# Fundamentals of Generative AI and Large Language Models: Theory and Practice

- Institution: IISc Bangalore PES University RV University
- Department: Computer Science and Engineering
- Taught by: Prof. Sriram Ganapathy, Prof. Ashwini Kodipalli, Prof. Baishali Garai
- Level: Undergraduate
- Language: English
- Subjects: Computer science, Engineering
- Source: [NPTEL](https://nptel.ac.in/courses/106108002)
- Licence: [CC BY-NC-SA](https://nptel.ac.in/faq) (Non-commercial use only.)
- Syllabus: [at the source](https://nptel.ac.in/courses/106108002)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

This course provides a rigorous exploration of modern generative AI, covering latent-variable models such as Autoencoders, VAEs, GANs, and Diffusion Models that form the backbone of contemporary generative systems.

Learners will develop a deep understanding of probabilistic modeling, adversarial training dynamics, denoising diffusion processes, and latent space manipulation for high-fidelity data generation.

The sequence modeling module bridges classical NLP with modern architectures, introducing RNNs, LSTMs, and culminating in the Transformer framework that powers today’s Large Language Models.

Emphasis is placed on mathematical foundations, architectural intuition, and practical implementation using widely adopted deep learning libraries.

By the end of the course, learners will be equipped to analyze, design, and implement state-of-the-art generative models and LLM-based systems across diverse application domains.

Intended audience: UG and PG students of all the AICTE affiliated institutions

Prerequisites: Students must have completed introductory courses in Programming and Machine Learning/Deep Learning.Knowledge of Python and basic mathematical concepts is necessary to follow the hands-on exercises.

## Lectures

1. [Introduction to Generative AI](https://invisiblenetwork.ai/learn/nptel/106108002/b796bbc2d638) (YouTube)
2. [Activation Functions & Loss Functions in Deep Learning](https://invisiblenetwork.ai/learn/nptel/106108002/5b57cda5bbc1) (YouTube)
3. [Optimizers - Part A](https://invisiblenetwork.ai/learn/nptel/106108002/b729161e0868) (YouTube)
4. [Optimizers - Part B](https://invisiblenetwork.ai/learn/nptel/106108002/0f1ba0c0b5a8) (YouTube)
5. [Convolutional Neural Network - Part A](https://invisiblenetwork.ai/learn/nptel/106108002/1b150b85f215) (YouTube)
6. [Convolutional Neural Network - Part B](https://invisiblenetwork.ai/learn/nptel/106108002/149fc17ea3bc) (YouTube)
7. [Introduction to Google Colab](https://invisiblenetwork.ai/learn/nptel/106108002/394ead7b0611) (YouTube)
8. [Practical Exercise - 1](https://invisiblenetwork.ai/learn/nptel/106108002/c7a638af37f5) (YouTube)
9. [Practical Exercise - 2](https://invisiblenetwork.ai/learn/nptel/106108002/272ac8f54c5b) (YouTube)
10. [Introduction to Autoencoder](https://invisiblenetwork.ai/learn/nptel/106108002/fc293e35625e) (YouTube)
11. [Training objective: Reconstruction Loss (MSE, Binary Cross-Entropy)](https://invisiblenetwork.ai/learn/nptel/106108002/5929fb5c32ca) (YouTube)
12. [Types of Autoencoders: Architecture and Code-Level Understanding](https://invisiblenetwork.ai/learn/nptel/106108002/a8c9fbb9918d) (YouTube)
13. [Regularization Techniques in AE: Denoising](https://invisiblenetwork.ai/learn/nptel/106108002/ea81fb724cb5) (YouTube)
14. [Regularization Techniques in AE: Sparse](https://invisiblenetwork.ai/learn/nptel/106108002/50be39f5941e) (YouTube)
15. [Regularization Techniques in AE: Contractive](https://invisiblenetwork.ai/learn/nptel/106108002/23d135f3d705) (YouTube)
16. [Numerical Example, Limitations of AE](https://invisiblenetwork.ai/learn/nptel/106108002/85a905ed439f) (YouTube)
17. [Practical Exercise - 1](https://invisiblenetwork.ai/learn/nptel/106108002/fae4e0dfd8c3) (YouTube)
18. [Practical Exercise - 2](https://invisiblenetwork.ai/learn/nptel/106108002/e5864ace27dd) (YouTube)
19. [Intuition behind KL Divergence - Part A](https://invisiblenetwork.ai/learn/nptel/106108002/7c877f041dcf) (YouTube)
20. [Intuition behind KL Divergence - Part B](https://invisiblenetwork.ai/learn/nptel/106108002/3aaee7db7cb1) (YouTube)
21. [Introduction to VAE and the working of the Encoder](https://invisiblenetwork.ai/learn/nptel/106108002/4c27e3513f0d) (YouTube)
22. [Working of Probabilistic Decoder, ELBO, Loss Function of VAE](https://invisiblenetwork.ai/learn/nptel/106108002/b14b257196a6) (YouTube)
23. [Reparameterization Trick](https://invisiblenetwork.ai/learn/nptel/106108002/60c943603df9) (YouTube)
24. [Numerical Example](https://invisiblenetwork.ai/learn/nptel/106108002/969b266724ad) (YouTube)
25. [Practical Exercise - 1](https://invisiblenetwork.ai/learn/nptel/106108002/bc6245152d58) (YouTube)
26. [Entanglement, Disentanglement Latent Space, and Beta-VAE](https://invisiblenetwork.ai/learn/nptel/106108002/72fe4afaae44) (YouTube)
27. [Conditional VAE](https://invisiblenetwork.ai/learn/nptel/106108002/d35d767d4d14) (YouTube)
28. [Latent Space Interpolation](https://invisiblenetwork.ai/learn/nptel/106108002/01e6d7dbfbad) (YouTube)
29. [Practical Exercise - 2](https://invisiblenetwork.ai/learn/nptel/106108002/e3fd4f09c101) (YouTube)
30. [Practical Exercise - 3](https://invisiblenetwork.ai/learn/nptel/106108002/9c3a8566cc01) (YouTube)
31. [Motivation for GANs](https://invisiblenetwork.ai/learn/nptel/106108002/55704885a9d5) (YouTube)
32. [GAN Architecture](https://invisiblenetwork.ai/learn/nptel/106108002/01a31b6e4e92) (YouTube)
33. [GAN Objective and Loss Functions](https://invisiblenetwork.ai/learn/nptel/106108002/25236a4aaef4) (YouTube)
34. [GAN Convergence and Nash equilibrium](https://invisiblenetwork.ai/learn/nptel/106108002/deb7ee3d24f9) (YouTube)
35. [Introduction to DCGAN](https://invisiblenetwork.ai/learn/nptel/106108002/e9d6df5dd845) (YouTube)
36. [Practical Exercise - 1](https://invisiblenetwork.ai/learn/nptel/106108002/4cd3e3bc8792) (YouTube)
37. [Practical Exercise - 2](https://invisiblenetwork.ai/learn/nptel/106108002/4b76c10053c2) (YouTube)
38. [Conditional GAN](https://invisiblenetwork.ai/learn/nptel/106108002/deda39c433dc) (YouTube)
39. [Pix2Pix GAN](https://invisiblenetwork.ai/learn/nptel/106108002/b9c2c2c820ea) (YouTube)
40. [Cycle GAN](https://invisiblenetwork.ai/learn/nptel/106108002/d9b53db6de78) (YouTube)
41. [Style GAN](https://invisiblenetwork.ai/learn/nptel/106108002/d195fca77dc6) (YouTube)
42. [Style GAN 2](https://invisiblenetwork.ai/learn/nptel/106108002/4f855a596ab3) (YouTube)
43. [Practical Exercise - 1](https://invisiblenetwork.ai/learn/nptel/106108002/3e845608a132) (YouTube)
44. [Introduction to Diffusion Model](https://invisiblenetwork.ai/learn/nptel/106108002/04c47092ba23) (YouTube)
45. [Mathematics of Diffusion Models](https://invisiblenetwork.ai/learn/nptel/106108002/c6946721d410) (YouTube)
46. ["Denoising Diffusion Probabilistic Model- Forward Process"](https://invisiblenetwork.ai/learn/nptel/106108002/ca6bdae1c1b4) (YouTube)
47. ["Denoising Diffusion Probabilistic Model- Reverse Process"](https://invisiblenetwork.ai/learn/nptel/106108002/bcfb23c37ab9) (YouTube)
48. [Hand on on forward Diffusion process](https://invisiblenetwork.ai/learn/nptel/106108002/2535c453e8aa) (YouTube)
49. [U-Net for Denoising](https://invisiblenetwork.ai/learn/nptel/106108002/8f1c53f5e3d0) (YouTube)
50. [Classifier Guided Diffusion Model](https://invisiblenetwork.ai/learn/nptel/106108002/1c2dc9e1e17d) (YouTube)
51. [Classifier free Diffusion Models](https://invisiblenetwork.ai/learn/nptel/106108002/05710496de80) (YouTube)
52. [Stable Diffusion Model](https://invisiblenetwork.ai/learn/nptel/106108002/7a5fbfbf905d) (YouTube)
53. [Hands-on on reverse diffusion process](https://invisiblenetwork.ai/learn/nptel/106108002/e9a3e4d5e5ad) (YouTube)
54. [Foundations of Natural Language Processing](https://invisiblenetwork.ai/learn/nptel/106108002/dfc031fde610) (YouTube)
55. [Sequential Modeling with RNNs and LSTM](https://invisiblenetwork.ai/learn/nptel/106108002/af362a72e5c0) (YouTube)
56. [Evolution From LSTMs to Transformers](https://invisiblenetwork.ai/learn/nptel/106108002/65236f52a751) (YouTube)
57. [Transformer Architecture: Encoder](https://invisiblenetwork.ai/learn/nptel/106108002/db7078cde958) (YouTube)
58. [Practical Exercise - 1](https://invisiblenetwork.ai/learn/nptel/106108002/787d5a1019ab) (YouTube)
59. [Transformer Architecture: Decoder](https://invisiblenetwork.ai/learn/nptel/106108002/86e37b2b33b7) (YouTube)
60. [Bidirectional Encoder Representations from Transformer (BERT)](https://invisiblenetwork.ai/learn/nptel/106108002/59415eed449e) (YouTube)
61. [Generative Pre-trained Transformer (GPT) Decoder-only Large Language Model](https://invisiblenetwork.ai/learn/nptel/106108002/e41972a557b0) (YouTube)
62. [Prompt Engineering Basics](https://invisiblenetwork.ai/learn/nptel/106108002/fcd65c13054c) (YouTube)
63. [Hands-on on LLM](https://invisiblenetwork.ai/learn/nptel/106108002/5a0e5a293d43) (YouTube)
64. [LLMs – Recap](https://invisiblenetwork.ai/learn/nptel/106108002/e3fc4de001c4) (YouTube)
65. [In-context Learning](https://invisiblenetwork.ai/learn/nptel/106108002/0b6818ee3b34) (YouTube)
66. [Low-Rank Adaptation (LoRA)](https://invisiblenetwork.ai/learn/nptel/106108002/01f144f10261) (YouTube)
67. [RAG Principle](https://invisiblenetwork.ai/learn/nptel/106108002/4c2121426c49) (YouTube)
68. [RAG Recent Advances](https://invisiblenetwork.ai/learn/nptel/106108002/0d719c7d93ed) (YouTube)
69. [Tutorial on In-context Learning, RAG and LoRA](https://invisiblenetwork.ai/learn/nptel/106108002/365742ed36c5) (YouTube)
70. [LLMs for Text Generation](https://invisiblenetwork.ai/learn/nptel/106108002/533fcc683856) (YouTube)
71. [LLMs for Audio, Video and Multimodal Tasks](https://invisiblenetwork.ai/learn/nptel/106108002/3dc28fcb7e68) (YouTube)
72. [Size vs Performance and Benchmarking](https://invisiblenetwork.ai/learn/nptel/106108002/cc6508c3b7da) (YouTube)
73. [Bias, Fairness and Safety](https://invisiblenetwork.ai/learn/nptel/106108002/b293ba90dd50) (YouTube)
74. [Tutorial on LLMs, Multimodal LLMs, Bias, Fairness, Evaluation and Safety](https://invisiblenetwork.ai/learn/nptel/106108002/11601bedb503) (YouTube)