Course Schedule

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

Topic	Deadlines & Materials
Week 1: January 22 – 28
Introduction to Big Data Lecture 1 Recording Big Data Case Studies and Datasets Lecture 2 Recording A Quick Tour of Go Lecture 3 Recording	Google Flu Trends Traps in Big Data Analysis Netflix Recommendations How Facebook Labels You Oxide LLM Usage Guide Go resources Go Official Documentation A Tour of Go Learn Go With Tests Go builtins Go Youtube Channel Go by Example Goland IDE SSHing to Orion
Week 2: January 29 – February 4
Unit 1: Scaling and Storage Slightly More Advanced Go Scaling Out Research Papers and HDFS Presentation
Week 3: February 5 – 11
Network Design
Week 4: February 12 – 18
Fault Tolerance and Consensus
Week 5: February 19 – 25
Distributed Hash Tables
Week 6: February 26 – March 4
Data Models
Week 7: March 5 – 11
Unit 2: Distributed & Parallel Computation Introduction to Distributed Computation Hadoop Setup
Week 8: March 12 – 18
Spring Break!
Week 9: March 19 – 25
Hadoop MapReduce
Week 10: March 26 – April 1
Designing a MapReduce Job
Week 11: April 2 – 8
Spark Setup Cluster Orchestration
Week 12: April 9 – 15
Unit 3: Streaming Algorithms and Applications Big Data Sampling Techniques Bloom Filters
Week 13: April 16 – 22
Data Sketches
Week 14: April 23 – 29
Spatiotemporal Data Working with Spark
Week 15: April 30 – May 6
Spark Streaming SageDB, Machine Learning
Week 16: May 7 – 13
Wrapping up the Semester
Week 17: May 14 – 20
Final Quiz: Monday, May 18 ⋅ 10:00am – 10:30 am