If you are an aspiring data scientist, you may have come across the terms artificial intelligence (AI), machine learning, deep learning and neural networks.

You can not think of data without data science and machine learning coming to mind. They carry out specific activities but are strongly interwoven with each other. One is only complete with the other.

The technology, in private beta since the summer of 2021, automates many skills needed to move machine learning models into production, according to the company, helping data science and machine ...

Upon completion of this course, participants should be able to: ¿ Understand how big data and machine learning can complement traditional data and analytical techniques in macroeconomic analysis and ...

Data really powers everything that we do. Research activities in the data science area are concerned with the development of machine learning and computational statistical methods, their theoretical ...

Core math topics like linear algebra, statistics, and calculus form the foundation of data science.• Real-world projects and ...

PRIMO is based on dictionary learning, a field of machine learning that generates rules based on extensive training data sets. PRIMO was trained using 30,000 high-resolution simulated images of ...

Generative AI, which is technically a first cousin of AI, combines data science and machine learning at its core. To fully leverage this potential, leaders must build teams that understand the ...

Northwestern’s Master of Science in Machine Learning and Data Science (MLDS) program provides data scientists with a technical background in machine learning and artificial intelligence, complemented ...

Apply to the Machine Learning for Data Science Certificate program today at the College of Computing & Informatics. Please refer to the application deadlines below: For Fall 2025: Fall classes start ...

Differential privacy is a method for protecting people’s privacy when their data is included in large datasets. Because differential privacy limits how much the machine learning model can depend ...

This course aims to provide an introduction to the quantitative analysis of data, blending classical statistical methods with recent advances in computational and machine learning. You will cover key ...