Over deze cursus
Modern businesses need to make sense of vast amounts of (structured or unstructured) data in order to support business decisions, and remain competitive. Data-driven AI techniques address this purpose. It comprises the strategies and technologies used by organizations for the data analysis of business information. It provides insight into the business activities to support decision making.
This course provides an introduction to the major aspects of data-driven AI. It introduces the fundamental concepts, and covers the main methods and techniques to enable applications in real-world business context. It starts with the data provisioning process, ranging from data collection and preparation to modelling, evaluation and deployment, and continues with the approaches for data visualization. Next, analytical techniques for supervised learning (prediction and classification) and unsupervised learning (clustering) are introduced. Topics of more recent relevance such as deep learning and text mining are also discussed. Furthermore, the concept of explainable AI is introduced and some related techniques are discussed.
Leerresultaten
Upon completing the course successfully, students will be able to:
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discuss the key concepts of data-driven AI for business intelligence and its importance in modern business,
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use data visualization techniques to understand and assess the business data,
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set up a data mining study according to established (scientific) procedures,
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understand various data mining and machine learning methods, including clustering, regression, classification, deep learning, and natural language processing techniques.
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apply various data mining and machine learning techniques to business problems using appropriate tools (e.g., Python).
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understand and apply the concept/methods of explainable AI.
Voorkennis
Je moet voldoen aan één van de onderstaande verzamelingen met eisen
- Verzameling 1
- Bachelor of Science (BSc) afgerond
- Verzameling 2
- Schakelprogramma afgerond
- Verzameling 3
- Geen van onderstaande cursussen mag zijn behaald
- Business Intelligence (1BM56)
Bronnen
- Han, J., Micheline K., and Jian P. (2012) Data mining: concepts and techniques. Elsevier
- Grossmann, W.; Rinderle-Ma, S. (2015) Fundamentals of Business Intelligence, Springer-Verlag, Berlin, Heidelberg.
Aanvullende informatie
- Meer infoCursuspagina op de website van Eindhoven University of Technology
- Neem contact op met een coordinator
- StudiepuntenECTS 5
- Niveaumaster
Aanbod
Startdatum
3 februari 2025
- Einddatum6 april 2025
- Periode *Blok GS3
- LocatieEindhoven
- VoertaalEngels
De inschrijving begint over 23 dagen