Global Academic Alliance

πŸ›οΈ Official Portal of the Deep Science and Technology Consortium | Global Academic Alliance
DSTC-00550 Online (e-LMS) Graduate / Intermediate

Artificial Intelligence for Smart Energy Grids Course

by - DSTC

Master Artificial Intelligence for Smart Energy Grids in 4 weeks through hands-on, project-based online training with DSTC.

β˜…β˜…β˜…β˜…β˜… Be the first to review β€’ 4 Weeks Β· 40 hrs β€’ e-Certificate Included
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From β‚Ή5,500 + GST

πŸ’» Software & Environment Setup

AI & Machine Learning in Healthcare

The computational toolchain and environment used throughout Artificial Intelligence for Smart Energy Grids Course.

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# 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 Artificial Intelligence for Smart Energy Grids Course

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

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Scholar Registration

For scholars whose department, college or employer pays the fee. We raise a proforma invoice to your institution; you attach the signed processing letter or bank slip.

The proforma invoice is emailed here as well as to you.
πŸ“„ Upload Sponsorship Slip / Letter

Signed letter on official letterhead, or the bank transfer slip. PDF/JPG/PNG, up to 5 MB.

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