NON-CREDIT Certificate in Analytics for Analysts Executive Education | Open Enrollment Becoming competent in analytics involves knowing what questions to ask, what methods to utilize in evaluating significant quantities of data, and how to use the insights gained to take action and influence business decisions. The Certificate in Analytics for Analysts has been designed for both individuals and analytics teams to gain immediate and practical skills to solve pressing business challenges. Participants will analyze business cases and use a variety of analytics tools to build value through a data strategy within their organization. This program offers a unique multi-day deep dive across the entire analytics ecosystem and culminates in a short Analytics Capstone Project. By completing six (6) half-day virtual sessions (*Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics and Optimization), and a one-page narrative Analytics Capstone Project, participants will earn a Certificate in Analytics for Analysts from Wake Forest Executive Education and the School of Business’ Center for Analytics Impact. *Each topic is split into two – 4 hour virtual instructor led sessions on consecutive days in the course calendar. This program is not current accepting registrations, please join our mailing list to be notified the next time the program is offered. Join Our Mailing List Required Sessions and Capstone Descriptive Analytics Descriptive analytics is often considered the place to start when evaluating data and the historical insights needed to make effective business decisions. At first glance, descriptive data might appear as the least interesting part of the analytics ecosystem. Yet it forms the backbone of most analytics and, unlike machine learning and data science, most analysts, even those without quantitative backgrounds, intuitively understand descriptive results. Faculty will examine the synergies between data and the decisions we make, and by the end of the program, participants will comprehensively understand data collection and analysis, so the best data drives the best outcomes for your organization. What You’ll Learn Why descriptive analytics is the most important starting point in developing an analytics driven workplace. How to build a “level set” and common language in your organization around descriptive analytics. Understanding and application of data aggregation, extraction, analysis, visualization and data story telling as each relates to descriptive analytics. How to develop a framework for building descriptive analytics KPIs and communicating results effectively to both internal and external customers. How to quickly build descriptive analytics models so that you can extract actionable insights. How to influence leaders and decision makers at your organization by telling an impactful story around descriptive data. × Descriptive Analytics Descriptive analytics is often considered the place to start when evaluating data and the historical insights needed to make effective business decisions. At first glance, descriptive data might appear as the least interesting part of the analytics ecosystem. Yet it forms the backbone of most analytics and, unlike machine learning and data science, most analysts, even those without quantitative backgrounds, intuitively understand descriptive results. Faculty will examine the synergies between data and the decisions we make, and by the end of the program, participants will comprehensively understand data collection and analysis, so the best data drives the best outcomes for your organization. Learn More Atoms / 03.Icon / Plus Circle Predictive Analytics Getting started in predictive analytics takes thoughtful planning and a little time, but it’s a necessary tool that virtually any business can implement. Being committed to an approach or model is key, as is the willingness to invest the time and resources needed to achieve success. Ultimately, predictive analytic models can help businesses acquire, manage, and grow new and existing customers. Using techniques such as data mining, statistical modeling, machine learning, and even artificial intelligence, predictive analytics helps analyze existing data to make future predictions. We can generate future insights with more certainty, and more reliably forecast scenarios, trends, and behaviors. What You’ll Learn Understand how to look at data and gain needed insights to move your business forward. Improve and enhance your ability to forecast and make sound, predictable recommendations with data Explore statistical methods and machine learning techniques to identify the likelihood of future outcomes based on historical data. The right questions to ask in challenging assumptions of analytics and AI How to use frameworks and tools to recognize the power and potential of data in driving competitive advantage. How data can be used effectively from diverse industries and functional areas by networking with peers × Predictive Analytics Getting started in predictive analytics takes thoughtful planning and a little time, but it’s a necessary tool that virtually any business can implement. Being committed to an approach or model is key, as is the willingness to invest the time and resources needed to achieve success. Ultimately, predictive analytic models can help businesses acquire, manage, and grow new and existing customers. Learn More Atoms / 03.Icon / Plus Circle Prescriptive Analytics & Optimization 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. By using optimization models and other readily available tools, we can determine the best near-term outcomes and make the best decisions for our organizations. As we evaluate business objectives, key metrics such as profitability improvement, cost reductions, and client satisfaction can be optimized with prescriptive analytics. During this program, applications in business including production planning, location analysis, supply chain design, transportation, marketing/product design and financial portfolio analysis will be discussed. Additionally, the use and application of rule-based systems and heuristics with an emphasis on optimization modeling of real business problems will be explored and tested. We will utilize hands-on real-world case studies using open-source software (Open Solver) in Microsoft Excel, R for Optimization, and AMPL – algebraic modeling system. What You’ll Learn Analytics techniques in the context of real-world prescriptive 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 and Nonlinear Models Practical business applications of optimization models in operations, supply chain, marketing and finance with the free opens source software Excel add-in, Open Solver. × Prescriptive Analytics & Optimization 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. By using optimization models and other readily available tools, we can determine the best near-term outcomes and make the best decisions for our organizations. Learn More Atoms / 03.Icon / Plus Circle Analytics Capstone Project Within one week of the final session program, participants will be required to submit a one-page narrative outlining the application of course learnings to an internal analytics or business challenge. Program faculty will review each project submission and provide feedback. Once the review is complete, each participant will receive a signed certificate suitable for framing. What You’ll Learn Descriptive Analytics Predictive Analytics Prescriptive Analytics & Optimization × Analytics Capstone Project Within one week of the final session program, participants will be required to submit a one-page narrative outlining the application of course learnings to an internal analytics or business challenge. Program faculty will review each project submission and provide feedback. Once the review is complete, each participant will receive a signed certificate suitable for framing. Learn More Atoms / 03.Icon / Plus Circle “This program has opened my eyes to the numerous ways to solve/optimize data problems that I face on an everyday basis.” — Analytics Program Participant, Certificate Objectives and Expected Outcomes: By the end of the course, participants will be able to: Establish a “level set” and common language in your organization around analytics. Understand techniques for using data to generate new ideas, experiment with solutions, and evaluate alternatives Frame a business problem that can be tested through various analytics methods Use data to reduce decision making uncertainty Manage big data sets to solve real-world problems Analytics Capstone Project Within one week of the final session program, participants will be required to submit a one-page narrative outlining the application of course learnings to an internal analytics or business challenge. Program faculty will review each project submission and provide feedback. Once the review is complete, each participant will receive a signed certificate suitable for framing. Additional Information Dates, Location, Schedule The Certificate in Analytics for Analysts will be offered in six half-day sessions over the course of five weeks. Each session will be offered virtually. Final Capstone projects are due one week after the final course session. Descriptive Analytics (Shannon McKeen) Session 1: March 7, 2023 1-5pm EST Session 2: March 8, 2023 1-5pm EST Predictive Analytics (Tonya Balan) Session 1: March 21, 2023 1-5pm EDT Session 2: March 22, 2023 1-5pm EDT Prescriptive Analytics and Optimization (Chris Smith) Session 1: April 4, 2023 1-5pm EDT Session 2: April 5, 2023 1-5pm EDT Capstone Due: April 12, 2023 by midnight Cost Certificate in Analytics for Analysts Spring 2023 – $2,800 for all sessions in the certificate track. Materials 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. This program assumes basic proficiency in Microsoft Excel. Refund and Cancellation Policies Program Cancellation This course is offered contingent upon sufficient enrollment. If a course must be canceled, 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 canceled courses. Individual Cancellation – Refund Policy Prospective participants who withdraw at least 10 days prior to the start of a course will receive a full refund of tuition paid. Contact Us For more information, or to speak with a program adviser, please send an email to execedinfo@wfu.edu. Meet the Faculty Shannon McKeen Shannon McKeen, Professor of the Practice & Executive Director for the Center for Analytics Impact, Wake Forest School of Business Tonya Balan, Ph.D. Tonya Balan, Associate Teaching Professor, Wake Forest School of Business Chris Smith Chris Smith, Associate Professor of Business Analytics, Wake Forest School of Business Wake to What’s Next Contact Us