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Data Mining in Finance

The amount of data available to manage risk in a portfolio as well as the information needed to perform a thorough financial analysis of a company grow at an ever increasing speed. Moreover, data can no longer be gathered from one single source of information.

This practical program covers key techniques - including several aspects of supervised and unsupervised machine learning - that you can use when mining financial data.

Most exercises and case studies are illustrated in Python, allowing you to learn how to work with this flexible programming language.

  • Date:
  • 26th - 27th October 2017
  • Venue:
  • Manhattan - New York
  • Fee:
  • US$1785 per day


  • You might be eligible for preferential rates. Please contact us to check if your company is a member of the LFS Global Client Programme.

This course is also available in London, Singapore and Sydney

Who The Course is For

  • Portfolio managers
  • Risk managers
  • Professionals looking to introduce data-mining concepts in their day-to-day tasks
  • IT developers
  • Statisticians
  • Quant analysts
  • Financial engineers

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Prior Knowledge

  • Basic notions of statistics
  • Good working knowledge of Excel
  • No prior knowledge of Python is required

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