Algorithmic Techniques for Taming Big Data

CDS DS 563

  • Quantitative Reasoning II
  • Creativity/Innovation

Growing amounts of available data lead to significant challenges in processing them efficiently. In many cases, it is no longer possible to design feasible algorithms that can freely access the entire data set. Instead of that we often have to resort to techniques that allow for reducing the amount of data such as sampling, sketching, dimensionality reduction, and core sets. Apart from these approaches, the course will also explore scenarios in which large data sets are distributed across several machines or even geographical locations and the goal is to design efficient communication protocols or MapReduce algorithms. The course will include a final project and programming assignments in which we will explore the performance of our techniques when applied to publicly available data sets. Effective Fall 2021, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Creativity/Innovation.

FALL 2021 Schedule

Section Instructor Location Schedule Notes
A1 Onak MCS B33 TR 2:00 pm-3:15 pm Mts w/CAS CS543

FALL 2021 Schedule

Section Instructor Location Schedule Notes
B1 Onak MCS B37 W 10:10 am-11:00 am Mts w/CAS CS543

Note that this information may change at any time. Please visit the Student Link for the most up-to-date course information.