Přístupnostní navigace
E-application
Search Search Close
Course detail
FP-zvdPAcad. year: 2026/2027
The course "Data Processing and Visualization" includes an introduction to data processing and visualization, where students will learn about definitions, importance, tools, and technologies, as well as the basics of statistics and data analysis. It then focuses on data structures and formats, data preprocessing, basic and advanced visualization techniques, interactive visualizations, time series visualization, and big data visualization. Students will also learn about the ethics and interpretation of data, analyze case studies, and become familiar with trends and the future of data processing, including new technologies, big data, and cloud databases.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Entry knowledge
The following prerequisites are expected:Basic knowledge of statistics and probabilityBasic knowledge of working with spreadsheet software (e.g., Excel)Basic knowledge of database systems and fundamentals of SQL
Rules for evaluation and completion of the course
Conditions for Graded Credit: The student must obtain at least 50% of the points during the semester, which is 50 points out of 100. Plagiarism or unauthorized collaboration on projects or tests will result in the denial of credit and may lead to disciplinary proceedings.Midterm Test: Completion of a practical task according to the assignment (40 points). The minimum number of points required is 20.Project: One project according to the assignment with the appropriate documentation (60 points). The minimum number of points required is 30.The assignment is introduced in the third lecture. The evaluation is in accordance with the ECTS grading scale.
Course Completion for Students with Individual Study PlansCredit Completion of a project according to the assignment with the appropriate documentation. The assignment is presented in the third lecture.A minimum of 50 points out of 100 is required.
Aims
The aim of the course "Data Processing and Visualization" is to provide students with the theoretical and practical knowledge necessary for data processing and visualization. Students will learn to use various tools and technologies for data analysis and visualization, which will enable them to develop skills in interpreting and presenting data analysis results. An important part of the course is also familiarizing students with ethical issues related to data processing. The course will prepare students to work with large data sets and modern technologies in the field of data analytics.
Study aids
Study supports are displayed in e-learning.
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
specialization BAK-EAM-UAD , 2 year of study, summer semester, compulsoryspecialization BAK-EAM-EP , 2 year of study, summer semester, compulsory
Lecture
Teacher / Lecturer
Syllabus
1. Introduction to Data Processing and VisualizationDefinition and ImportanceOverview of Tools and TechnologiesBasics of Statistics and Data Analysis (Descriptive and Inferential Statistics)2. Data Structures and FormatsStructured and Unstructured DataData FormatsData Preprocessing (Cleaning, Transformation, and Normalization)3. Basic Visualization TechniquesBasic Charts (Bar, Pie, Line)Advanced Visualizations (Heatmaps, Scatter Plots)Tools for Data Visualization (Tableau, Power BI, Matplotlib)4. Interactive VisualizationsCreating Interactive DashboardsUsing Interactive ElementsVisualization of Geographical Data (Map Visualizations, GIS)5. Time Series VisualizationTime Series AnalysisVisualization Techniques for Time SeriesVisualization of Big Data (Challenges and Solutions, Tools)6. Ethics and Data InterpretationEthical Issues in Data ProcessingInterpretation and Presentation of ResultsCase Studies (Real Examples, Discussion and Analysis)7. Trends and Future in Data ProcessingNew Technologies and ApproachesBig Data and AnalyticsCloud Databases
Exercise
1. Introductory ExerciseIntroduction to Tools and EnvironmentBasic Data Operations2. Working with Data FilesImport and Export of DataManipulation of Data Frames3. Data Cleaning and PreprocessingIdentification and Removal of ErrorsNormalization and Transformation of Data4. Basic VisualizationsCreating Basic ChartsAdjusting and Customizing Charts5. Advanced VisualizationsCreating Advanced ChartsUsing Advanced Visualization Techniques6. Interactive DashboardsCreating Interactive DashboardsWorking with Interactive Elements7. Geographical Data VisualizationWorking with Map VisualizationsUsing GIS Tools8. Time Series VisualizationAnalysis and Visualization of Time SeriesUsing Appropriate Visualization Techniques9. Big Data VisualizationWorking with Large Data SetsUsing Tools for Big Data Visualization10. Case StudiesAnalysis of Real Data SetsCreating Visualizations for Case Studies11. Project WorkDesign and Implementation of Own Project12. Project WorkDesign and Implementation of Own Project13. Presentation and Interpretation of Results
Self-study
Individual preparation for an ending of the course