Course Syllabus

Overview

Students should watch Udacity 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
1Jan 18-22[1. Intro to Big Data Analytics], [2. Course Overview]
2Jan 25-29[3. Predictive Modeling][Hadoop & HDFS Basics]HW1 Due (Jan 31)
3Feb 1-5[4.MapReduce]& [HBase][Hadoop Pig & Hive]
4Feb 8-12[5.Classification evaluation metrics], [6.Classification ensemble methods]HW2 Due (Feb 14)
5Feb 15-19[7. Phenotyping], [8. Clustering][Scala Basic], [Spark Basic], [Spark SQL]
6Feb 22-26[9. Spark][Spark Application] & [Spark MLlib]HW3 Due & Project Group Formation & Project Requirements Release (proposal/draft/final) (Feb 28)
7Mar 1-5[10. Medical ontology][NLP Lab]
8Mar 8-12[11. Graph analysis][Spark GraphX]Project Proposal Due (Mar 14)
9Mar 15-19[12. Dimensionality Reduction], [13. Patient similairty], [14. CNN][Deep Learning Lab]HW4 Due (Mar 21)
10Mar 22-26[15. DNN], [16. RNN]
11Mar 29-Apr 2Project DiscussionHW5 Due (Apr 4)
12Apr 5-9Project Discussion
13Apr 12-16Project DiscussionProject Draft Due (Apr 18)
14Apr 19-23Project DiscussionFinal Exam (Apr 25)
15Apr 26-30Project DiscussionFinal Project Due (code + presentation + final paper) (May 2)
16May 3-6Project Submission

Previous Guest Lectures

See RESOURCE section.