Szczecin

Biuro Aloha, Jerzego Janosika 17, Szczecin, Polska, 71-424

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F# for Data Science

21 godzin
Data science is the application of statistical analysis, machine learning, data visualization and programming for the purpose of understanding and interpreting real-world data. F# is a well suited programming language for data science as it combines efficient execution, REPL-scripting, powerful libraries and scalable data integration. In this instructor-led, live training, participants will learn how to use F# to solve a series of real-world data science problems. By the end of this training, participants will be able to:
  • Use F#'s integrated data science packages
  • Use F# to interoperate with other languages and platforms, including Excel, R, Matlab, and Python
  • Use the Deedle package to solve time series problems
  • Carry out advanced analysis with minimal lines of production-quality code
  • Understand how functional programming is a natural fit for scientific and big data computations
  • Access and visualize data with F#
  • Apply F# for machine learning
Explore solutions for problems in domains such as business intelligence and social gaming Audience
  • Developers
  • Data scientists
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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F#: Introduction to Functional Programming

14 godzin
F# is a functional-first programming language. It is a strongly typed language that supports different styles of programming, including functional, imperative, object-oriented, and reactive. F# is fully supported in Visual Studio and Xamarin Studio. In this instructor-led, live training, participants will learn functional programming as they step through the creation of a series of sample applications and utilities. By the end of this training, participants will be able to:
  • Understand the principles of functional programming.
  • Write elegant, maintainable code for solving complex computing problems.
  • Use F# with Javascript and C# to create asynchronous web applications.
Format of the course
  • Part lecture, part discussion, exercises and heavy hands-on practice
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