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Engineering Analytics
2 Days | 1.4 CEUs

Overview:

In this program, engineers and managers will be introduced to the fundamentals of Engineering Analytics, that is, the process of leveraging data into actionable insights. These strategies will be applicable to a wide range of applications including customer segmentation for better resource utilization, improved performance tracking for diagnosis and maintenance, classification strategies for improved inventory management, better use of sales data for increased revenues and customer satisfaction, and better forecasts. The course will serve as a foundation for those interested in sitting for the INFORMS certification. 

Basic methods will be introduced in the areas descriptive and predictive analytics and Big Data. Participants will get hands on experience through the use of case studies and example problem demonstrations. Throughout this introductory program, Microsoft-based tool such as Excel will be used when appropriate. Other analytics software tools, in particularly those that are in the public domain, will be discussed.

Participants should bring a laptop with Excel installed.

What You Will Learn: 

  • Apply techniques for data visualization
  • Describe the importance of segmentation and classification strategies
  • Use basic tools of descriptive and predictive analytics 
  • Interpret the impact of Big Data on decision making
  • Describe the underlying technology in Big Data
  • State the strategic implications of analytics 
  • Prepare for the INFORMS Analytics Certification  

Course Content

  • Introduction to engineering analytics 
  • Data visualization strategies
  • Data cleaning
  • User interaction
  • Business impact
  • Descriptive analytics: data models
  • Data properties
  • Databases
  • Design issues
  • Descriptive analytics: dimension reduction
  • Soundar Kumara extraction
  • Regression techniques 
  • Descriptive analytics: clustering and segmentation
  • Clustering
  • Segmentation
  • Hierarchical models
  • K-means methods
  • Case study illustration
  • Descriptive analytics: classification strategies
  • Logistic regression
  • Measures of accuracy
  • Predictive analytics: introduction principal component analysis
  • Principal component analysis for prediction
  • Predictive Analytics: forecasting 
  • Nonparametric methods
  • Case study illustration
  • Big data: unstructured data concepts
  • Data models
  • Database requirements for big data
  • Big data: enterprise modeling
  • Mapreduce 
  • Hadoop 
  • Big data requirement from an enterprise perspective
  • Networks and analytics 
  • The use of graphs and networks in analytics 
  • The use of social media networks 

CLASS CANCELLATION:

IIE reserves the right to cancel a class up to 15 business days prior to the scheduled start date

 

registration fee

Member: $795
Non-Member: $1,145

course schedule

Course ID: 2027
Nov 4 - 5, 2014
Norcross, GA
2027

Course ID: 2116
Sep 19 - 20, 2016
Norcross, GA
2116

 
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