M.Sc. (Information Technology) Data Science Syllabus - Mumbai University
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.
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Syllabus for Data Science
- a Data Science Technology Stack: Rapid Information Factory Ecosystem, Data Science Storage Tools, Data Lake, Data Vault, Data Warehouse Bus Matrix, Data Science Processing Tools ,Spark, Mesos, Akka , Cassandra, Kafka, Elastic Search, R ,Scala, Python, MQTT, The Future.
- b Layered Framework: Definition of Data Science Framework, Cross- Industry Standard Process for Data Mining (CRISP-DM), Homogeneous [OC1, OC2, Ontology for Recursive Uniform Schema, The Top Layers of a Layered Framework, Layered Framework for High-Level Data Science and Engineering
- c Business Layer: Business Layer, Engineering a Practical Business Layer
- d Utility Layer: Basic Utility Design, Engineering a Practical Utility Layer
- a Three Management Layers: Operational Management Layer, Processing-Stream Definition and Management, Audit, Balance, and Control Layer, Balance, Control, Yoke Solution, Cause-and-Effect, Analysis System, Functional Layer, Data Science Process
- b Retrieve Superstep: Data Lakes, Data Swamps, Training the Trainer [OC4, OC5, Model, Understanding the Business Dynamics of the Data Lake, Actionable Business Knowledge from Data Lakes, Engineering a Practical Retrieve Superstep, Connecting to Other Data Sources.
- c Assess Superstep: Assess Superstep, Errors, Analysis of Data, Practical Actions, Engineering a Practical Assess Superstep
- a Process Superstep : Data Vault, Time-Person-Object-Location-Event Data Vault, Data Science Process, Data Science,
- b Transform Superstep : Transform Superstep, Building a Data OC9, OC10] Warehouse, Transforming with Data Science, Hypothesis Testing, Overfitting and Underfitting, Precision-Recall, Cross-Validation Test.
- a Transform Superstep: Univariate Analysis, Bivariate Analysis, Multivariate Analysis, Linear Regression, Logistic Regression, Clustering Techniques, ANOVA, Principal Component Analysis (PCA), Decision Trees, Support Vector Machines, Networks, Clusters, and Grids, Data Mining, Pattern Recognition, Machine Learning, Bagging Data,Random Forests, Computer Vision (CV) , Natural Language Processing (NLP), Neural Networks, TensorFlow.
- b Organize and Report Supersteps : Organize Superstep, Report Superstep, Graphics, Pictures, Showing the Difference
Books and References
- 1 Practical Data Science Andreas APress 2018 François Vermeulen
- 2 Principles of Data Science Sinan Ozdemir PACKT 2016
- 3 Data Science from Scratch Joel Grus O’Reilly 2015
- 4 Data Science from Scratch Joel Grus Shroff 2017 first Principle in python Publishers
- 5 Experimental Design in N C Das Shroff 2018 Data science with Least Publishers Resources
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.
Use Part 1 or Part 2 NEP first so the module scope matches your Mumbai University exam.
Use MSc IT notes only after confirming the semester units and topic order.
Open MSc IT question papers after the syllabus check so revision follows the same course structure.