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Data Science II: Big Data Analytics

Financial technology concept. FINTECH. stock photo

INET 4710

Credits
4
Delivery Method
In person
Cost
Tuition | Fees
Terms

About This Course

Scales machine learning models and data analysis to a Big Data platform. Map Reduce and Spark frameworks are introduced as approaches to parallel algorithm development. Hands-on labs.

Sample course topics: Matrix and graph operations, linear regression model, similarity, mining data streams, clustering, dimensionality reduction, and Hadoop big data platform. 

Sample textbook: Mining of Massive Datasets, 2nd Edition by Jure Leskovec, Anand Rajaraman, and Jeffrey David Ullman.

Instructor

Martial Diby
Martial Diby

MS, data science, Northwestern University; BS, economics, Pierre Mendes France
Universite, France; BS, business management, University of Minnesota Crookston

Martial Diby is an advanced analytics manager at BestBuy, where he is responsible for architecting, designing, and implementing enterprise-level machine learning and AI solutions for various internal business groups. His expertise lies in the scientific discovery and translation of actionable insights into effective decisions using algorithms, technologies from data science, and artificial intelligence to design, develop, deploy, and operationalize decision-support models for descriptive, predictive, and prescriptive analytics.

  • INET 4710 Data Science II: Big Data Analytics