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B.E Artificial Intelligence and Machine Learning AI for Financial and Banking Application Lab Syllabus - Mumbai University 2026

This is the Fourth Year AI-ML syllabus under REV-2019 'C' Scheme, in force from the academic year 2023-24. The University has not yet published an NEP 2020 syllabus for this year of the degree, and this is the scheme its examinations are set on.

AI-for-financial-Banking-application-Lab.pdf
Semester 8 · Fourth Year AI-ML

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Syllabus for AI for financial & Banking application Lab

Semester 8 · Fourth Year AI-ML

Suggested List of Experiments

  • 1 Setting up a Digital Money Transfer System
  • 2 Calculating Sharpe Ratios for Investment Portfolios 3, Cluster Analysis of Financial Data for Market Segmentation
  • 4 Analyzing Market Sentiment using the Markov Regime Switching Model
  • 5 Developing and Backtesting a Simple Trading Algorithm
  • 6 Implementing Advanced Risk Management Techniques in Trading Algorithms
  • 7 Fraud Detection using Machine Learning Algorithms
  • 8 Visualizing Fraud Patterns and Analytics
  • 9 Designing and Backtesting Complex Trading Strategies
  • 10 Evaluating and Enhancing the Performance of Trading Algorithms
  • 11 Applying Machine Learning for Predictive Fraud Analytics

Textbooks

  • 1 Financial Analytics with R Building a Laptop Laboratory for Data Science MARK J. BENNETT University of Chicago DIRK L. HUGEN University of Iowa
  • 2 Artificial Intelligence in Finance A Python-Based Guide, Yves Hilpisch A
  • 3 Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection , Bart Baesens, Veronique Van Vlasselaer, Wouter Verbeke
  • 1 “ Machine Learning for Asset Managers" by Marcos López de Prado
  • 2 "Advances in Financial Machine Learning" by Marcos López de Prado. Digital References:
  • 1 https://www.eastnets.com/newsroom/digital-transformation-in-the-banking-and-financial-services-sector
  • 2 https://www.techopedia.com/definition/34633/generative-ai

Reproduced from the University of Mumbai syllabus for B.E. (Artificial Intelligence and Machine Learning) under REV-2019 'C' Scheme, in force from the academic year 2023-24. Wording is as printed in that syllabus. The University sets no module list for this course; what she publishes is the objectives, outcomes and assessment guidelines reproduced above.

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.

PDF 7.8 (R-A) B.E. (Artificial Intelligence and Machine Learning) Sem I & II (Revised, NEP 2020) NEP 2020 syllabus Read full PDF Read
PDF 6.21 (N) B.E. (Artificial Intelligence and Machine Learning) Sem III & IV (NEP 2020) NEP 2020 syllabus Read full PDF Read
PDF 6.42 (R) B.E. (Artificial Intelligence and Machine Learning) Third Year, Sem V & VI (REV-2019 'C' Scheme) REV-2019 'C' Scheme syllabus Read full PDF Read
PDF B.E. (Artificial Intelligence and Machine Learning) Fourth Year, Sem VII & VIII (REV-2019 'C' Scheme) REV-2019 'C' Scheme syllabus Read full PDF Read
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