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M.Sc. (Information Technology) Advanced Artificial Intelligence Syllabus - Mumbai University 2026

This is the University of Mumbai syllabus for M.Sc. (Information Technology) under NEP 2020, in force from the academic year 2024-25. Semesters I and II are set by item 6.29 (N) and Semesters III and IV by item 6.2 (N). The University examines this programme under form 1113161, whose Summer 2026 timetable is headed NEP-2020; the distance and older Choice Based modes of the same degree are examined under different forms and different papers.

Advanced Artificial Intelligence Syllabus.pdf
Major · Semester 3 · 2 credits

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Syllabus for Advanced Artificial Intelligence

Major · Semester 3 · 2 credits

  • 1 Implementing advanced deep learning algorithms such as convolutional neural OC1 networks (CNNs) or recurrent neural networks (RNNs) using Python libraries like TensorFlow or PyTorch.
  • 2 .Building a natural language processing (NLP) model for sentiment analysis or OC2 text classification.
  • 3 Creating a chatbot using advanced techniques like transformer models.
  • 4 Developing a recommendation system using collaborative filtering or deep learning approaches.
  • 5 Implementing a computer vision project, such as object detection or image segmentation.
  • 6 Training a generative adversarial network (GAN) for generating realistic images. OC6
  • 7 Applying reinforcement learning algorithms to solve complex decision-making OC7 problems.
  • 8 Utilizing transfer learning to improve model performance on limited datasets.
  • 9 Building a deep learning model for time series forecasting or anomaly detection. OC9
  • 10 Implementing a machine learning pipeline for automated feature engineering and OC10 model selection.
  • 11 Using advanced optimization techniques like evolutionary algorithms or Bayesian optimization for hyperparameter tuning.
  • 12 Deploying a machine learning model in a production environment using containerization and cloud services.
  • 13 Use Python libraries such as GPT-2 or textgenrnn to train generative models on a OC13 corpus of text data and generate new text based on the patterns it has learned.
  • 14 Experiment with neural networks like GANs (Generative Adversarial Networks) OC14 using Python libraries like TensorFlow or PyTorch to generate new images based on a dataset of images.

Books and References

  • 1 Deep Learning Ian Goodfellow, Yoshua MIT Pres 2020 Bengio, and Aaron Courville
  • 2 Artificial Intelligence: A Modern Stuart Russell and Peter Prentice 2020 Approach Norvig Hall
  • 3 Reinforcement Learning: An Richard S. Sutton and MIT Press 2023 Introduction Andrew G. Barto
  • 4 Python Machine Learning Sebastian Raschka and Packt 2021 Vahid Mirjalili Publication
  • 5 Cngage Artificial Intelligence Saroj Kaushik, Cengage 2019 Publication

Reproduced from the University of Mumbai syllabus for M.Sc. (Information Technology) under NEP 2020, in force from the academic year 2024-25. Wording, unit numbering and lecture allocation are as printed in that syllabus. The PDF above is the syllabus's own page, unaltered.

The complete syllabus

This subject is cut from the University circular for the whole diploma. Open it here if you want the whole thing rather than a single subject.

PDF 2019 20 MSc IT Part 1 Syllabus NEP 2020 syllabus, in force from 2024-25 Read full PDF Read
PDF 2024 25 MScIT Part 2 SEM III & IV NEP NEP 2020 syllabus, in force from 2024-25 Read full PDF Read
MSc IT Syllabus Study Path
Start with the syllabus document.
Use Part 1 or Part 2 NEP first so the module scope matches your Mumbai University exam.
Move to notes after the scope check.
Use MSc IT notes only after confirming the semester units and topic order.
Practice with papers last.
Open MSc IT question papers after the syllabus check so revision follows the same course structure.
Report or request
Done!