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Lecture
Data Visualization: Techniques and Applications
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Related lectures (32)
Data Visualization: Techniques, Tools & Concepts
Covers data visualization techniques, tools, and concepts for effective data representation.
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Introduction to Spark Runtime Architecture
Introduces Apache Spark, covering its architecture, RDDs, transformations, actions, fault tolerance, deployment options, and practical exercises in Jupyter notebooks.
Digital Urban History: QGIS Practical Session
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Data Visualization Techniques: Applications and Principles
Discusses data visualization techniques, emphasizing their applications and principles for effective communication of complex information.
Data Science Essentials: Pandas, Numpy, Matplotlib
Introduces Pandas, Numpy, and Matplotlib for data analysis and visualization in Python.
Excel Exercise: Trends
Explores trend analysis in Excel using rent data from 1995 to 2023.
Data Wrangling Techniques: HBase and Hive Integration
Covers data wrangling techniques using HBase and Hive, focusing on integration and practical applications.
Introduction to Data Stream Processing: Concepts and Applications
Covers the principles of data stream processing and its applications in real-time data analysis.
Collaborative Data Science: Tools and Techniques
Introduces collaborative data science tools like Git and Docker, emphasizing teamwork and practical exercises for effective learning.
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