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Covers best practices and guidelines for big data, including data lakes, architecture, challenges, and technologies like Hadoop and Hive.

Data Visualization: Techniques, Tools & Concepts

Covers data visualization techniques, tools, and concepts for effective data representation.

Principal Component Analysis: Dimension Reduction

Covers Principal Component Analysis for dimension reduction in biological data, focusing on visualization and pattern identification.

Google Earth Engine: Analyzing Geospatial Data

Introduces Google Earth Engine, focusing on its capabilities for geospatial analysis and environmental monitoring.

Super-vision: Celebrating EPFL's Doctoral Theses History

Explores EPFL's doctoral theses history, data visualization, and the innovative D3 approach.

Data Science for Engineers: Part 2

Explores data manipulation, exploration, and visualization in data science projects using Python.

Advanced Pandas Functions

Focuses on advanced pandas functions for data manipulation, exploration, and visualization with Python, emphasizing the importance of understanding and preparing data.

Data Analysis: KMnO4 Concentrations

Covers the analysis of KMnO4 concentrations using data from a CSV file.

Data Visualization: Techniques and Applications

Explores data visualization techniques, design impact, and interactive applications for effective information communication.

Introduction to Spark Runtime Architecture

Introduces Apache Spark, covering its architecture, RDDs, transformations, actions, fault tolerance, deployment options, and practical exercises in Jupyter notebooks.