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Please choose one morning session and one afternoon session.
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If you are not already an NCAIR member, your NCAIR membership must be submitted and payment initiated to NCAIR before you enroll in the Summer Drive-In events.
Schedule
| Event | Title | Course description | Add to Cart |
| 10:00AM - 12:00PM | Introduction to SAS Programming | We start with the basics: presenting syntax rules, reading a Microsoft Excel worksheet, creating a new variable, and building simple reports. Then we give you the opportunity to try things on your own with hands-on practices following the lecture and discussion. |  |
| 10:00AM - 12:00PM | Analytical Insight of Institutional Data: A Case Study | Participants will be given a project from the Dean of the College of Engineering. While attempting to answer the statistical questions requested by the Dean, participants will be encouraged to discuss different SAS statistical procedures. From exploring the data to formalizing a model to deploy, this case study will walk through the steps of statistical analysis. Come ready to share a few of your favorite SAS Statistical Procedures and maybe learn about a couple more. | |
| 10:00AM - 12:00PM | Data Mining Tour of Enterprise Miner | In this session we'll take a quick tour of SAS Enterprise Miner. Enterprise Miner is a premier SAS tool for building predictive models and performing other data mining tasks. We'll see how Enterprise Miner is used to explore and prepare data. We'll perform a k-means clustering application and build many predictive models including a decision tree, a logistic regression model and a neural network. Model deployment will also briefly be covered. | |
| 1:00PM - 3:00PM | Text Mining with Enterprise Miner | Interested in seeing some practical examples of Text Mining? In this lively session, we will first transform the results of a "web-crawl" of current events into "structured data" (numeric dimensions representing of the text) using SAS Enterprise Miner software. Learn the proper use of Text Miner nodes as we answer questions, explore and investigate the data.
In a second example, we will read free-form text (patient comments on prescription drug use) to build a model that will then automatically categorize new patient comments into the correct category using the Score node. |
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| 1:00PM - 3:00PM | Introduction to Computer Vision - Lecture Only | Deep learning is an area of machine learning that has become ubiquitous with computer vision. Computer vision technologies are being used in new applications and are being incorporated across industries to solve both familiar and unfamiliar problems. For some tasks, computer vision models have surpassed human accuracy. In this workshop, participants will learn the pivotal aspects and building blocks of a convolutional neural network. Demonstrations will use SAS Cloud Analytic Services (CAS) to take advantage of the in-memory distributed environment. CAS provides a fast and scalable environment to build complex models and analyze big data by using algorithms designed for parallel processing. Graphics Processing Units (GPUs) are leveraged for larger models demonstrated in this session. | |
| 1:00PM - 3:00PM | SAS Visual Analytics for Viya | This course describes how to use SAS Visual Analytics for SAS Viya to discover your data and create reports in an elegant and intuitive web-based interface. You learn about the SAS Visual Analytics architecture and how to interact with the SAS Visual Analytics environment from SAS Drive. Join us as we discover in-memory data and create interactive reports and dashboards. | |
| 1:00PM - 3:00PM | IPEDS Data Session | RTI staff will provide an introduction to useful tools for analyzing and viewing IPEDS data. This session will demonstrate how to access IPEDS data using selected NCES consumer-focused tools and related IPEDS data tools and guide participants through the basic functions, processes, and capabilities of the tools. Participants will learn how to use the various tools to access IPEDS data or download the data for further analysis through hands-on practice and take-home exercises.
Note: Participants will need to bring their own laptop to this session. |
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