Description

Much is said about the path of companies seeking digital transformation and how the adoption of Artificial Intelligence contributes to solving business problems, positively impacting operating results. In a scenario of digital acceleration and increased pressure for efficiency improvement as a result of the pandemic, investing in innovation becomes a matter of survival and not only of competitive advantage.

In this context, technology initiatives should be seen as a "means" to achieve a result, and not the other way around. In addition, one must understand exactly what are the business “pains” and what is the company's cultural maturity in order to implement these projects.

In this webinar we will present some business “pain points” (i.e: lack of team’s technical skills, inefficient planning process, lack of demand pattern understanding, customer churn, risk management) and which frameworks and technologies can be used to solve them, e.g. predictive models such as linear regression, decision trees, ensemble models, neural networks, classification models and clustering.

Instructor's Bio

Ricardo Bolognesi Dias

 AI Research Scientist at I.Systems Brazil

Ricardo is an AI Research Scientist at I.Systems Brazil and has extensive experience in planning, having worked for more than 15 years in several leading companies in their segments such as: Oracle, Accenture, Estee Lauder, Natura and Grupo Pão de Açúcar. He has a specialization in Supply Chain Management from APICS (American Production and Inventory Control Society) and a postgraduate degree in Retail and Consumer Market from FIA USP. In the last few years he was certified in Big Data & Data Science by MITx and founded the company Intuito Analitica whose objective aims to share AI knowledge through the analytical community. Currently leads Demand Planning projects and has studied the practical application of supervised learning for time series forecasting.

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Webinar

  • 01

    AI Revolution: Opportunities and Challenges from a business perspective

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