Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

Data structures and algorithms constitute the foundational toolkit of computer science, enabling efficient storage, retrieval and manipulation of data. Data structures—ranging from arrays, linked ...

Overview: Algorithm selection is an engineering decision: the wrong choice can freeze a system at scale, regardless of ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

The massive datasets that power machine learning algorithms and systems are complex, noisy, and vulnerable to various kinds of errors, contamination, and adversarial corruptions. As data science and ...

Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...

The algorithms that underlie modern artificial-intelligence (AI) systems need lots of data on which to train. Much of that data comes from the open web which, unfortunately, makes the AIs susceptible ...

Overview: Fewer than half of enterprise machine learning models reach production, and the root cause is almost always a ...

Web Development vs. Data Science vs. Machine Learning: Students aspiring to build a career in IT or Computer Science often ...