Welcome to the repository for the "Visual Data Analysis" course that I successfully completed as part of my Master's program in Computer Science at the University of Bonn. This course provided me with an in-depth exploration of the exciting field of data visualization and analysis, equipping me with valuable skills and knowledge.
Throughout this comprehensive course, I immersed myself in a diverse array of topics related to data visualization:
- 📊 Dimensionality Reduction Techniques: I mastered advanced techniques such as PCA, Kernel PCA, t-SNE, LDA, and IsoMap to reduce high-dimensional data for effective visualization.
- 🌈 Color Perception and Utilization: I gained insights into human color perception and learned how to harness the power of color in data visualizations for maximum impact.
- 🗺️ Geographical Maps: I delved into the intricacies of geographical data representation, covering various map projections, including cylindrical and non-pseudo cylindrical.
- 📈 Basic Visualization Techniques: I honed my skills in essential visualization methods, including scatterplots, boxplots, star glyphs, star coordinates, parallel coordinates, pie plots, barplots, and histograms.
- 🧬 Scientific Visualization: I navigated the complexities of scientific visualization, including the interpretation of X-ray, CT scan, and MR scan data, as well as volume rendering, isosurfaces, and more.
- 🐍 Libraries and Tools: I harnessed the power of Python and a wide range of libraries such as pandas, numpy, plotly, matplotlib, Dash, scikit-learn, seaborn, and the formidable VTK (Visualization Toolkit). Additionally, I explored data visualization with the ParaView application.
🏆 I am immensely proud to announce that I have successfully completed the "Visual Data Analysis" course. This accomplishment symbolizes my dedication to learning and my unwavering commitment to mastering complex data analysis techniques.
I am thrilled to apply the skills and knowledge acquired from this course to real-world data analysis projects and continue my exploration of the captivating realm of data visualization. If you have any questions about this course or wish to collaborate on data analysis endeavors, please do not hesitate to reach out!
Note: This README stands as a testament to my achievement in the "Visual Data Analysis" course at the esteemed University of Bonn.