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Program Chair
Swagatam Das
Program Coordinator
Partha Pratim Mohanta
Advisory Committee
Sanghamitra Bandyopadhyay
Bhabatosh Chanda
Dipti Prasad Mukherjee
Naqueeb Ahmad Warsi
Pinakpani Pal
Gautam Paul
Sumana Ghosh
Utpal Garain
Debapriyo Majumdar
Organizing Chairs
Anish Chakrabarty
Faizanuddin Ansari
Kushal Bose
Srinjoy Roy
Priyobrata Mondal
Arghya Pratihar
Administrative Chairs
Aniruddha Mondal
Debanjan Dutta
Arghya Pratihar
Finance Chairs
Dipesh Chanda
Dilip Kumar Gayen
Chandra Sekhar Das
Sourav Chakraborty
Speakers
Professors, Scientists,
Post-docs, and Research Scholars from ISI, other eminent institutions and R&D labs
Organizing Committee
Aniruddha Mandal
Ayanabha Dasgupta
Bhaskar Pramanik
Ganesh Agarwal
Mayank Deora
Pritam Mukherjee
Subhajit Saha
Samujjal Ghosh
Shinjon Chakraborty
Indronil Ojha
External Advisory Committee
Aditya Panda
Avisek Gupta
Bikash Santra
Sankha Subhra Mullick
Shounak Dutta
Susmita Ghosh
Web Chairs
Pritam Mukherjee
Subhajit Saha
Dilip Kumar Gayen
Aniruddha Mandal
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The Objective: The Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata is organizing the 5th Winter School on Deep Learning - From Amateur to Connoisseur: A Journey Transforming Perceptrons to Agents. This winter school will focus heavily on developing solutions ranging from basic to advanced real-world challenging problems with main focus on hands-on sessions, in addition to making associated theory easy to understand. Participants will learn from the basics of machine learning to the advanced deep learning-based approaches with application to Computer Vision and Natural Language Processing including Agents. Theoretical lectures will be delivered by renowned professors and scientists (from ISI and other esteemed organizations) who have made significant contributions in their area of research. The lectures will be supplemented by meticulous hands-on sessions instructed by post-docs and research scholars.
Course Coverage: The 5th winter school will have the following course structure (theory & associated hands-on)
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Basics of Python and Libraries of Importance.
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Rudiments of Probability Theory for Machine Learning.
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Basics of Deep Learning Library: PyTorch.
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Essentials of Matrix Calculus and Linear Algebra for Machine Learning.
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Bird’s Eye View of Machine Learning.
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Primer on Text, Video, and Image Data processing.
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Gradient-based Optimization techniques.
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Rudiments of Artificial Neural Networks and Backpropagation.
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Steps towards Deep Learning: Activation, Normalization, Regularization, Loss functions.
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Convolutional Neural Networks, Architectures of Deep Neural Network Models.
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Physics Informed Neural Network
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Generative Deep Neural Network Models: GANs, VAEs, and Diffusion.
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Recurrent Neural Networks and Backpropagation through Time.
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Attention Mechanism and Transformers.
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Introduction to Graph Neural Networks.
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Introduction to Topological Data Analysis.
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Explainable and Trustworthy Artificial Intelligence.
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Emerging Learning strategies: Contrastive learning, Semi-supervised, zero/few-shot learning, Causal learning, etc.
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Adversarial Attacks, Defence, and Robust Deep Neural Network Models.
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Deep Reinforcement Learning.
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Large Language Models, In-Context Learning, Expressiveness of LLMs.
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Agentic AI, Prompt Engineering, RAG.
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LLM Reasoning, Trustworthiness.
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A Day-Long Real-World Project Implementation.
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Problem Framing and Goal Definition
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System Architecture and Agent Design
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Data Acquisition and Environment Setup
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Implementation and Workflow Orchestration
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Testing, Evaluation, and Iterative Improvement
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Deployment, Ethics, and Future Scalability
Mode of Tutorials: Lectures and Hands-on sessions will be conducted in online mode only. All sessions will be on Fridays, Saturdays and Sundays and the recordings will be shared with all participants.
Who Can Apply?
Professionals from academia and industry, research/project scholars, masters and final-year bachelors students. Interested candidates must visit the site
https://sites.google.com/view/wsdl26.
Important Dates:
Registration Window: December 03 – December 31, 2025
Course Duration: January 16 – March 08, 2026
For application, registration fees and other details:
https://sites.google.com/view/wsdl26/apply
Contacts:
E-mail: wsdl.ecsu2026@gmail.com
Phone: (+91) 033 2575 2915 (ECSU 912); (+91) 917003251611 (Shinjon)
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