EBA 3400 Programming, Data Extraction and Visualisation
EBA 3400 Programming, Data Extraction and Visualisation
This course covers basic Python programming and data manipulation and visualization packages, aiming to provide students with fundamental skills for solving practical problems in data science. Using a hands-on learning approach, students will develop their programming skills through a variety of in-class and out-of-class exercises.
Throughout the course, students will:
- Learn how to translate real-world problems into Python code and explore the possibilities of using programming to complete data science tasks.
- Learn basic data analytics and develop an understanding of the exploratory phase in empirical investigations.
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.
This course will train logical thinking by converting ideas into computer programs, thereby improving students' analytical skills. It will develop critical thinking skills by analyzing and extracting information from a wide range of datasets. Overall, the course aims to improve students' information literacy by providing them with a technical understanding of 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 28 hours of synchronous classroom instruction and 17 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: Submission other than PDF Exam/hand-in semester: First Semester Weight: 30 Grouping: Individual Duration: 3 Hour(s) Exam code: EBA 34002 Grading scale: ECTS Resit: Examination every semester |
Exam category: Submission Form of assessment: Submission other than PDF Exam/hand-in semester: First Semester Weight: 70 Grouping: Individual Duration: 3 Hour(s) 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 | 28 Hour(s) | |
Individual problem solving | 17 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.