Skip to main content

About Study Course

ECTS:5
Course supervisor:Sergio Uribe, Sergio Andres Uribe Espinoza
Study type:Full time
Course level:Master's
Target audience:Business Management; Communication Science; Dentistry; Health Management; Information and Communication Science; Life Science; Management Science; Marketing and Advertising; Medical Services; Medical Technologies; Medicine; Midwifery; Political Science
Language:English
Study course description Full description, Full time
Branch of science:Mathematics

Objective

The "Data Processing and Visualization" course aims to provide students with the essential skills and knowledge required to proficiently manipulate, analyze, and visualize data using the R programming language. The course is designed to provide a comprehensive introduction to data science concepts, focusing on data manipulation, cleaning, and exploratory data analysis. Through hands-on and project-based learning, students will develop the ability to create insightful visualizations, effectively communicate data-driven insights, and apply analytical techniques to solve real-world problems in digital health and health management.

Prerequisites

Basic knowledge of spreadsheets or Excel is desirable but not required for this course. It is designed to accommodate students with no prior experience in programming or data analysis and provides a foundational understanding of data science concepts using R.

Learning outcomes

Knowledge

1.Upon completing the module´s course the students will:
Understand the principles and techniques of exploratory data analysis, focusing on summarization and visualization of data.
Recognize the importance of tidy data and its role in facilitating analysis.
Learn about data cleaning processes essential for accurate exploratory analysis.

Skills

1.The students will be able to:
Conduct thorough exploratory analyses using various visualization techniques.
Identify patterns, trends, and anomalies in datasets.
Utilize R to manipulate and prepare data for analysis effectively.

Competence

1.Students will be able to:
Assess data quality and make necessary adjustments to facilitate insightful explorations.
Create informative visualizations that communicate the findings clearly and effectively.
Develop an analytical mindset that prioritizes understanding data structures and relationships within data.

Study course planning

Planning period:Year 2026, Spring semester
Study programmeStudy semesterProgram levelStudy course categoryLecturersSchedule
Digital transformation in the health care sector2Master'sRequired
Digital transformation in the health care sector 2Master'sRequired