Purdue’s Foundations of Data Science Graduate Certificate gives students the opportunity to learn in-demand data science skills in less time than a traditional master’s degree – making fast career ...

We are interested in questions relating to the mathematical foundations of data science, with particular focus on the social context of data science research, including the ethical implications of ...

Offered: Winter (TTh 9:30-10:50 a.m.) and Spring (TTh 12:30-1:50 p.m.) Foundations of Data Science will cover the fundamentals of data science and the context within which this field operates. This ...

The Foundations of Data Structures and Algorithms specialization includes two optional preparation courses and a three-course pathway to earn admission to the Online MS in Computer Science. You must ...

This course will provide an introduction to the mathematical and algorithmic foundations of data science. Topics include the counterintuitive nature of data in high dimensions, important linear ...

Data Science Foundations introduces the fundamentals of data science, including terminology and concepts, core models and algorithms, technologies, and application scenarios. It considers the key ...

and validation with an on-campus and online certificate in Data Science Foundations. This certificate is for qualified professionals who want to enhance their skill set and can be a foundation to ...

Purdue’s Foundations of Data Science Graduate Certificate teaches data science competencies in less time than a traditional master’s degree. By taking a handful of 100% online courses, you can add a ...

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, ...

Who is the Graduate Certificate in Data Science Foundations program for? Drexel College of Computing & Informatics' Post-Baccalaureate/Graduate Certificate in Data Science Foundations is designed for ...

Introduces concepts and skills fundamental to Data Science including: getting data, data wrangling, exploratory data analysis, basic statistics, data visualization, data modeling, and learning. The ...