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DSTC-HISTO-2608 Open Online Doctoral / R&D Specialist 3 Days · Live + Recorded

Deep Learning for Histopathology Image Analysis

by - DSTC

Apply CNNs and transformers to whole-slide images for computational pathology.

Starting from ₹1,499+GST

Register Now

Core Parameters

Level:
Doctoral / R&D Specialist
Duration / Workload:
3 Days · Live + Recorded (12 Hrs Total)
Venue Mode:
Online
Prerequisites:
PhD candidates, postdoctoral researchers, academic faculty, and industry R&D teams.

📅 Important Schedule Dates (Tentative)

Session Commencement (Tentative):
29 Aug 2026 · 8:00 PM IST
Session Conclusion (Tentative):
31 Aug 2026 · 8:00 PM IST
Enrollment Deadline (Tentative):
28 Aug 2026
Schedule Note: This schedule is tentative and subject to minor adjustments. Once the program registrations go live, all finalized dates and times will be sent to registered interest leads.

🎯 Program Aim

Participants learn to build deep-learning pipelines for histopathology whole-slide images, covering tiling, model training, and interpretability for computational pathology.

📋 Workshop Objectives

Handle whole-slide images and tiling
Build CNN/transformer classifiers
Apply transfer learning to tissue data
Address class imbalance and stain variation
Interpret models with attention/Grad-CAM

👥 Who Should Enroll?

Computational pathology researchers
Medical-imaging data scientists
PhD scholars in AI for healthcare
Digital-pathology R&D teams

🚀 Key Learning Outcomes

A histopathology classification pipeline
WSI preprocessing and tiling skills
Model interpretability outputs
Verified e-Certificate of Industrial Competency

💎 What You'll Gain from this Program

🎥
Live & Recorded Sessions
Lifetime access to class recordings
🎓
e-Certificate upon Completion
Cryptographically verified credentials
💬
Post-Workshop Query Support
Direct chat access to mentors & council
💻
Hands-On Learning Experience
Step-by-step Jupyter notebooks & code

Curriculum Outline

Day 1 Data

Whole-Slide Images

WSI formats, tiling, stain normalization and dataset construction.

Day 2 Modeling

CNNs & Transformers

Transfer learning, augmentation and handling class imbalance.

Day 3 Interpretation

Explainable Pathology

Attention maps, Grad-CAM and clinical validation considerations.

Apply CNNs and transformers to whole-slide images for computational pathology.

Participants learn to build deep-learning pipelines for histopathology whole-slide images, covering tiling, model training, and interpretability for computational pathology.

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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.
📄 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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