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 ...

AI is everywhere. The advances in AI have benefited virtually every commercial industry - but there is as much (or more!) hype about AI as there is real AI. In the midst of this are the terms - AI, ...

Every few years, drug development goes through a moment where a new technology promises to change everything. Artificial ...

Both fields are in high demand, pay well, and lead to exciting, future-proof careers. If you're deciding between becoming a data scientist or an AI engineer, the choice often comes down to what ...

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 ...

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Ph.D student Austin P. Wright wins a best paper runner-up award at an international conference for an algorithm used on the Mars Perseverance Rover than can be used in applications in earth science ...

Single-cell RNA sequencing (scRNA-seq) is a method for measuring gene expression in individual cells, allowing observation of various cellular processes, including cell differentiation, the cell cycle ...