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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The Machine Learning for Earth System Sciences certification course offers a comprehensive exploration of spatio-temporal statistics and data mining, focusing on their applications in earth system sciences. Intended for final-year undergraduates, postgraduates, and research students, it covers earth system observations, data analytics, and modelling in domains like hydrology and climate.

Prerequisites include mandatory machine learning knowledge, optional deep learning expertise, and a working understanding of earth system science domains. The Machine Learning for Earth System Sciences certification by Swayam caters to both undergraduate and postgraduate levels, fostering a solid grasp of statistical concepts in analysing earth system phenomena.

Also Read: Online Machine Learning Certification Courses

The Highlights

Elective Online Course
8 Weeks Duration
Offered by IIT Kharagpur

Programme Offerings

Certificate of completion
Practical Learning
Hands-on Experience

Courses and Certificate Fees

Fees Informations	Certificate Availability	Certificate Providing Authority
INR 1000	yes	IIT Kharagpur

The Machine Learning for Earth System Sciences certification fees is free. However, if you want a certificate, you must register and take the proctored exam at designated centres, which is optional and comes with a fee of Rs 1000.

Machine Learning for Earth System Sciences Certification Fee Structure

Particulars	Total Fees
Machine Learning For Earth System Sciences (exam)	Rs 1000/-

Eligibility Criteria

Academic Qualifications

The Machine Learning for Earth System Sciences certification course is intended for students in their final year of undergrad studies, postgraduates, and research students, requiring a basic understanding of machine learning, with deep learning being optional, and familiarity with one or two earth system science domains.

Certification Qualifying Details

To receive the Machine Learning for Earth System Sciences certification by Swayam, you need a minimum average assignment score of 10/25 and an exam score of 30/75.

What you will learn

After completing the Machine Learning for Earth System Sciences certification syllabus, you will gain a thorough understanding of spatio-temporal statistics and data mining concepts, establishing a strong foundation for subsequent topics. You will also delve into the practical applications of the concepts in earth system sciences, covering hydrology, climate, and soil.

Upon completion of the Machine Learning for Earth System Sciences training, you will gain the skills to effectively analyse earth system observations, perform data analytics, and create models that contribute to a nuanced understanding of complex phenomena.

Who it is for

GIS ExpertData ScientistAtmospheric ScientistRemote Sensing TechnicianEnvironmental ScientistResearch Scientist

The Machine Learning for Earth System Sciences online course is suitable for individuals interested in the intersection of computer science and earth system sciences. This course is particularly suitable for:

Admission Details

Follow these steps to join the Machine Learning for Earth System Sciences classes:

Step 1: Browse the URL below:

https://onlinecourses.nptel.ac.in/noc23_cs86/preview

Step 2: Click on the “Sign-in/ Register” button

Step 3: Fill out the necessary details and submit the form

The Syllabus

Evaluation process

The Machine Learning for Earth System Sciences certification offers an optional exam. Your final score is determined by averaging the best 8 out of 12 assignments (25%) and your proctored exam score (75%).

IIT Kharagpur Frequently Asked Questions (FAQ's)

1: What are the prerequisites for enrolling in the Machine Learning for Earth System Sciences online course?

Mandatory prerequisites include a solid understanding of machine learning, while familiarity with deep learning is optional. Additionally, participants should have a working knowledge of earth system sciences.

2: What is the duration of the Machine Learning for Earth System Sciences training, and is it suitable for both undergraduates and postgraduates?

The course spans 8 weeks. It is designed to cater to both undergraduate and postgraduate students, providing a comprehensive learning experience for participants at different academic levels

3: How is the Machine Learning for Earth System Sciences online course structured, and what topics are covered?

The course explores spatio-temporal statistics and data mining concepts. It then covers topics such as earth system observations, data analytics, and modelling in domains like hydrology, climate, and soil.

4: What practical skills will I gain from the Machine Learning for Earth System Sciences certification course?

Participants will acquire practical skills in applying spatio-temporal statistics and data mining to analyse earth system observations. The course emphasises hands-on experience in data analytics and modelling.

5: How does the Machine Learning for Earth System Sciences certification contribute to academic credentials?

Upon successful completion, participants will earn 2 credit points, enhancing their academic credentials. This recognition highlights the proficiency gained in applying statistical methodologies to address challenges within the earth system.