Use modern machine learning tools and python libraries. Explain how to deal with linearly-inseparable data. Compare logistic regression’s strengths and weaknesses. Explain what decision tree is & how ...

Articulate the primary interpretations of probability theory and the role these interpretations play in Bayesian inference Use Bayesian inference to solve real-world statistics and data science ...

You don't have to spend a fortune and study for years to start working with big data, analytics, and artificial intelligence. Demand for "armchair data scientists" – those without formal ...

This course aims to cover various tools in the process of data science for obtaining, cleaning, visualizing, modeling, and interpreting data. Most of the tools introduced in this course will be based ...

This introductory ethics module for data science courses includes a reading, homework assignments, and case studies, all designed to spark a conversation about ethical issues that students will face ...