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)
1Aug 19-23[1. Intro to Big Data Analytics], [2. Course Overview]
2Aug 26- Aug 30[3. Predictive Modeling][Hadoop & HDFS Basics]HW1 Due (Sep 2)
3Sep 2-6[4.MapReduce]& [HBase][Hadoop Pig & Hive]
4Sep 9-13[5.Classification evaluation metrics], [6.Classification ensemble methods]HW2 Due (Sep 16)
5Sep 16-20[7. Phenotyping], [8. Clustering][Scala Basic], [Spark Basic], [Spark SQL]Project Group Formation (Sep 23)
6Sep 23-27[9. Spark][Spark Application] & [Spark MLlib]Project Proposal Due (Sep 30)
7Sep 30- Oct4[10. Medical ontology][NLP Lab]
8Oct 7-11[11. Graph analysis][Spark GraphX]HW3 Due (Oct 14)
9Oct 14-18[12. Dimensionality Reduction], [13. Patient similairty], [14. CNN][Deep Learning Lab]
10Oct 21-25[15. DNN], [16. RNN]HW4 Due (Oct 28)
11Oct 28- Nov 1Project Discussion
12Nov 4-8Project DiscussionProject Draft Due (Nov 11)
13Nov 11-15Project DiscussionFinal Exam (Nov 17-18)
14Nov 18-22Project Discussion
15Nov 25-29Project DiscussionFinal Project Due (Dec 2)
16Dec 2-6Final Grading

Previous Guest Lectures

See RESOURCE section.