Big Data Analytics


Big Data Analytics

MET CS 777 (4 credits)

This course is an introduction to large-scale data analytics. Big Data analytics is the study of how to extract actionable, non-trivial knowledge from massive amount of data sets. This class will focus both on the cluster computing software tools and programming techniques used by data scientists, as well as the important mathematical and statistical models that are used in learning from large-scale data processing. On the tools side, we will cover the basics systems and techniques to store large-volumes of data, as well as modern systems for cluster computing based on Map-Reduce pattern such as Hadoop MapReduce, Apache Spark and Flink. Students will implement data mining algorithms and execute them on real cloud systems like Amazon AWS, Google Cloud or Microsoft Azure by using educational accounts. On the data mining models side, this course will cover the main standard supervised and unsupervised models and will introduce improvement techniques on the model side.
Prerequisite: MET CS 521, MET CS 544 and MET CS 555. Or, MET CS 677. Or, Instructor's consent.

2024SPRGMETCS777 A1, Jan 18th to Apr 25th 2024

Days Start End Type Bldg Room
R 06:00 PM 08:45 PM MET 122

2024SPRGMETCS777 O1, Jan 16th to Mar 4th 2024

Days Start End Type Bldg Room
ARR TBD TBD ROOM

2023FALLMETCS777 A1, Sep 6th to Dec 6th 2023

Days Start End Type Bldg Room
W 06:00 PM 08:45 PM MET 101

2023FALLMETCS777 O1, Sep 5th to Oct 23rd 2023

Days Start End Type Bldg Room
ARR TBD TBD ROOM

2023SUM1METCS777SO1, May 9th to Jun 26th 2023

Days Start End Type Bldg Room
ARR TBD TBD ROOM

 

Format & Syllabus