour(s)
Problem sessions
Examination
16 Hour(s)
Two course papers, multiple choice exam and final exam
Student's own work with learning resources
65 Hour(s)
Own work with theory and problems