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Artificial Intelligence and Machine Learning (AI/ML) are nowadays increasingly present across all industries and sectors since every company needs to stand out in today’s competitive environment in which margins are low.
In this session, we will discuss two current topics from this field: first, democratising AI/ML, allowing business users and data scientists to easily implement ML models, and second, applying AI/ML to improve production quality.

First part: although data science is everywhere, many users still feel that it is difficult to employ the tools and techniques available. However, with the trend of democratising AI/ML, building, interpreting and applying AI/ML models has become much more accessible for non-experts. In this part of the session, you will learn about how business users can build advanced analytics models without code using HR department data.

Second part: we will look at the topic of production quality. The use case will exemplify the topic of IT/OT data convergence and how the manufacturing quality of a product from a large organisation was analysed and improved using AI/ML. You will find out how the scrap rate was reduced, thus increasing productivity and supporting the producer’s sustainability strategy.

Moderator:

Joan Moragon, Innovation Coach & Creative Designer at SAP
Joan started his professional career at SAP Dublin, supporting after-sales services for HR solutions and Innovation Technologies. Now in Barcelona, ​​he is part of an innovation team that designs experiences for SAP customers and helps them uncover innovation opportunities.

 

Programa

1. Demonstrate how business analysts, data scientists and citizens can start creating models and applying ML without coding using human resources data.
2. The goal is to present how a chemical company applies AI to predict quality during the manufacturing process.
a. We cover the AI/ML model and its implementation and deployment approach.
3. Q&A

Masterclass taught by SAP (CIDAI core partner)

Taught by:

  • Gonzalo Hernan Sendra, AI/ML Solution Advisor at SAP Gonzalo is a member of SAP’s Global Center of Excellence for Data Value. He holds a PhD in Engineering and has always been interested in the industrial application of data science. He has advised customers on how to address business challenges with AI/ML, integrate these models into the business process and operationalise them in a production environment.
  • Stojan Maleschlijski, Machine Learning Engineer at SAP Stojan is a member of SAP’s Global Center of Excellence for Data Value. He focuses on applying Machine Learning and AI to assist customers in becoming more data-driven, agile and resilient to disruptions. Before joining SAP, he worked in Signal and Image Processing in various industries. He holds a PhD from the University of Heidelberg, Germany.
  • Andreas Forster, Data Scientist at SAP Andreas is a member of SAP’s Global Center of Excellence for Data Value. With a background in analytics and statistics, he has been working for around 10 years on Machine Learning projects with customers of all sizes and from very different industries.
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