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 while Analytics students should navigate to Edx instead, please check details on Canvas.

Schedule

Week #DatesVideo lessonsLabDeliverable Due
1Aug 17-21[1. Intro to Big Data Analytics], [2. Course Overview]
2Aug 24-28[3. Predictive Modeling][Hadoop & HDFS Basics]HW1 Due (Aug 30)
3Aug 31- Sep 4[4.MapReduce]& [HBase][Hadoop Pig & Hive]
4Sep 7-11[5.Classification evaluation metrics], [6.Classification ensemble methods]HW2 Due (Sep 13)
5Sep 14-18[7. Phenotyping], [8. Clustering][Scala Basic], [Spark Basic], [Spark SQL]
6Sep 21-25[9. Spark][Spark Application] & [Spark MLlib]HW3 Due & Project Group Formation & Project Requirements Release (proposal/draft/final) (Sep 27)
7Sep 28- Oct 2[10. Medical ontology][NLP Lab]
8Oct 5-9[11. Graph analysis][Spark GraphX]Project Proposal Due (Oct 11)
9Oct 12-16[12. Dimensionality Reduction], [13. Patient similairty], [14. CNN][Deep Learning Lab]HW4 Due (Oct 18)
10Oct 19-23[15. DNN], [16. RNN]
11Oct 26-30Project DiscussionHW5 Due (Nov 1)
12Nov 2-6Project Discussion
13Nov 9-13Project DiscussionProject Draft Due (Nov 8)
14Nov 16-20Project Discussion
15Nov 23-27Project DiscussionFinal Exam (Dec 1)
16Noc 30-Dec 4Project SubmissionFinal Project Due (code + presentation + final paper) (Dec 6)

Previous Guest Lectures

See RESOURCE section.