KI:STE E-Learning

Computational aspects of AI for environmental sciences

How to cope with > 1 TByte of data

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Lessons

Intro Part I - Data science and big data analytics

Web accessible data & data publications

Pythons request library

Some hints for good data management

The netCDF file format

The role of metadata

Work with netCDF data in Python

Intro Part II - Data science and big data analytics

Types of data in Earth system science

5 "V" of Earth system data types

How to cope with > 1 TByte of data

Intro Part III - Data science and big data analytics

Challenges of large-scale data analysis and data system architectures

Data structures, data models & data patterns

Classic design patterns

Modern design patterns

Hadoop & MapReduce

How to cope with > 1 TByte of data

This final section of part 2 provides a glimpse on tools and techniques for working with really large datasets.

Lecturer

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PD Dr. Martin Schultz

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Additional Material

Additional Material

Additional Material

Git Repository with Jupyter Notes

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Forschungszentrum Jülich Aachen University RWTH University of Cologne University of Bonn

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