Data Analysis and Visualization (5cr)

Objectives (course unit)

After completing the course, the students will be able to:
- Analyze what kind of data is needed or can be used for visualizations
- Transform and load basic data into analytics software (Tableau Public)
- Design simple visualizations
- Evaluate the quality of visualization applications

Content (course unit)

Data analytics concepts and process, data preprocessing and basic viz pipeline processing steps, tools (Tableau), types of visualizations, dashboards and interactive visualizations.

Prerequisites (course unit)

Students should have a basic understanding of how to use a computer and browse the internet (incl. using and editing plaintext files in a text editor). Note: Students also need their own pc they can install programs into (at least the Tableau Public desktop application).

Assessment criteria, pass/fail (course unit)

The student is able to reach the objectives of this course
The student is not able to reach the objectives of this course

Exam schedules

No exam.

Assessment scale

0-5

Teaching methods

Contact teaching
Assignments (the primary learning method)
Group work and presentation

Learning materials

Moodle course with links to additional material.

Student workload

See the period timetable. See the Moodle course for instructions when and how to attend the contact teaching hours

Further information

The course is organized (only) remotely, using MS Teams. See the Moodle course for instructions how to attend the contact teaching hours: https://moodle.tuni.fi/course/view.php?id=24455

Assessment criteria - fail (0) (Not in use, Look at the Assessment criteria above)

Less than 30% of the exercises completed.

Assessment criteria - satisfactory (1-2) (Not in use, Look at the Assessment criteria above)

The student is familiar with the essential concepts and can implement simple applications with specific instructions. At least 30% of the exercises completed.

Assessment criteria - good (3-4) (Not in use, Look at the Assessment criteria above)

The student is familiar with the basic concepts and can implement simple applications autonomously. At least 60% of the exercises completed.

Assessment criteria - excellent (5) (Not in use, Look at the Assessment criteria above)

The student is familiar with the main concepts, is able to critically evaluate application requirements, and can implement realistic applications autonomously. At least 90% of the exercises completed. A good group work completed and presented.