Machine Learning For Earth System Sciences

COURSE DURATION :8 Weeks

@VTU COE

5.0
(1) 225 Students
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What you will learn

  • Computer Science and Engineering

This course will start with a gentle recapitulation of relevant concepts of spatio-temporal statistics and data mining, following which it will take up the topics of earth system observations, earth system data analytics and earth system modeling in various domains, such as hydrology, climate and soil.

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Lecture 06 : Extreme Events
Preview 28:58
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Lecture 07 : Extreme Value Theory
Preview 34:30
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Lecture 08 : Causality
Preview 32:20
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Lecture 09 : Networks
Preview 31:37
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Lecture 10 : Data Assimilation
Preview 30:40

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Lecture 11 : Challenges and Opportunities for ML in ESS
Preview 29:56
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Lecture 12 : Types of Machine Learning Problems in ESS
Preview 33:00
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Lecture 13 : Convolutional Networks for Spatial Problems
Preview 34:07
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Lecture 14 : Sequential Models for Temporal Problems
Preview 29:13
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Lecture 15 : Probabilistic Models for Earth System Science
Preview 32:22

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Lecture 16 : Identification of Indian Monsoon Predictors
Preview 30:54
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Lecture 17 : Statistical Downscaling of Rainfall with Machine Learning
Preview 33:32
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Lecture 18 : Detection of Anomaly and Extreme Events
Preview 32:58
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Lecture 19 : Identifying Causal Relations from Time-Series - 1
Preview 30:49
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Lecture 20 : Identifying Causal Relations from Time-Series - 2
Preview 33:41

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Lecture 21 : Spatio-Temporal Modelling of Extremes
Preview 37:00
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Lecture 22 : Hierarchical Bayesian Models for Spatio-Temporal Processes
Preview 28:16
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Lecture 23 : Geostatistical modelling for mapping based on in-situ measurements
Preview 35:53
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Lecture 24 : Nowcasting of Extreme Weather Events
Preview 32:47
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Lecture 25 : Discovering Clustered Weather Patterns
Preview 36:35

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Lecture 26 : Interpretable Machine Learning for Earth System Science
Preview 37:42
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Lecture 27 : Object Detection in Satellite Imagery
Preview 37:42
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Lecture 28 : Object Detection in Satellite Imagery - 2
Preview 34:21
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Lecture 29 : Image Fusion from Multiple Sources for Remote Sensing
Preview 35:53
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Lecture 30 : Image Segmentation for Remote Sensing
Preview 33:24

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Lecture 31 : Satellite Imagery as a Proxy for Geophysical Measurements
Preview 33:58
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Lecture 32 : Precipitation Nowcasting from Remote Sensing
Preview 36:17
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Lecture 33 : Deep Domain Adaptation for Remote Sensing
Preview 36:37
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Lecture 34 : Introduction to Earth System Modelling
Preview 36:00
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Lecture 35 : Stochastic Weather Generator
Preview 37:55

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Lecture 36 : Physics-Inspired Machine Learning for Process Models - 1
Preview 37:55
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Lecture 37 : Physics-Inspired Machine Learning for Process Models - 2
Preview 36:06
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Lecture 38 : Parameterizations for Sub-Grid Processes Using ML
Preview 39:31
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Lecture 39 : Data Assimilation for Earth System Model Correction
Preview 36:58
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Lecture 40 : ML for Climate Change Projection & Course Conclusion
Preview 39:56
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Rajath Arikeri

when will i get the exam

7 months ago
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Rajath Arikeri

when will i get the exam

7 months ago
0
img
Rajath Arikeri

when will i get the exam

7 months ago
0
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Devarala Siva sai gandhi

even i didnot get

7 months ago
0

5.0

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Pooja N M

8 months ago

When I will receive certificate

Meet Your Instructor
@VTU COE
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Instructor
3.4 Rating
19056 Students
902 Courses
About Instructor

VTU is one of the largest Technological Universities in India with 24 years of Tradition of excellence in Engineering & Technical Education, Research and Innovations. It came into existence in the year 1998 to cater the needs of Indian industries for trained technical manpower with practical experience and sound theoretical knowledge.

video

Free

  • Course Duration
    22 h 17 m 8 s
  • Course Level
    Intermediate
  • Student Enrolled
    225
  • Language
    English
This Course Includes
  • 22 h 17 m 8 s Video Lectures
  • 2 Quizzes
  • 0 Assignments
  • 0 Downloadable Resources
  • Full Lifetime Access
  • Certificate of Completion