Knowledge Discovery and Data Architecture to Know your Customer

At the end of the course the participants will be able to:

• recognise their organisation’s data pipeline
• identify knowledge discovery projects in their environment
• story telling for a data mining project from an ethics and policies point of view
• design the main stages of a data mining project
• formulise and visualise the insights behind each set of data using models
• hands-on a data mining project using customer behaviour data
• process mining

In this training, participants will learn, integrate, apply, and evaluate core concepts and tools to explore the available data with extracting, reporting, and using its wisdom. They will dive deep into the advanced methods and techniques of knowledge discovery using sophisticated commercial as well as open-source programming languages.

Through this course, the participants will develop their own data pipeline from scratch for multiple real-life marketing projects. Furthermore, they will also be exposed to data lakes, GDPR, data governance, and more. At the end of this three-hour course the trainees will have the awareness of required skills to design and execute their own know-your-customer project.

At the end of the course, participants will receive a certificate of attendance issued by the House of Training.

Peiman A. Sarvari; Luxembourg Institute of Science and Technology

Prof. Peiman A. Sarvari is an artificial intelligence expert and data scientist at Luxembourg Institute of Science and Technology. He has an outstanding background in data engineering, cloud computing, robotics, operations research, and computer simulation. Peiman A. Sarvani helps academia with lecturing on subjects such as big data, AI, and Information Communication Technologies in different European universities. He has successfully managed and fulfilled several business projects on digitalisation and platform design. He is a certified AWS architect, SCADA, and Apache Kafka developer. Currently, Peiman is coupling IoT and AI for better industrial and business performances. He designs state-of-the-art data pipelines engaging the usages of mathematical optimisers to design data-driven industrial and social communities.