ALIK SOKOLOV MSC, CFA LEAD DATASCIENTIST DELOITTE Alik is a mathematician and data scientist, and holds a Master’s degree in Mathematics from the University of Toronto, as well as the CFA designation. Alik has extensive practical experience with machine learning, with a career focus in applying and creating machine learning algorithms to tackle problems within the financial services industry. As a lead data scientist at Deloitte, he has built models and led teams that created envelope-pushing solutions in banking, using advanced techniques to tackle complex business problems. Alik is also involved with enterprise analytics and AI strategy, both internally for Deloitte and with large Canadian enterprises, helping define AI strategy, talent models, toolset & best practice choices for machine learning groups. Alik has also created courses teaching data science and machine learning that have been delivered to hundreds of Deloitte practitioners, MACHINE LEARNING Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance. DESCRIPTION AI and Machine Learning are transforming how people work and how business interact with their customers, with Financial Services being no exception. This conference is an opportunity to look “under the hood” of how machine learning is being applied at the cutting edge of financial services, across Lines of Business such as credit risk, marketing, back office and customer relationships. OBJECTIVE The course will cover machine learning from both a theoretical and practical point of view, with a focus on pragmatic applications & real financial services examples. Topics will cover supervised & unsupervised learning, as well as high level workflows from business problem definition down to analysis and integration with business strategy. Participants will be encouraged to understand problems from a quantitative point of view, as well as through the lens of strategy and business usage. The course will cover theory, applications & common usage of key machine learning techniques, as well as case studies from the financial and professional services industries. TOPICS 1. 2. 3. 4. 5. 6. 7. 8.
Introduction to machine learning, types & definitions Supervised learning introduction Unsupervised learning introduction Machine learning workflow & applications Supervised learning deep dive Unsupervised learning deep dive Model evaluation & applications Wrap up, trends and best practices in ML
CURSO EN INGLÉS Fecha: 22 de Marzo 2018 Precio: $15,000.00 M.N. + IVA DURACIÓN: 8 Horas (1 Clase) Lugar: Hotel St. Regis Ciudad de México
REQUERIMIENTOS • Contar con nivel medio o superior de inglés. • Ser egresado de carreras económico - administrativas. • De preferencia, trabajar en instituciones financieras. • Es necesario el uso de laptop.
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