Discover how deep learning is revolutionizing Earth observation, enabling the analysis of massive NetCDF files and predicting anomalies in environmental data.
Climate anomalies such as heatwaves, floods, droughts, and extreme precipitation events are increasing in frequency and intensity due to climate change. Accurate prediction of these anomalies requires models that can capture complex spatial patterns and temporal dynamics across large-scale environmental datasets.
This workshop focuses on the application of spatiotemporal deep learning techniques to climate anomaly prediction. Participants will explore how advanced AI models—including CNNs, RNNs, LSTMs, ConvLSTMs, Transformers, and Graph Neural Networks—can be used to analyze satellite imagery, geospatial datasets, and time-series climate data.
The aim of this workshop is to equip participants with the theoretical foundations and practical skills required to design, implement, and evaluate spatiotemporal deep learning models for accurate climate anomaly prediction.
📅 Day 1 — The Setup & Data Prep
📅 Day 2 — The Core AI / Tech Implementation (ConvLSTM)
📅 Day 3 — Tangible Output & Paper Readiness
March 13, 2026
IST 04:30 PM IST
March 13, 2026 – March 15, 2026
IST 05:30PM IST
Analyze and preprocess climate and geospatial time-series datasets
Develop spatiotemporal deep learning models for anomaly detection
Implement CNN, LSTM, Transformer, and hybrid architectures for climate forecasting
Build a prototype AI-based climate anomaly prediction system
Evaluate model accuracy, uncertainty, and interpretability for real-world applications
Apply AI-driven insights to support climate risk assessment and resilience planning
₹2,499
$50
The live sessions of this workshop are over, so the live fees no longer apply. The recordings are being uploaded. They appear in your dashboard as soon as they are ready, and we will e-mail you then.
Yes. Paid participants get the session recordings and study material in their NanoSchool dashboard (My registrations → Recorded Lectures / Study Material).
Watch the recording in your dashboard and send your questions to the mentor through the support desk.
Yes, an e-certificate of participation after the workshop, with a QR code anyone can verify and an "Add to LinkedIn" button.
Choose the category that matches your current role: Student, Ph.D. Scholar / Researcher, Academician / Faculty or Industry Professional.
By card, UPI or PayPal on the payment page; international bank transfer is also available there.
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Registration open
Live, mentor-led and certified. Dates and times in IST.
