EBA 3400 Programming, Data Extraction and Visualisation
EBA 3400 Programming, Data Extraction and Visualisation
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.
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.
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.
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' analytical skills, such as enabling critical thinking through the analysis and visualization of large amounts of data, working on technical problems, and in general improve the students' information literacy through gaining a technical understanding in information processing.
- Python basics
- Programming environment.
- Variables and data types.
- Input and output.
- Control flow (conditionals and loops).
- Functions.
- Data extraction and visualization
- Reading and writing data.
- Data summarization and quality assessment.
- Subset selection and data manipulation.
- Data aggregation and statistics computation.
- Data visualization and interpretation.
The course consists of 30 hours of synchronous classroom instruction and 15 hours of asynchronous learning. Asynchronous learning activities include exercises, quizzes, and readings.
The Python programming language will be taught in the course.
- Please note that while attendance is not compulsory, it is the student’s own responsibility to obtain any information provided in class.
- Students wishing to improve their grades may retake the exam at the next scheduled exam.
Higher Education Entrance Qualification
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
No specific prerequisites are required.
| Assessments |
|---|
Exam category: Submission Form of assessment: Handin - all file types Weight: 30 Grouping: Group (1 - 3) Duration: 3 Day(s) Exam code: EBA 34002 Grading scale: ECTS Resit: Examination every semester |
Exam category: Submission Form of assessment: Handin - all file types Weight: 70 Grouping: Individual Duration: 3 Hour(s) Comment: . Exam code: EBA 34003 Grading scale: ECTS Resit: Examination every semester |
All exams must be passed to get a grade in this course.
| Activity | Duration | Comment |
|---|---|---|
Teaching | 30 Hour(s) | |
Individual problem solving | 15 Hour(s) | Asynchronous activities: exercises, quizzes, and readings. |
Feedback activities and counselling | 15 Hour(s) | |
Student's own work with learning resources | 100 Hour(s) | |
Examination | 40 Hour(s) |
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.