Data Science Academy
Learn how you can leverage machine learning to unlock hidden value of all your data and build up analytics talent in your organization
We are the world's leading machine learning experts in retail
Tomorrow's retailers are in urgent need of innovative technology and talent. Only the right combination of analysis, accurate forecasts and employee expertise allow retail organization to optimize and automate their decision-making in replenishment and pricing. Turn the enormous amount of data gathered everyday into your competitive advantage.
At Blue Yonder, we help leading retailers master this task. We work together with our customers by offering both thought leadership and expert trainings in machine learning and data science for retail. We offer bespoke courses tailored to your specific needs.
We work hand in hand with our retail customers in their path towards becoming data driven companies.
Take a look at our training offer below:
Management Introduction: How Machine Learning keeps Retailers Ahead of Trends
Description:
This course introduces you to the retail revolution. You will be provided with a greater insight into why machine learning and AI have become top agenda items for executives in the retail space. You will learn about the value decision automation provides to future-looking retailers, especially in replenishment and pricing processes.
Goals
After this course, you will have a better understanding about how machine learning and artificial intelligence are disrupting the retail space. You will also learn how this can be leveraged to optimize and automate replenishment and pricing strategic decisions.
Content
- Predictive Analytics: How machine learning and artificial intelligence are used to predict future events
- Prescriptive Analytics: How to transform predictions and (predicted) uncertainty into optimized decisions, how to avoid cognitive biases
- Decision Automation: Taming the biases and the huge number of decisions
- Practical examples from retail: store and distribution center replenishment, pricing
Target Audience:
Management teams, VP and experts in supply chain, replenishment, logistics, pricing, category management and IT.
Machine Learning for Automated Replenishment Along the Supply Chain: Stores and Distribution Centers
Description:
This course introduces machine learning in the context of supply chain management and replenishment at stores and distributions centers in particular. You will learn how machine learning enables supply chain management experts to make strategic decisions and optimize relevant KPIs.
Goals
After this course, you will have an understanding how machine learning is used to optimize and automate replenishment decisions. With hands-on exercises, you will gain a greater insight into how machine learning technology can optimize relevant KPIs.
Content
- Machine learning applied to supply chain management, with focus on replenishment of stores and distribution centers
- Understanding replenishment KPIs: strategic advantages of using machine learning
- Replenishment Optimization with machine learning in complex scenarios
- Change Management: Developing a data culture throughout the organization
Target Audience:
Management teams, VP and experts in supply chain, replenishment, logistics and category management.
Machine Learning for Optimized Prices and Markdown Decisions Along Products' Lifecycle
Description:
This course introduces machine learning in the context of pricing, both in brick and mortar and online stores. You will learn more about how machine learning technology enables the CFO, category managers, store managers or other price process owners to optimize base price setting and markdown decisions.
Goals
After this course, you will understand how machine learning can calculate optimized prices daily and why this is superior to legacy technologies, such as rules based systems. Using presentations, real-world examples and hands-on exercises we'll provide you with greater insight into the inner workings on how bottom-line KPIs, such as profits or revenues, are increased with historical sales data and modern self-learning algorithms.
Content
- Machine learning applied to deriving price elasticities
- Understanding the impact of pricing rules/scenarios
- Putting the power of a KPI-based price strategy into operation
- Change Management: Developing a data culture throughout the organization
Target Audience:
Category managers, store managers, price process owners, price strategists
Goals
Machine learning solutions are the cornerstone of algorithmic enterprises as they support or automate business decisions using sophisticated algorithms. In this course, you will learn what predictive applications are and how data science and artificial intelligence are the core of disrupting business models.
Course content
- What are machine learning solutions: How business decisions are formed and how machine learning solutions are used to support or automate processes
- Statistics primer: How we perceive probabilities and how to deal with probabilities and uncertainties in our business decisions
- Artificial Intelligence and Deep Learning: Overview on data science methods, machine learning, artificial intelligence as well as deep learning
- Evaluation of predictions: Theoretical basis for evaluating predictions, most frequently used metrics, cognitive biases and examples from the retail industry
Target Audience:
Management teams, business analysts, data scientists
Data Integration to Blue Yonder Machine Learning Solutions
Description:
This course is a detailed introduction to Blue Yonder solutions and you can learn about the different data formats requirements through practical exercises. You will be trained as a data expert for Blue Yonder solutions so that you can fully advise your company on how to get data ready for use with Blue Yonder's solutions.
Goals of the course
After the course, you will be in the position to transform your company's data into Blue Yonder's required format and to deliver it back to your system.
In addition, you will be able to query the forecasts in Blue Yonder's solutions and make them available back into your system. This course will allow IT experts to advise management teams and business unit managers on how forecast quality can be optimized through additional data sources and better data conditions, which can then be leveraged within Blue Yonder solutions.
Course content
- Introduction to Blue Yonder's solutions landscape
- The standard delivery categories of the Blue Yonder interface
- The Blue Yonder forecast query
- Criteria for data quality and temporal data requirements
- Error analysis in problematic data delivery
- Influential factors on forecast quality from the customer side
- Practical exercises for supplying and obtaining data
Target Audience:
IT managers, IT experts