Data Visualization: Techniques, Tools & Concepts

Related lectures (32)

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Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.

Explores finite element methodology, covering geometric modeling, technical data, physical behavior assumptions, and mesh convergence studies.

Explores the tools and features of Vectorworks Design Suite 2022 for design and visualization.

Covers data manipulation and exploration using Python with a focus on visualization techniques.

Covers eigenvalues, eigenfunctions, Hermitian operators, and the measurement of observables in quantum chemistry.

Covers Python basics, Pandas, data manipulation, visualization, and machine learning.

Covers the fundamentals of spectroscopy, including tools, color, Doppler effect, and molecular behavior.

Covers the analysis of ECG heart rate data and respiratory flow measurements using Excel.

Explores creating dashboards in ServiceNow, focusing on advantages, transition from homepages, and important concepts like tasks and incidents.

Introduces collaborative data science tools like Git and Docker, emphasizing teamwork and practical exercises for effective learning.