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The Data Incubator November Data Science Training with Federal Reserve Boar...

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DC 20009

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This is a private training, led by The Data Incubator, for employees of the Federal Reserve Board.



Course Content

Data Science for Business Leaders

While there is strong and growing demand for data scientists and engineers, there is also a under-appreciated need for business professionals who can communicate with and facilitate collaboration between technical and business teams within an organization. This module covers a variety of topics geared toward giving business leaders a high-level understanding of machine learning and artificial intelligence methods and how they can be applied to solve business problems and make intelligent decisions. In this course, participants will learn fundamentals of machine learning methods with an emphasis on how and where these methods may be applied; strategies for evaluating data science projects to identify wins; strategies for working with data science teams and projects; and guidelines for avoiding pitfalls and challenges commonly encountered in data science applications.

Introduction to Predictive Analytics

Machine learning requires strong statistical foundations. In this module, we solidify that groundwork by reviewing probability concepts such as important distributions, Bayes' Rule, and conditional expectation - and move on to rigorous statistical analysis: parameter estimation, hypothesis testing, p-values, z-scores, and other core concepts in statistical inference. We extend this basis of statistical knowledge into machine learning basics: regression, regularization, overfitting, and important learning metrics. Students put these concepts into practice on real-world data sets, using Python's stats-oriented libraries to ask interesting, relevant questions and draw concrete inferences from population data.



About the instructors:

Tim Schwuchow is a Data Scientist in Residence at The Data Incubator. Prior to joining The Data Incubator, he earned degrees in economics from Harvard and Duke. Professionally, he has designed and instructed several undergraduate- and graduate-level courses at Duke, worked as an analyst at D. E. Shaw & Co., a quantitative hedge fund, and worked as an economist for the Postal Regulatory Commission.

Russell Martin is a Data Scientist in Residence at The Data Incubator. Russ has was his PhD in Applied Mathematics from Georgia Tech. After completing his degree, he worked for seventeen years in the United Kingdom, including roles at Warwick University and the University of Liverpool. Russell teaches our Data Science Fellowship and leads corporate trainings for TDI’s training partners.

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DC 20009

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