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DSTC-00092 Online (e-LMS) Graduate / Intermediate

Unlock Wind & Solar Potential with Physics-Informed Neural Networks (PINNs)

by - DSTC

Model wind and solar with physics-informed neural networks.

โ˜…โ˜…โ˜…โ˜…โ˜… Be the first to review โ€ข 4 Weeks ยท 40 hrs โ€ข e-Certificate Included
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From โ‚น2,500 + GST

๐Ÿ’ป Software & Environment Setup

AI & Machine Learning in Healthcare

The computational toolchain and environment used throughout Unlock Wind & Solar Potential with Physics-Informed Neural Networks (PINNs).

Unlock wind solar potential courseUnlock wind solar potential online trainingBest unlock wind solar potential certificationUnlock wind solar potential for researchersUnlock wind solar potential hands-on workshopLearn unlock wind solar potential
# Recommended conda environment
conda create -n dstc_env python=3.11 -y
conda activate dstc_env
pip install torch torchvision scikit-learn monai pydicom
PyTorch / TensorFlow
Deep-learning model training
MONAI
Medical-imaging deep-learning framework
scikit-learn
Classical ML, evaluation & pipelines
Weights & Biases
Experiment tracking & reproducibility
Supported OS: Linux (Ubuntu 22.04+), macOS, or Windows via WSL2.
Hardware: 16 GB RAM minimum; a CUDA GPU helps for deep-learning modules.

Earn government-registered certification in Unlock Wind & Solar Potential with Physics-Informed Neural Networks (PINNs)

e-Certificate and e-Marksheet issued on successful completion.

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Scholar Registration

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