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DSTC-00342 Online (e-LMS) Graduate / Intermediate

Digital Twins: Predictive Modeling for Dynamic Industrial Processes

by - DSTC

Model dynamic industrial processes with digital twins.

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

Data Science & Analytics

The computational toolchain and environment used throughout Digital Twins: Predictive Modeling for Dynamic Industrial Processes.

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# Recommended conda environment
conda create -n dstc_env python=3.11 -y
conda activate dstc_env
pip install numpy pandas scikit-learn matplotlib seaborn
Python 3.11 + Jupyter
Interactive analysis notebooks
pandas / NumPy
Data wrangling & numerics
scikit-learn
Modelling & evaluation
Plotly / Seaborn
Statistical visualisation
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 Digital Twins: Predictive Modeling for Dynamic Industrial Processes

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

View full course โ†’

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.
๐Ÿ“„ 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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