Big Data Analytics
| Hours: 3 0 3 |
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“VSM model, data representation, data transformation and pre-processing, Search, Indexing and memory, natural Language Processing: data n-grams, Streams, Information and Language, analyzing Sentiment and Intent, Databases and their Evolution, Big data Technology and Trends, Map-Reduce, Big data analysis using Hadoop, data mining using mahout, classification, clustering, and mining, information extraction, deep learning from heterogeneous data, forecasting, data analysis: regression and feature selection, recent trends in big data.
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| Pre-requisites: none | Co-requisites: none |
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Hours: XYZ where X = Lecture, Y = Lab, Z = Credit
All hours are per week.
3 Lab hours constitute 1 credit hour
1 credit hour implies 1 lecture of 50mins per academic week. 16 weeks in total.
Pre-Requisite courses are courses required to be completed before this course may be taken
Co-Requisite courses are courses required to be taken along with this course
