Course Syllabus

Overview

Students should watch Canvas/Ed Lessons course videos according to the following schedule. It is recommended for students to do lab sessions on the schedule by yourself as early as possible since some of homework may cover the lab materials scheduled later than the homework. For the online video lectures, CS/CSE students should go to Udacity or Canvas to access to the sources.

Schedule

Week #DatesVideo lessonsLabDeliverable & Due (EDT)
1Jan 12-16[1. Intro to Big Data Analytics], [2. Course Overview]
2Jan 19-23[3. Predictive Modeling][Hadoop & HDFS Basics]HW1 Due (Jan 26)
3Jan 26-30[4.MapReduce]& [HBase][Hadoop Pig & Hive]
4Feb 3-6[5.Classification evaluation metrics], [6.Classification ensemble methods]HW2 Due (Feb 9)
5Feb 9-13[7. Phenotyping], [8. Clustering][Scala Basic], [Spark Basic], [Spark SQL]Project Group Formation (Feb 16)
6Feb 16-20[9. Spark][Spark Application] & [Spark MLlib]Project Proposal Due (Feb 23)
7Feb 23-27[10. Medical ontology][NLP Lab]
8Mar 2-6[11. Graph analysis][Spark GraphX]HW3 Due (Mar 9)
9Mar 9-13[12. Dimensionality Reduction], [13. Patient similairty], [14. CNN][Deep Learning Lab]
10Mar 16-20[15. DNN], [16. RNN]HW4 Due (Mar 23)
11Mar 23-27Project Discussion
12Mar 30- Apr 3Project Discussion
12Apr 6-10Project DiscussionFinal Exam (Apr 12-13)
13Apr 13-17Project DiscussionFinal Project Due (Apr 20)
14Apr 20-24Final Grading
15Apr 27- May 1Final Grading

Previous Guest Lectures

See RESOURCE section.