ACP Data Science & Predictive Analytics for Business Professionals

This intensive hands-on course gives you the skills necessary to extract stored data elements, understand what they mean in the company, transform their formats, and derive new relationships among them to produce a dataset suitable for analytical modeling. Use these skills to produce a fully processed data set, compatible for building powerful predictive models that can be deployed to increase profitability in your company.

This hands-on course teaches the skills necessary to extract stored data elements, understand what they mean, transform their formats, and derive new relationships among them in order to produce a dataset suitable for analytical modeling. Data preparation for data mining consists of three elements: (1) Data Mining Process delineation (you have to understand the overall process), (2) Data Understanding (you can’t properly prepare data until you understand it), (3) Data Pre-processing (transforming data into a form compatible with data mining.) By the end of the course, you will be able to use these skills to produce a fully processed data set, compatible for building powerful predictive models that can be deployed to increase profitability for your company.

Learn how to use the basics of predictive analytics and modeling data to determine which algorithms to employ. Learn “best practices” and the influence various options have on predictive models to gain a deeper understanding of how the algorithms work qualitatively. Understand common approaches to deployment of predictive models and be able to integrate models into decision-making processes. Learn how to monitor models, when to update them, how to deploy and refine them, and to develop applicable performance metrics.

Highly successful businesses know that the rules have changed. No longer can they rely solely on their product or service to grow; they must leverage their data (financial, customer support, web interactions, etc.) to better understand their customers and learn from the collective experiences of their organizations to remain competitive. This course provides individuals the skills needed to effectively collect and manage Big Data and perform data-driven discovery and prediction, extracting value and competitive intelligence for their organizations.

The world produces more than 2.5 exabytes of data every day. Visualization is one key approach to gaining insight from this mountain of data, enabling you to see trends and patterns (along with gaps and outliers) in the data that are not easily identified in rows and columns of numbers. Visualization can also provide access to huge data sets, such as weather, web traffic, sales and voting records. Data sets of this size have the potential to be overwhelming and inaccessible; a good visualization provides a way to explore, understand, and communicate the data, along with actions the data indicate should be taken. You will use Tableau in conjunction with Alpine to explore and analyze data and learn how it can be used to visualize Big Data.

This course will begin with a review of some case histories of Big Data use. Basic elements of successful Big Data implementation will be covered as well as a review of commercially available tools and technology. A focus will be placed on value opportunities in online marketing, search optimization and site performance modeling.