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 18-22[1. Intro to Big Data Analytics], [2. Course Overview]
2Aug 25-29[3. Predictive Modeling][Hadoop & HDFS Basics]HW1 Due (Sep 1)
3Sep 1-5[4.MapReduce]& [HBase][Hadoop Pig & Hive]
4Sep 8-12[5.Classification evaluation metrics], [6.Classification ensemble methods]HW2 Due (Sep 15)
5Sep 15-19[7. Phenotyping], [8. Clustering][Scala Basic], [Spark Basic], [Spark SQL]Project Group Formation (Sep 22)
6Sep 22-26[9. Spark][Spark Application] & [Spark MLlib]Project Proposal Due (Sep 29)
7Sep 29- Oct 3[10. Medical ontology][NLP Lab]
8Oct 6-10[11. Graph analysis][Spark GraphX]HW3 Due (Oct 13)
9Oct 11-17[12. Dimensionality Reduction], [13. Patient similairty], [14. CNN][Deep Learning Lab]
10Oct 20-24[15. DNN], [16. RNN]HW4 Due (Oct 27)
11Oct 27-31Project Discussion
12Nov 3-7Project Discussion
12Nov 10-14Project DiscussionFinal Exam (Nov 16-17)
13Nov 17-21Project Discussion
14Nov 24-28Project DiscussionFinal Project Due (Nov 24)
15Dec 1-5Final Grading

Previous Guest Lectures

See RESOURCE section.