Course Schedule

The following is a tentative schedule for the course (subject to change).

	Date	Topic	Readings/Materials
1	Aug 23 - 25	Introduction to Big Data Lecture 1 (8/23) Lecture 2 (8/25)	Keshav: How to Read a Paper Ginsberg et al.: Google Flu Trends
2	Aug 28 - Sep 1	Communication and Network Design Lecture 3 (8/28) Lecture 4 (8/30) Protocol Buffers Lecture 5 (9/1)	A Brief Introduction to Git Research Paper 1: HDFS (Due 8/31) Paper Evaluation Template Project 1 Specification
3	Sep 6 - 8	HDFS Lecture 6 (9/6) Messaging and Serialization Lecture 7 (9/8)	Related Paper: Thrift
4	Sep 11 - 15	Distributed Hash Tables Lecture 8 (9/11) DHT Fault Tolerance, Data Models Lecture 9 (9/13) Lecture 10 (9/15)	Research Paper 2: Dynamo (Due 9/14) Using the bass Cluster
5	Sep 18 - 22	DFS Test Cases Lecture 11 (9/18) Consistency Lecture 12 (9/22)
6	Sep 25 - 29	Byzantine Fault Tolerance Lecture 13 (9/25) Discussion: DFS Faults (9/27) Spanner Lecture 14 (9/29)	Research Paper 3: Spanner (Due 9/28) Related Paper: Chubby
7	Oct 2 - 6	Proof-of-work and Bitcoin Lecture 15 (10/2) Big Data Programming Models Lecture 16 (10/6)	Article on NTP + Rogue Bit Silk Road Operator Dread Pirate Roberts
8	Oct 9 - 11	MapReduce Lecture 17 (10/9)	Research Paper 4: MapReduce (Due 10/12)
9	Oct 18 - 20	MapReduce Discussion Lecture 18 (10/20)	Project 1 (Due 10/18)
10	Oct 23 - 27	Spatiotemporal Data Lecture 19 (10/25) Storm Lecture 20 (10/27)	Research Paper 5: Storm @Twitter (Due 10/26)
11	Oct 30 - Nov 3	Hadoop Tips Lecture 21 (10/30) Lecture 22 (11/1) Lecture 23 (11/3)	Geohash Visualization Geohash Lookup
12	Nov 6 - 10	Counting Streams Lecture 24 (11/6) Summarizing and Sampling Lecture 25 (11/8) Spark Discussion Lecture 26 (11/10)	Research Paper 6: Spark (Due 11/9)
13	Nov 13 - 17	Spark Setup Lecture 27 (11/15) Lecture 28 (11/17)	Research Paper 7: RDDs (Due 11/16)
14	Nov 20 - 22	Project 3 Lecture 29 (11/20)
15	Nov 27 - Dec 1	Machine Learning with Spark Lecture 30 (11/27)	Research Paper 8: TensorFlow (Due 11/30)
16	Dec 4 - 6	Final Project Wrap-up