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Data Science - Mathematical Methods

Data Science - Mathematical Methods
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  • Curriculum
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Objectives On completion of this tutorial, you will be able to:
  • Define functions and list their uses in computing
  • Identify and define key mathematical methods, including linear algebra and calculus, and recall their role in computing applications
  • Recognize and define important statistical measures and methods and identify their role in advanced business computing applications
Tutorial Overview Advanced business computing applications such as artificial intelligence (AI) and machine learning (ML) require advanced mathematics and statistics. While relatively few financial professionals need to be experts in these disciplines, it is important for all those who use financial technology tools to understand the mathematical and statistical concepts and methods that underlie them. Doing so can help financial professionals use technology more effectively, as well as help them to identify appropriate applications for different tools and to be aware of those tools' limitations. This tutorial provides an overview of the core mathematical and statistical methods that are important to contemporary data science. Prerequisite Knowledge AI & Machine Learning (ML) - Primer Tutorial Level: Intermediate Tutorial Duration: 50 minutes
  • 1 Sections
  • 2 Lessons
  • 0m Duration
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Data Science - Mathematical Methods

2 Lessons
  • Data Science - Mathematical Methods
  • Data Science - Mathematical Methods - Completion

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