Found 11 relevant results in 3.38s where lecturer="Andrea Ferrario"
This course will enable participants to shape the AI-driven future of their company. It focuses on building a roadmap of company-specific AI use cases roadmap, innovating with AI business models, and on the capabilities non-AI companies need to build to organically deploy AI. While acquiring the skills to drive an AI Transformation participants will draft an AI strategy for their own organization
In this course, students learn to plan, implement, and evaluate modern business analytics to generate value from data for society, organizations and individuals. This serves the pressing need of firms to improve their efficiency – such as customer satisfaction, competitive advantage – and launching innovative services by leveraging the growing amounts of data and methods, such as machine learning.
Machine learning has revolutionized various domains across industry sectors. Advances in GenAI has triggered this development and has created additional fantasies for future applications. Hence, an understanding its practical applications is crucial for professionals in today’s data-driven world. This course delves into the concepts of ML, its applications and use cases and ethical considerations.
This course provides you with real-world case studies and projects in finance and insurance where machine learning methods have been successfully applied.
Provides you with a comprehensive understanding of the ethical dimensions and challenges around machine learning applications in a business and societal context.
This final task challenges the CAS in Machine Learning in Finance and Insurance participants to transform an inspired idea into a tangible prototype. Drawing inspiration from the workshops of Block II and Block III, you will develop and implement a pioneering project that showcases your acquired expertise.
Provides you with a comprehensive introduction to the fundamentals of machine learning, including key concepts, algorithms, and practical applications.
Machine learning models are widely used in multiple sectors of society (e.g., healthcare, financial services, job-markets and judicial system). The research domain of interpretable machine learning (iML) aims at designing and testing methods that allow users to understand machine learning models and their outcomes, assessing and managing the risks stemming from their use.
This lecture dives deep into AI-driven marketing, blending theory with hands-on data analysis from real-world retail scenarios. Students explore a diverse array of predictive analytics tools, engage in a competitive prediction challenge, and receive expert mentorship. Beyond marketing, they will acquire skills impacting various sectors. Perfect for aspiring marketers and AI enthusiasts.
Technological advances, digitization and the ability to store and process vast amounts of data has changed the landscape of financial services in recent years. This course will unpack these innovations and technologies underlying these transformations and will reflect on the impacts on the financial markets.