Machine learning requires strong statistical foundations. In this module, we solidify that groundwork by reviewing probability concepts such as important distributions, Bayes' Rule, and conditional expectation. We then move on to rigorous statist[...]
Today, data is more than just a corporate asset. As data consumers, we’ve become accustomed to having up-to-the-minute analytics for any event that might affect our business or personal lives. We’re becoming used to the influence of IoT in our homes,[...]
Predictive analytics projects are not successful inherently and automatically. They must deliver real business impact and mitigate the risks that are part of any complex project. Understanding the role of predictive analytics as part of decision supp[...]
Do you find analytic practitioners’ activities baffling and somewhat “out of reach?” Do you need to better understand the methods, techniques, and processes of business analytics? This course covers many technical issues that are often misapplied in [...]
In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concept[...]
This course will prepare analytic practitioners and functional managers to make sense of predictive modeling and take control of the analytic process. We’ll introduce the foundation for data-intensive analytic projects that deliver insight, clarity, [...]
This course covers the latest Spark v2 features.
This course introduces the building blocks needed to implement predictive capabilities within an organization. It also helps develop the necessary understanding about how models, people, and decision processes must interact to drive actual business i[...]