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This course is the first in the four-course Supply Chain Analytics Professional certificate program. It prepares you to apply leading-edge analytical methods and technology enablers across the supply chain. You’ll learn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, you’ll learn about data cleansing, exploratory data analysis, and visualization. You’ll use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data. You will leave knowing how to gather, analyze, and prepare your data through descriptive analytics before you dig into deeper applications.

The online version of the course is comprised of (4) half-day instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.

Who Should Attend

Experienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.

How You Will Benefit

• Understand the most relevant planning challenges across the strategic, tactical, and operational levels of supply chains
• Learn the difference between analytics types, the links between them, and how to best use them to improve supply chain management (SCM) processes
• Use Key Performance Indicators (KPIs) to find causes of underperformance in supply chains and to plan for analytics projects that will address strategic SCM goals
• Utilize Python and PowerBI to understand, visualize, and analyze data in order to prepare for deeper analytics

What Is Covered

• The role of analytics in SCM
• Types of analytics (descriptive, diagnostic, predictive, and prescriptive) and the relationships between them
• Preprocessing (cleaning and integrating) data as it relates to SCM
• Conducting exploratory data analysis on supply chain data
• Best practices for visualizing data and building dashboards
• Identifying and analyzing KPIs of SCM
• Hands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)

This course is the third in the four-course Supply Chain Analytics Professional certificate program. It introduces the field of machine learning, an area where algorithms learn patterns from data to support proactive decision making, as it applies to supply chain management. You’ll use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance. You’ll use Python and PowerBI to create and analyze regression, clustering, and classification models.

The course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course. An optional pre-course webinar is typically held the Thursday before the course start date (July 6).

Who Should Attend

Experienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.

How You Will Benefit

• Understand the role of machine learning (ML) in Supply Chain Management (SCM)
• Apply advanced analytics techniques to build planning tools that can leverage large and real-time data sets
• Apply ML in demand forecasting and predictive maintenance
• Understand how to assess ML model performance, improve models, and pick the best model for a decision
• Use Python and PowerBI to build, analyze, and deploy ML models

What You Will Learn

• How ML relates to SCM
• ML algorithms such as regression trees, clustering techniques, decision trees, random forests, logistic regression
• Aspects of ML projects including parameter tuning, cross validation, and assess model performance
• Application of ML in demand forecasting for sales and operations planning (S&OP) and inventory management
• Application of ML in predictive maintenance
• Hands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)

This course provides a deep dive into the ways in which artificial intelligence (AI) optimizes supply chain efficiency. Participants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization. The course also covers ethical AI use, good and bad use of generative AI (GenAI), and rapidly emerging use cases. By the end, professionals will be skilled in applying AI to enhance supply chain processes and drive success in their organizations.

Who Should Attend

This course targets supply chain managers, data analysts, logistics professionals, procurement specialists, and business leaders aiming to harness GenAI for enhanced supply chain operations. It is ideal for those interested in GenAI-driven efficiency, strategic insights, and navigation of GenAI's role in transforming supply chain processes.

How You Will Benefit

• Enhance decision-making capabilities through GenAI-driven insights to optimize processes and boost efficiency.
• Acquire practical skills in prompt engineering and the use of generative AI models.
• Explore practical use cases that can be reapplied.
• Learn about good and bad use of GenAI for individuals, teams, and organizations.
• Become better equipped to effectively harness GenAI capabilities in supply chain activities and planning.

What Is Covered

• Foundational understanding of using GenAI in supply chain management
• Basics of GenAI
• Crafting effective AI prompts and their applications in optimizing warehouse layouts
• Predictive maintenance and supplier selection
• Elimination of redundant tasks through AI
• Ethical considerations, risk assessments, and strategy for AI adoption
• Practical strategies and real-world examples for implementing AI solutions effectively and making informed decisions

This course provides a deep dive into the ways in which artificial intelligence (AI) optimizes supply chain efficiency. Participants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization. The course also covers ethical AI use, good and bad use of generative AI (GenAI), and rapidly emerging use cases. By the end, professionals will be skilled in applying AI to enhance supply chain processes and drive success in their organizations.

Who Should Attend

This course targets supply chain managers, data analysts, logistics professionals, procurement specialists, and business leaders aiming to harness GenAI for enhanced supply chain operations. It is ideal for those interested in GenAI-driven efficiency, strategic insights, and navigation of GenAI's role in transforming supply chain processes.

How You Will Benefit

• Enhance decision-making capabilities through GenAI-driven insights to optimize processes and boost efficiency.
• Acquire practical skills in prompt engineering and the use of generative AI models.
• Explore practical use cases that can be reapplied.
• Learn about good and bad use of GenAI for individuals, teams, and organizations.
• Become better equipped to effectively harness GenAI capabilities in supply chain activities and planning.

What Is Covered

• Foundational understanding of using GenAI in supply chain management
• Basics of GenAI
• Crafting effective AI prompts and their applications in optimizing warehouse layouts
• Predictive maintenance and supplier selection
• Elimination of redundant tasks through AI
• Ethical considerations, risk assessments, and strategy for AI adoption
• Practical strategies and real-world examples for implementing AI solutions effectively and making informed decisions

This course is the fourth in the 4-course Supply Chain Analytics Professional certificate program. It incorporates learning advanced analytics and mathematical optimization to find solutions for supply chain problems. You’ll learn how to use linear programming, mixed integer programming, and heuristics to conduct prescriptive analytics related to production processes, distribution networks, and routing. The course serves as a capstone for the program by culminating in a hackathon where you’ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.

The online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.

Who Should Attend

Experienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.

How You Will Benefit

• Use mathematical optimization to transform Supply Chain Management (SCM) processes.
• Apply LP, MIP, and heuristics to SCM, particularly in production planning, routing, and network design.
• Utilize PowerBI and Python in optimization projects.
• Participate in a hackathon that pulls together everything learned throughout the certificate program.

What Is Covered

• Role of mathematical optimization in addressing complex SCM challenges  
• Appropriate application of linear programming (LP), mixed integer programming (MIP), and heuristics
• Evaluation of production processes, distribution networks, and routes using optimization
• Ability to pull together all content of the certificate program into a prescriptive analytics project
• Hands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)

This course is the second in the four-course Supply Chain Analytics Professional certificate program. It emphasizes operational performance metrics to align supply chain management with strategic business goals. You’ll learn several statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) along with inventory management models. You’ll use diagnostic analytics with PowerBI and Python to conduct demand and service profiling, undertake root cause analysis, and use time series forecasting in inventory management.

The online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.

Who Should Attend

Experienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.

How You Will Benefit

• Understand why and how to align Supply Chain Management (SCM) strategy with business strategy
• Learn statistics techniques as they relate to SCM
• Understand inventory management models and how to apply statistics techniques to them
• Create time series forecasts based on SCM data
• Utilize Python and PowerBI to perform statistical analyses, create time series forecasts and visualize results

What Is Covered

• The importance of aligning SCM and business strategy
• How to ask the right business questions as they relate to SCM
• How to use statistics to identify issues, compare data, and forecast decision outcomes
• Statistical concepts including variance analysis and hypothesis testing
• Inventory management models
• Applying statistics to inventory management models
• Forecasting techniques including time series forecasting
• Hands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)

This course prepares you for the basics of transportation operations and analysis. Throughout the course, you’ll review the key elements of transportation such as modes of transportation, transportation procurement, cost minimization techniques, the role of ports in global logistics, and international trade terms. There will also be discussion around emerging trends in North American transportation markets, emerging techniques, and greenhouse gas emissions reduction.

Who Should Attend

This course is designed for Supply Chain Managers, Distribution Managers, Transportation Planners, Transportation Clerks, Transportation Analysts, and Transportation Managers and learners seeking to enter these roles.  Supply chain professionals from other domains will also benefit through gaining insights into transportation operations.

How You Will Benefit

• Understand the characteristics and best use of specific transportation modes
• Apply transportation cost analysis techniques
• Understand the multimodal role of ports in global trade
• Identify and apply best practices in transportation procurement
• Understand how to minimize transportation costs through consolidation techniques
• Understand the role of Incoterms in global trade
• Understand emerging techniques in logistics including techniques to reduce greenhouse gas emissions in logistics

What You Will Learn

• Comparison of characteristics of alternative transportation modes
• Components of Port Logistics systems
• Best practices in transportation procurement
• Application of practical transportation cost analysis techniques
• INCOTERMS purpose, types, and use
• Greenhouse gas emission generation in logistics and mitigation strategies
• New business models in logistics enabled by emerging technologies

This seminar presents a synthesis of research focused on leveraging these data sources for infectious disease prediction, spanning from classical statistical approaches to modern AI architectures.

Key Areas of Discussion:

• Statistical Methodologies: The presentation covers a family of models that combine autoregressive time series structure with penalized regression on Google search data. This includes extensions to spatial-temporal modeling, multi-disease settings, and COVID-19 adaptation.
• AI Architectures: Recent work on attention-based transformer architectures for time series forecasting will be discussed, highlighting methods for multivariate dependency modeling, in-context learning, and efficient linear attention.
• Practical Application: Drawing from ongoing participation in the CDC FluSight forecasting initiative, the session compares the strengths and limitations of both paradigms and shares practical lessons learned from real-time deployment.

The talk aims to offer perspective on when and how statistical rigor and deep learning flexibility each contribute to reliable disease forecasting.

About the Speaker

Dr. Shihao Yang is a Harold E. Smalley Early Career Professor and Assistant Professor in the School of Industrial and Systems Engineering at Georgia Tech. He completed his PhD in statistics and post-doc in Biomedical Informatics at Harvard University. Dr. Yang’s research focuses on data science, with special interest in time series, dynamical systems, and applications in infectious disease transmission forecasting.

To attend, please register online via Zoom.

Hui Zou
Department of Statistics
Stanford University

In the practice of statistical modeling, it is often desirable to have an accurate predictive model with a sparse representation. The lasso is a promising model building technique, performing continuous shrinkage and variable selection simultaneously. Although the lasso has shown success in many situations, it may produce unsatisfactory results in some scenarios: (1) the number of predictors (greatly) exceeds the number of observations; (2) the predictors are highly correlated and form

Participants will be introduced to generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization. The workshop will also cover ethical AI use, good and bad uses of generative AI (GenAI), and rapidly emerging use cases. By the end of the session, participants will have a better understanding of how to begin applying AI to enhance supply chain processes and drive success within their organizations.

Event includes networking, presentation, light bites, beverages, and Q&A.

Featuring Chris Gaffney, Managing Director of the Supply Chain and Logistics Institute (SCL), Academic Program Director for Georgia Tech Professional Education, and Edenfield Executive-in-Residence and a Professor of the Practice in the H. Milton Stewart School of Industrial and Systems Engineering.

Register via Eventbrite to attend the event taking place at the Georgia Tech Atrium (147 Technology Parkway Northwest, Peachtree Corners, GA 30092), the first-of-its-kind professional, academic, and research innovation space within Curiosity Lab’s state-of-the-art Innovation Center.

Register Online to Attend

This course will demonstrate how warehouse operations are a key enabler to a successful supply chain implementation and the starting point for a transformation. It is critical to manage safety, quality and efficiency. Learn to leverage the lean supply chain modifications to improve customer responsiveness and reduce operating costs and in doing so contributing to a supply chain that creates a competitive advantage for a company. To accomplish this goal, we must bring lean principles into the warehouse and distribution center.

Who Should Attend

Supply chain professionals, logistics professionals, material managers, production control managers, transportation managers, warehousing managers and purchasing managers

How You Will Benefit

Upon completion of this course, you will be able to:

• Isolate the key elements of lean thinking to be used in the warehouse
• Value stream map warehouse operations
• Utilize lean tools to reduce waste in the warehouse
• Create a warehouse operation based on visual management and real time problem solving
• Reduce inventories in warehouse operations
• Create collaboration between warehousing and other functional areas

Benefits:

• Reduce inventories in the warehouse
• Reduce warehousing costs by as much as 25%
• Implement lean in the warehouse
• Create logistics collaboration between warehousing and other functional areas

What is Covered

• Lean Warehouse Overview
• Supply Chain Implementation Framework
• Lean Storage Planning Approach
• Application of a Lean Storage Location Sizing Method
• JIT Implementation Approach
• How To Develop Standard Work Batches
• Generation of an Operational Diagram
• Creation of a Daily Operational Work Load Plan
• Development of a Progress Control Board

The requirement for high levels of customer service, increasing numbers of SKUs and high labor costs have dramatically increased the complexity of warehouse operations. It is no longer sufficient to manage a warehouse based on a simple, arbitrary “ABC” classification of SKUs, which treats all those in a category as if they were identical. Instead, each decision – such as where to store or where to pick product – must be based on careful engineering and economic analysis. Each SKU must identify its own cheapest, fastest path through the warehouse to the customer and then compete with all the other SKUs for the necessary resources. This results in warehouse operations that are finely tuned to patterns of customer orders and maximally efficient. Learn the concepts necessary to address modern warehouse trade-offs between space and time in optimizing and managing your warehouse.

Essential learning for those who are seeking cost reductions through better handling methods. Also valuable for those who must replace, upgrade, or add material handling equipment. The two-day course will include case examples and a guided exercise to ensure mastery of the techniques presented.

WHO SHOULD ATTEND

Supply chain and logistics consultants, supply chain engineers and analysts, facility engineers, and warehouse supervisors and team leaders

HOW YOU WILL BENEFIT

Upon completion of this course, you will be able to:

• Exchange space for time (or vice versa) to better meet business objectives
• Understand when to use dedicated storage and when to use shared storage
• Identify the most convenient locations in a warehouse based on an economic model
• Identify patterns in customer orders and exploit these to speed fulfillment
• Evaluate warehouse performance
• Optimally size and stock a forward pick area
• Understand the best practices in order-picking
• Understand how to think about automation
• Evaluate and choose a Warehouse Management System and survive the installation

WHAT IS COVERED

• Management of warehouse fundamentals: Space and time (labor hours)
• Storage policies: Dedicated and shared and their use
• Warehouse analytics: How to discover opportunities for improvement through data-mining
• Pallet operations and layout
• How to size and stock a forward area for split-pallet picks
• How to size and stock a forward area for split-case picks
• Order-picking in high-volume and in low-volume environments
• Benchmarking warehouse performance
• Maintaining inventory accuracy
• Warehouse management systems
• Issues and trends in automation

COURSE MATERIALS

Participants receive a course notebook.

COURSE PREREQUISITES

None.

CERTIFICATE INFORMATION

This course is part of the Supply Chain Management (SCM) Certificate.

PROGRAM TIMES

On the first day, please check in at least 30 minutes before the class start time.

• First Day - 8:30am to 5:00pm
• Second Day - 8:30am to 5:00pm
• Third Day - 8:30am to 4:00pm

This course prepares students in the basics of transportation operations and analysis.  The course includes review of the key elements of transportation such as: modes of transportation, transportation procurement, cost minimization techniques, the role of ports in global logistics, and international trade terms.  The course also will discuss emerging trends in North American transportation markets, emerging techniques, and greenhouse gas emissions reduction.

WHO SHOULD ATTEND

This course is designed for Supply Chain Managers, Distribution Managers, Transportation Planners, Transportation Clerks, Transportation Analysts, and Transportation Managers and learners seeking to enter these roles.  Supply chain professionals from other domains will also benefit through gaining insights into transportation operations.

HOW YOU WILL BENEFIT

Upon completion of this course, you will be able to:

• Understand the characteristics and best use of specific transportation modes
• Apply transportation cost analysis techniques
• Understand the multimodal role of ports in global trade
• Identify and apply best practices in transportation procurement
• Understand how to minimize transportation costs through consolidation techniques
• Understand the role of Incoterms in global trade
• Understand emerging techniques in logistics including techniques to reduce greenhouse gas emissions in logistics

WHAT IS COVERED

• Comparison of characteristics of alternative transportation modes
• Components of Port Logistics systems
• Best practices in transportation procurement
• Application of practical transportation cost analysis techniques
• INCOTERMS purpose, types, and use
• Greenhouse gas emission generation in logistics and mitigation strategies
• New business models in logistics enabled by emerging technologies

Presenter: Seok Joon Kim 

Seminar Title

AHEAD of Time: Toward Robots That Behave Like Human Companions 

Affiliation 

George W. Woodruff School of Mechanical Engineering (Georgia Tech College of Engineering), Symbiotic and Augmented Intelligence Laboratory (SAIL)

Participation & Visibility 

We actively encourage cross-departmental participation and welcome engagement from both internal academic units and external industry partners. Our goal is to foster a robust community of practice around XR at Georgia Tech. 

Subscribe & Sign Up 

To join our mailing list and RSVP your attendance for these seminar series, please sign up here: RSVP HERE. Lunch will be served for those who RSVP.

Presenter: Alex Yang

Seminar Title

 LitForager: Exploring Multimodal Literature Foraging Strategies in Immersive Sensemaking 

Affiliation

IVI Lab (Immersive Visualization & Interaction Lab), School of Interactive Computing (Georgia Tech College of Computing)

Seminar Title

We actively encourage cross-departmental participation and welcome engagement from both internal academic units and external industry partners. Our goal is to foster a robust community of practice around XR at Georgia Tech. 

Participation & Visibility

We actively encourage cross-departmental participation and welcome engagement from both internal academic units and external industry partners. Our goal is to foster a robust community of practice around XR at Georgia Tech. 

Subscribe & Sign Up 

To join our mailing list and RSVP your attendance for these seminar series, please sign up here: RSVP HERE. Lunch will be served for those who RSVP.

Register Online to Attend