Deep Learning for Natural Language Processing Course | IIT Kharagpur
Course Details
| Exam Registration | 1526 |
|---|---|
| Course Status | Ongoing |
| Course Type | Elective |
| Language | English |
| Duration | 12 weeks |
| Categories | Computer Science and Engineering, Data Science, Artificial Intelligence |
| Credit Points | 3 |
| Level | Undergraduate/Postgraduate |
| Start Date | 19 Jan 2026 |
| End Date | 10 Apr 2026 |
| Enrollment Ends | 02 Feb 2026 |
| Exam Registration Ends | 20 Feb 2026 |
| Exam Date | 24 Apr 2026 IST |
| NCrF Level | 4.5 — 8.0 |
Unlock the Power of Language with Deep Learning
Natural Language Processing (NLP) is the driving force behind today's most innovative technologies—from intelligent chatbots and real-time translation to sophisticated search engines and content summarizers. At the heart of this revolution lies Deep Learning, which has become the default framework for tackling complex NLP challenges. If you're looking to build a career at this exciting intersection, a structured, expert-led course is invaluable.
We are thrilled to present a detailed overview of the 12-week course "Deep Learning for Natural Language Processing," instructed by the renowned Prof. Pawan Goyal from IIT Kharagpur. This course is meticulously designed to take you from foundational concepts to the cutting-edge techniques powering modern AI.
About the Instructor: Learn from an Award-Winning Expert
Gaining knowledge from a leading researcher provides unparalleled insight. Your guide for this journey is Prof. Pawan Goyal, an Associate Professor at the Department of Computer Science and Engineering, IIT Kharagpur.
- Education & Background: B.Tech from IIT Kanpur, PhD from the University of Ulster, UK, and post-doctoral research at INRIA Paris.
- Research Excellence: His work focuses on Natural Language Understanding, Information Retrieval, and Sanskrit Computational Linguistics, published in top-tier conferences like ACL, EMNLP, SIGIR, and AAAI.
- Prestigious Recognition: Recipient of the Google India AI/ML Research Award 2020 and the INAE Young Engineers Award 2020.
Learning from an instructor of this caliber ensures you grasp not just the "how," but also the "why" behind the algorithms.
Who Should Take This Course?
This course is crafted for motivated learners ready to dive deep into NLP.
- Intended Audience: Advanced Undergraduate and Postgraduate students in Computer Science, Data Science, or related fields.
- Prerequisites: A foundational course in Machine Learning and basic proficiency in Python programming.
- Industry Support: The curriculum is highly relevant for roles at tech giants like Google, Microsoft, Amazon, Flipkart, and Adobe.
Course Overview: A 12-Week Journey from Fundamentals to Frontiers
The course layout is a comprehensive progression, blending theory with hands-on practice. Here’s a breakdown of what you will master each week:
| Week | Core Topics |
|---|---|
| Week 1-2 | Foundations: Introduction to NLP tasks, n-gram models, and core Deep Learning concepts like Neural Networks and Representation Learning. |
| Week 3-4 | Word & Sequence Models: Dive into Word2Vec, GloVe, and fastText. Understand Recurrent Neural Networks (RNNs, LSTMs, GRUs) for sequence labeling and generation. |
| Week 5-6 | The Transformer Revolution: Learn the Attention mechanism, the Transformer architecture, and Self-Supervised Learning with models like BERT, GPT, and T5. |
| Week 7 | Real-World Applications: Apply knowledge to Question Answering, Dialog Modeling, Text Summarization, with extensions for Indian languages. |
| Week 8-12 | Large Language Models (LLMs) & Beyond: Explore instruction fine-tuning, RLHF, in-context learning, Parameter-Efficient Fine-Tuning (PEFT like LoRA), Retrieval-Augmented Generation (RAG), and crucial topics like interpretability and ethics. |
Why This Course is Essential for Your AI Career
This course stands out by offering a holistic view of the NLP landscape:
- From Theory to Practice: It moves seamlessly from classic n-gram models to the latest LLM fine-tuning techniques, ensuring you understand the evolution of the field.
- Hands-On Mastery: Dedicated tutorials will help you translate theoretical knowledge into practical code, a critical skill for industry roles.
- Focus on Modern Paradigms: It dedicates significant time to crucial modern topics like Prompt Engineering, RLHF, PEFT, and RAG, which are essential for working with state-of-the-art models like GPT-4 and Claude.
- Ethical Foundation: The course concludes with a critical look at analysis, interpretability, and ethical considerations, preparing you to develop responsible AI.
Your Primary Learning Resource
The course aligns with the definitive textbook in the field: "Speech and Language Processing" by Daniel Jurafsky & James H. Martin (3rd Edition). This resource will provide deep dives and supplementary material to enhance your understanding.
Ready to Transform Your Understanding of NLP?
Whether you aim to contribute to groundbreaking research or build the next generation of AI products, a strong command of Deep Learning for NLP is non-negotiable. This 12-week course, under the guidance of Prof. Pawan Goyal, offers a structured, rigorous, and up-to-date pathway to gain that expertise. Take the first step towards mastering the language of AI.
Enroll Now →