Is programming experience required?

Yes, intermediate Python and PyTorch proficiency is expected to complete the assignments.

Will we get access to GPU clusters?

Yes, all registered scholars will receive sandbox access to cloud GPU environments for the duration of the practical modules.

💻 Software & Environment Setup

Bioinformatics & Computational Biology

The computational toolchain and environment used throughout Industrial Deep Learning & Bio-Sequence Modeling.

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# Recommended conda environment
conda create -n dstc_env python=3.11 -y
conda activate dstc_env
pip install biopython pandas pysam scikit-bio

Biopython
Sequence I/O, BLAST parsing, phylogenetics

SAMtools / BCFtools
Alignment & variant file manipulation

Bioconductor (R)
DESeq2, edgeR & limma for expression analysis

Nextflow
Reproducible, portable NGS pipelines

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 Industrial Deep Learning & Bio-Sequence Modeling

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

View full course →

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.