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EBA 3400 Programming, data extraction and visualisation

EBA 3400 Programming, data extraction and visualisation

Course code: 
EBA 3400
Department: 
Data Science and Analytics
Credits: 
7.5
Course coordinator: 
Wei-Ting Yang
Course name in Norwegian: 
Programming, data extraction and visualisation
Product category: 
Bachelor
Portfolio: 
Bachelor of Data Science for Business - Programme Courses
Semester: 
2022 Autumn
Active status: 
Active
Level of study: 
Bachelor
Teaching language: 
English
Course type: 
One semester
Introduction

The aim of this course is to equip the students with basic tools in programming, data extraction and visualization of datasets. Using a learning-by-doing approach, we solve basic problems encountered in data science using Python. The course will be using a blended learning approach with a focus on solving practical problems under guidance by teachers. Data examples for business applications will be given.

Learning outcomes - Knowledge

During the course students shall:

  • Learn basic data analytics, and have an overview of the exploratory phase of an empirical investigation.
  • Learn how to translate practical problems into Python code, and the possibilities that programming gives the data analyst. 
Learning outcomes - Skills

After completed course students will be able to:

  • Perform basic data exploration and visualization tasks.
  • Automate analyses that would otherwise be impossible to perform manually. Importantly, the course gives basic skills in Python programming.
  • Communicate the result of an empirical investigation based on the tools introduced in the course. 
General Competence

The course will strengthen the analytical abilities of the students, and give them tools to test their logic through writing computer programs. The course will further improve the students' abilities in central 21st century skills, such as enabling critical thinking through visualizing statements about large amounts of data, working on technical problems, and in general improve the students' information literacy through gaining a technical understanding in information processing.

Course content
  1. Basics of Python
    • Understand variables and data types.
    • Use statements for automated tasks (conditionals and loops).
    • Write functions.
  2. Data extraction and exploratory analysis
    • Read and write data with Python.
    • Access a sub-set of a dataset, changing parts of the data, etc.
    • Analyze data quality.
    • Compute summary statistics and interpret the results.
  3. Visualization techniques
    • Use univariate plots and multivariate plots to visualize data.
    • Interpret the results of the plots.
Teaching and learning activities

The course has 42 hours and will consist of lectures and problem solving using Python.

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

.

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

No specific prerequisites are required.

Exam categoryWeightInvigilationDurationSupport materialsGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
EBA 34001
Grading scale:
Point scale leading to ECTS letter grade
Grading rules:
Internal examiner with external supervisor
Resit:
All components must, as a main rule, be retaken during next scheduled course
40No3 Hour(s)Individual
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
EBA 34001
Grading scale:
Point scale leading to ECTS letter grade
Grading rules:
Internal examiner
Resit:
All components must, as a main rule, be retaken during next scheduled course
30No1 Week(s)Group (1 - 3)
Exam category:
Submission
Form of assessment:
Structured test
Exam code:
EBA 34001
Grading scale:
Point scale leading to ECTS letter grade
Grading rules:
Two examiners
Resit:
All components must, as a main rule, be retaken during next scheduled course
30Yes 45 Minute(s)
  • Bilingual dictionary
Individual
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:40
Invigilation:No
Grouping (size):Individual
Support materials:
Duration:3 Hour(s)
Comment:
Exam code:EBA 34001
Grading scale:Point scale leading to ECTS letter grade
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam category:Submission
Form of assessment:Written submission
Weight:30
Invigilation:No
Grouping (size):Group (1-3)
Support materials:
Duration:1 Week(s)
Comment:
Exam code:EBA 34001
Grading scale:Point scale leading to ECTS letter grade
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam category:Submission
Form of assessment:Structured test
Weight:30
Invigilation:Yes
Grouping (size):Individual
Support materials:
  • Bilingual dictionary
Duration: 45 Minute(s)
Comment:
Exam code:EBA 34001
Grading scale:Point scale leading to ECTS letter grade
Resit:All components must, as a main rule, be retaken during next scheduled course
Type of Assessment: 
Continuous assessment
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
42 Hour(s)
Feedback activities and counselling
36 Hour(s)
Student's own work with learning resources
86 Hour(s)
Examination
36 Hour(s)
One group asssignment and and two individual written exams. Approxemately 36 hours in total.
Sum workload: 
200

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.