Neural Networks for Computer Vision and Natural Language Processing

By Prof. Arijit Sur | IIT Guwahati

Learners enrolled: 3011 | Exam registration: 154

ABOUT THE COURSE:

Natural language processing (NLP) and computer vision (CV) have become increasingly significant due to their wide-ranging applications, such as language translation, speech recognition, image analysis, and automation in the healthcare, education, and transportation sectors. For under graduate and postgraduate college students, this course will offer a strong foundation in the concepts and techniques of deep learning, preparing them for advanced research and enhancing their employability in emerging technologies. Beginners in the industry will also benefit from practical insights into bridging theoretical knowledge with real-world applications, enabling them to contribute effectively to projects involving language and vision-based solutions. Faculty members will gain exposure to the latest developments and tools in the field, supporting their efforts to integrate cutting-edge topics into their teaching and research.

This course starts with fundamental machine learning concepts and will cover advanced deep learning techniques for modeling primary computer vision and NLP tasks. The course module design helps beginners understand the underlying neural network concepts and how to apply these networks to model different important NLP and vision tasks. Simple diagrammatic illustrations help students from various backgrounds understand complex learning models. The course contents are in massive demand in AI/ML-based IT industries.

INTENDED AUDIENCE: Final/Pre-final year B. Tech. (BE), M. Tech. (ME), PhD students

INDUSTRY SUPPORT: The IT industry is looking for AI/ML professionals.

Summary

Course Status :	Upcoming
Course Type :	Elective
Language for course content :	English
Duration :	12 weeks
Category :	Computer Science and Engineering Artificial Intelligence
Credit Points :	3
Level :	Undergraduate/Postgraduate
Start Date :	19 Jan 2026
End Date :	10 Apr 2026
Enrollment Ends :	26 Jan 2026
Exam Registration Ends :	13 Feb 2026
Exam Date :	25 Apr 2026 IST
NCrF Level	4.5 — 8.0

Note: This exam date is subject to change based on seat availability. You can check final exam date on your hall ticket.

Page Visits

Course layout

Week 1: Introduction to Machine Learning

Introduction to Learning
Machine Learning Fundamentals
Optimizing ML Models

Week 2: Deep Neural Network

Neural Network - Fundamentals
Introduction to Deep Learning

Week 3: Deep Model for Vision

Computer Vision through ML
Deep Learning Models

Week 4: Convolution Neural Network

CNN Architectures
Optimizing CNN
CNN with Residual Connections

Week 5: Sequential Modelling

Recurrent Neural Network
Neural Machine Translation

Week 6 & 7: Generative Models

Generative Modelling
Auto-regressive models
Variational Auto-Encoder
Generative Adversarial Network
Diffusion Models

Week 8: Large Language Model

Transformers
Language Modelling
Generative Pre-trained Transformer

Week 9: Zero and Few Shot Learning

Zero-Shot Learning
Few Shot Learning

Week 10: DL model for Image Enhancement

Image Enhancement
Deep Learning Models for Image Enhancing

Week 11: DL models for Image Classifications and Object Detection

Image Classification, Object Detection
DL Models for Image Classification, Object Detection.

Medical Imaging

Medical Image Analysis and Synthetic image generation

Week 12: Multimodal Analysis and Self-Supervised Learning

Deep models for multi-modal image and text modeling
Semi-supervised learning, contrastive learning
Self-supervised vision, and language modeling

Books and references

Text Books:

Neural Networks and Learning Machines, 3rd edition, Simon Haykin, Pearson Prentice Hall.
Link: https://www.dai.fmph.uniba.sk/courses/NN/haykin.neuralnetworks.3ed.2009.pdf
Deep Learning: By Ian Goodfellow and Yoshua Bengio and Aaron Courville, MIT Press, 2016
Link: https://www.deeplearningbook.org/

Reference Books:

Deep Learning for Computer Vision By Shanmugamani Rajalingappaa, Packt Publishing Limited
Deep Learning with Tensor Flow By Zaccone Giancarlo, Packt Publishing Limited

Instructor bio

Prof. Arijit Sur

IIT Guwahati

Prof. Arijit Sur received his Ph. D. degree from the Dept. of CSE, IIT Kharagpur, in 2010. Prof. Sur joined the Department of CSE, IIT Guwahati, as an Assistant professor in 2009 and is now a full professor there. His research mainly focuses on Deep Learning approaches to solving different Computer Vision ad NLP problems like image, video restoration, multi-modal image-text analysis, super-resolution, semantic segmentation, and change detection in various application domains like underwater vision, satellite and remote sensing image analysis, medical imaging, media forensics, etc. His group is also working on different machine learning-based problems like zero-shot learning, selfsupervised learning, robotic vision, and ML-based approaches for adaptive video streaming in a 5G environment. Prof. Sur founded a research project lab named "Multimedia Lab" in the Dept. of CSE in 2012. Ten research scholars are pursuing their Ph.D. work under his guidance; nine students have graduated. Dr. Sur has coauthored 40+ top-tier journal papers and more than 50 conference papers in different premier forums. Presently he is working as an Associate Editor of Multimedia Systems Journal, Springer.

Course certificate

The course is free to enroll and learn from. But if you want a certificate, you have to register and write the proctored exam conducted by us in person at any of the designated exam centres.

The exam is optional for a fee of Rs 1000/- (Rupees one thousand only).

Date and Time of Exams: April 25, 2026 Morning session 9am to 12 noon; Afternoon Session 2pm to 5pm.

Registration url: Announcements will be made when the registration form is open for registrations.

The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published. If there are any changes, it will be mentioned then.

Please check the form for more details on the cities where the exams will be held, the conditions you agree to when you fill the form etc.

CRITERIA TO GET A CERTIFICATE

Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100

Final score = Average assignment score + Exam score

Please note that assignments encompass all types (including quizzes, programming tasks, and essay submissions) available in the specific week.

YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.

Certificate will have your name, photograph and the score in the final exam with the breakup.It will have the logos of NPTEL and IIT Guwahati. It will be e-verifiable at nptel.ac.in/noc.

Only the e-certificate will be made available. Hard copies will not be dispatched.

Once again, thanks for your interest in our online courses and certification. Happy learning.

- NPTEL team