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Computational aspects of AI for environmental sciences
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Data structures, data models & data patterns
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Lessons

Intro Part I - Data science and big data analytics

2:35

Web accessible data & data publications

8:58

Pythons request library

7:27

Some hints for good data management

10:41

The netCDF file format

6:39

The role of metadata

4:00

Work with netCDF data in Python

6:32

Intro Part II - Data science and big data analytics

1:07

Types of data in Earth system science

6:29

5 "V" of Earth system data types

10:56

How to cope with > 1 TByte of data

1:33

Intro Part III - Data science and big data analytics

1:50

Challenges of large-scale data analysis and data system architectures

6:15

Data structures, data models & data patterns

4:45

Classic design patterns

14:10

Modern design patterns

15:20

Hadoop & MapReduce

6:29

Data structures, data models & data patterns

Data come in many different ways and formats. Relevant for Earth sciences are the following data types: unstructured data, point clouds, series and time series, tree structures, relational tables, graphs, gridded data, images and videos. Data structures and formats influence access patterns and access speed.

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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