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 24-28[1. Intro to Big Data Analytics], [2. Course Overview]
2Aug 31-Sep 4[3. Predictive Modeling][Hadoop & HDFS Basics]
3Sep 7-11[4. MapReduce] & [HBase][Hadoop Pig & Hive]HW1 Due (Sep 7)
4Sep 14-18[5. Classification evaluation metrics], [6. Classification ensemble methods]HW2 Due (Sep 21)
5Sep 21-25[7. Phenotyping], [8. Clustering][Scala Basic], [Spark Basic], [Spark SQL]
6Sep 28-Oct 2[9. Spark][Spark Application] & [Spark MLlib]Team Formation & Paper Selection Due (Sep 28)
7Oct 5-9[10. Medical ontology][NLP Lab]Project Proposal Due (Oct 5)
8Oct 12-16[11. Graph analysis][Spark GraphX]HW3 Due (Oct 19)
9Oct 19-23[12. Dimensionality Reduction], [13. Patient Similarity], [14. CNN][Deep Learning Lab]
10Oct 26-30[15. DNN], [16. RNN]HW4 Due (Nov 02)
11Nov 2-6Project Discussion
12Nov 9-13Project Discussion
13Nov 16-20Project DiscussionFinal Exam (Nov 22-23)
14Nov 23-27Project DiscussionFinal Report + Presentation Slides Due (Nov 30)
15Nov 30-Dec 4Final Grading

Previous Guest Lectures

See RESOURCE section.