About Workshop
AI-Driven Ocean Prediction, Climate Forecasting, and Marine Intelligence is a 3-day hands-on workshop designed to introduce participants to the use of artificial intelligence and open-source data tools for ocean and climate analysis.
The workshop focuses on practical learning through ocean and climate dataset exploration, marine data preprocessing, AI-based prediction, climate time-series forecasting, risk mapping, and marine decision-support applications. Participants will work with tools such as Google Colab / Jupyter Notebook, Python, Pandas, NumPy, Matplotlib, Xarray, NetCDF4, and Scikit-learn.
Aim
The aim of this workshop is to provide participants with practical knowledge of how artificial intelligence and open-source ocean data tools can be used for ocean prediction, climate forecasting, and marine intelligence.
What Participants Will Learn
- To introduce participants to the fundamentals of ocean prediction, climate forecasting, and marine intelligence.
- To help participants understand key marine and climate variables such as sea surface temperature, salinity, wind, waves, rainfall, pressure, and ocean currents.
- To provide practical exposure to ocean and climate datasets from sources such as NOAA, NASA, Copernicus Marine, ERA5, buoy data, satellite data, and Argo floats.
- To train participants in handling NetCDF, time-series, and geospatial ocean datasets.
- To enable participants to preprocess, clean, visualize, and interpret marine and climate data using open-source tools.
Structure
📅 Day 1: Ocean & Climate Data Foundations
- Role of ocean prediction in climate resilience, disaster preparedness, fisheries, shipping, and coastal planning
- Key marine and climate variables: sea surface temperature, salinity, wind, waves, rainfall, pressure, and ocean currents
- Introduction to satellite, buoy, Argo float, NOAA, NASA, Copernicus Marine, and ERA5 datasets
- Basics of NetCDF, time-series, and geospatial ocean data
- Data preprocessing, visualization, and pattern identification for marine intelligence
🛠️ Hands-on 1: Ocean & Climate Dataset Exploration
- Participants will explore real/sample marine datasets, understand variables, coordinates, and time dimensions, and visualize ocean-climate patterns.
🛠️ Hands-on 2: Marine Data Visualization & Preprocessing
- Participants will clean data, handle missing values, plot trends, and create basic maps or time-series visualizations for selected ocean variables.
📅 Day 2: AI Models for Ocean Prediction & Climate Forecasting
- AI workflow for ocean and climate prediction
- Feature selection for marine forecasting variables
- Machine learning models for sea surface temperature, wave height, wind speed, rainfall, and ocean-current prediction
- Time-series forecasting using ML and deep learning approaches
- Model evaluation using error metrics and prediction visualization
- Challenges: uncertainty, data gaps, bias, and model reliability in climate forecasting
🛠️ Hands-on 1: Ocean Variable Prediction Using AI Models
- Participants will build a basic machine learning model to predict a marine or climate variable such as sea surface temperature, wave height, wind speed, or rainfall.
🛠️ Hands-on 2: Climate Time-Series Forecasting Notebook
- Participants will create a simple forecasting workflow, compare predicted and actual values, and interpret model performance.
📅 Day 3: Marine Intelligence, Risk Mapping & Decision Support
- AI for marine intelligence, coastal risk, cyclone monitoring, flood prediction, and early warning systems
- Marine heatwave detection, anomaly identification, and climate impact assessment
- Applications in fisheries, biodiversity, shipping, offshore operations, and coastal management
- Explainable AI for interpreting ocean and climate models
- Digital twins, physics-informed AI, generative AI, and future trends in ocean forecasting
- Real-world deployment challenges in marine and climate intelligence systems
🛠️ Hands-on 1: Marine Risk Mapping & Climate Impact Visualization
- Participants will create simple risk maps or anomaly visualizations such as sea surface temperature anomalies, high-wave zones, or marine heatwave indicators.
🛠️ Hands-on 2: Mini Project: AI-Based Ocean or Climate Forecasting
- Participants will complete a guided mini project by selecting a dataset, preprocessing it, building a prediction or visualization workflow, and interpreting results for real-world marine decision-making.
🧰 Tools Used in the Workshop
- Google Colab, Python, Pandas, Xarray, Scikit-learn
Important Dates
Registration Ends
04: 00 PM
Workshop Dates
2026-05-08
05:30 PM
05:30 PM
What You Will Gain
- 3 days of expert-led live sessions
- Hands-on notebooks for ocean data analysis, AI modeling, forecasting, and risk mapping
- Practical training using Google Colab / Jupyter Notebook, Python, Pandas, NumPy, Matplotlib, Xarray, NetCDF4, and Scikit-learn
- Sample ocean and climate datasets for practice
- Minimum two hands-on activities per day
- Guided mini project on AI-based ocean or climate forecasting
- Time-series plots, prediction outputs, anomaly charts, and simple risk maps
- Session notes, tool links, and practice resources
- Certificate of participation / completion from NSTC/NanoSchool
Outcomes
- Understand the role of AI in ocean prediction, climate forecasting, and marine intelligence.
- Identify and interpret key marine and climate variables such as sea surface temperature, salinity, wind, waves, rainfall, pressure, and ocean currents.
- Explore ocean and climate datasets from sources such as NOAA, NASA, Copernicus Marine, ERA5, satellite data, buoy data, and Argo floats.
- Work with NetCDF, time-series, and geospatial ocean data using open-source tools.
- Preprocess, clean, and visualize marine datasets for ocean and climate analysis.
- Use Python, Pandas, NumPy, Matplotlib, Xarray, NetCDF4, and Scikit-learn for hands-on ocean data workflows.
Who Should Attend
- PhD scholars, research scholars, and postgraduate students from science, engineering, environmental science, climate science, oceanography, marine science, and related fields.
- Researchers, academicians, faculty members, and industry professionals interested in AI applications for ocean and climate systems.
- Professionals working in climate analytics, environmental monitoring, disaster management, coastal planning, fisheries, shipping, offshore operations, or sustainability.
- Students and learners interested in AI, machine learning, climate forecasting, ocean data analysis, and marine intelligence.
- Basic knowledge of Python, data analysis, or machine learning will be helpful but is not mandatory.
- Prior experience with oceanography or climate science is useful, but beginners with interest in the topic can also participate.
Deliverables
- 3 days of expert-led live sessions
- Hands-on notebooks for ocean data analysis, AI modeling, forecasting, and risk mapping
- Practical training using Google Colab / Jupyter Notebook, Python, Pandas, NumPy, Matplotlib, Xarray, NetCDF4, and Scikit-learn
- Sample ocean and climate datasets for practice
- Minimum two hands-on activities per day
- Guided mini project on AI-based ocean or climate forecasting
- Time-series plots, prediction outputs, anomaly charts, and simple risk maps
- Session notes, tool links, and practice resources
- Certificate of participation / completion from NSTC/NanoSchool