B.Sc. (Data Science) Deep Learning Syllabus - Mumbai University
This is the TY BSc Data Science syllabus under NEP 2020, in force from the academic year 2026-27. The University still sets the earlier Choice Based papers alongside it for ATKT candidates, so check which scheme your exam form names before you revise.
Loading syllabus...
Syllabus for Deep Learning
Module I: Introduction and Mathematical Basics for Deep Learning
- Introduction to Deep learning: What is Deep learning? Difference between Deep learning and Machine learning. Deep Networks: Deep feed forward network, regularization for deep learning, Optimization for Training deep models. Linear Algebra: Scalars, Vectors, Matrices and Tensors, Multiplying Matrices and Vectors, Identity and Inverse Matrices, Linear Dependence and Span, norms, special matrices and vectors, Eigen decompositions. Numerical Computation: Overflow and under flow, poor conditioning, Gradient Based Optimization, Constraint optimization. What is Language AI and Natural Language Processing evolution?
Module II: Deep Learning Models, Applications, and Research
- Convolution Applications: Convolutional Networks, Sequence Modelling, Applications Deep Learning Research: Linear Factor Models, Auto encoders, representation learning Generative Models: What Is Generative Modelling? Generative Versus Discriminative Modelling, Generative Modelling and AI, The Generative Modelling Framework, Representation Learning, Core Probability Theory, Generative Model Taxonomy, Approximate Inference, Deep Generative Models Applications: Transformers, Advance GANs 10 Text Books 1. Deep Learning, Ian Goodfellow, Yoshua Bengio, Aaron An MIT Press book 1 st 2016 2. Generative Deep Learning David Foster O’Reilly 2 nd 2023 11 Reference Books 1. Fundamentals of Deep Learning Nikhil Buduma O’Reilly, 1 st Edition, 2017 2. Deep Learning: Methods and Applications Deng & Yu Now Publishers,1 st 2013 3. Deep Learning CookBook Douwe Osinga O’Reilly 1 st 2017 12 Internal Continuous Assessment: Semester End Examinatin: 60% 40% 13 Continuous Evaluation through: 30 marks Semester End Examination 20 marks. Lecture attendance, Mid Term teste, assignment, class test, presentations on new real life applications and its working 14 Format of Question Paper: (Semester End Examination: 30 Marks. Duration: 1 Hr ) Q1: Attempt any three (out of five/six) from Module 1 (15 Marks) Q2: Attempt any three (out of five/six) from Module 1 (15 Marks)
Text Books
- 1 Deep Learning, Ian Goodfellow, Yoshua Bengio, Aaron An MIT Press book 1 st 2016
- 2 Generative Deep Learning David Foster O’Reilly 2 nd 2023
- 1 Fundamentals of Deep Learning Nikhil Buduma O’Reilly, 1 st Edition, 2017
- 2 Deep Learning: Methods and Applications Deng & Yu Now Publishers,1 st 2013
- 3 Deep Learning CookBook Douwe Osinga O’Reilly 1 st 2017
Reproduced from the University of Mumbai syllabus for B.Sc. (Data Science) under NEP 2020, in force from the academic year 2026-27. Wording is as printed in that syllabus. Module numbering is as printed there too.
The complete syllabus
This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.