Prescriptive Analytics – What’s a manager to do?
Prescriptive analytics differs from descriptive and predictive analytics in that prescriptive models yield a course of action to follow. That is, the output from a prescriptive model is a plan for management to follow. Applications in business including production planning, location analysis, supply chain design, transportation, marketing/product design and financial portfolio analysis will be discussed. This module will include hands-on experience using open-source software (Open Solver) in Microsoft Excel, R for Optimization, and AMPL – algebraic modeling system.
What You’ll Learn
In this one-day program, we will discuss prescriptive analytics including rule-based systems, heuristics and optimization, with an emphasis on optimization modeling of real business problems.
Key program takeaways include:
- Introduce analytics techniques in the context of real-world applications
- Improve your ability to view business processes and relationships systematically and analytically.
- Techniques for using data to generate new ideas, experimenting with solutions, and evaluating alternatives
- Optimization with Linear & Discrete Models
- Business Applications of Linear Models with Open Solver, R for Optimization, and AMPL – algebraic modeling system.
Who Should Attend?
This program is designed for analysts who want to learn more about predictive, descriptive, and prescriptive analytics and how making decisions with data can be enhanced through optimization models. This module is highly relevant for anyone seeking advanced knowledge in optimization modeling.
This course assumes prior knowledge of algebraic notation and Excel.
|7:45 – 8:15||Continental Breakfast|
|8:15 – 9:30||Introductions and agenda|
|What makes decision making difficult?|
|Analytics: Descriptive, Predictive and Prescriptive|
|9:30 – 10:15||Optimization: Business Applications of Linear Models|
|10:15 – 10:30||Break|
|10:30 – 11:30||Optimization Software|
|Excel Solver/ Open Solver|
|R for Optimization|
|AMPL – algebraic modeling system|
|11:30 – 12:00||Application of learnings to individual business challenges brought by participants|
|12:00 – 12:30||
|12:30 – 1:30||Hands-on Case Study: Linear Model|
|1:30 – 2:30||Optimization: Business Applications of Discrete Models|
|2:30 – 2:45||
|2:45 – 3:15||
Hands-on Case Study: Discrete Model
|3:15 – 4:00||
Optimization: Business Applications of Nonlinear Models
|4:00 – 4:45||
Application of learnings to individual business challenges brought by participants
|4:45 – 5:00||
Program begins promptly at 8:30 and will wrap-up no later than 5:00.
Wake Forest Innovation Quarter
575 N. Patterson Ave.
Winston-Salem, NC 27101
The cost of the program is $825 and includes materials, continental breakfast and lunch, and is due in full at time of registration. Additionally, Wake Forest University alumni and faculty receive a 25% tuition discount. For more information please send an email to firstname.lastname@example.org or call 336-758-2239.
Course materials are included in the cost of tuition. Course materials will be distributed electronically in advance of the program start date. Participants must have a laptop or tablet computer to access course materials.
Registration and Payment
This is an open enrollment program. Application is not required. Course registration is complete when payment is processed. Upon registration, a representative of Wake Forest will contact you to validate the registration information and to assist in fee payment. Please click the link below to begin the registration process.
Cancellation of Program
This course is offered contingent upon sufficient enrollment. If a course must be cancelled, all registered participants will be notified at least five (5) calendar days before the course’s start date. All registered participants will receive a 100% tuition refund. No fees will be charged for cancelled courses.
Prospective participants who withdraw at least 15 days prior to the start of a course will receive a full refund of tuition paid.
For More Information
For more information or to speak with a program adviser, please send an email to email@example.com or call 336-758-2239.