CS 291A: Scalable Internet Services

This course explores advanced topics in highly scalable Internet services and their underlying systems architecture. Software today is increasingly being delivered as a service: accessible globally via web browsers and mobile applications and backed by millions of servers. Modern frameworks and platforms are making it easier to build and deploy these systems, such as Ruby on Rails and Amazon’s EC2.

CS 192 Computational Thinking


Topics
Data Representation
Representation of Text
Representation of Images and Video
Representation of Sound and Music
Storing and Accessing Data
Iteration
Recursion
Universal Computation
Arithmetic Algorithms
Searching and Sorting
Advanced Algorithms
Analytical versus Numerical
Symbolic Computation
Everyday Cryptography
 

CS 292F: Foundations of Data Science

This is new gradaute-level course on mathematical foundations of data science, based on the forthcoming book Foundations of Data Science by Avrim Blum, John Hopcroft and Ravi Kannan. The current draft of the book is available at http://www.cs.cornell.edu/jeh/book2016June9.pdf

The course will primarily focus on the following topics:

Geometry of high-dimensionsl space
Matrix methods
Machine learning
Clustering
Graph models

The course work will consist of both programming and theory projects.

CS 595D AI safety and bias in machine learning


CS595D is a graduate computer science seminar that will explore topics
in AI safety and bias in machine learning. These are both fundamental
problems in AI research that have far more questions than answers.
Machine learning is currently deployed all over the world, classifying
data that impacts real people every single day. This year the EU passed
"right to explanation", a law that will take effect in 2018, and will
affect all companies that operate in Europe (yes Google, Facebook, etc).