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Data Science with R Workshop

Brian Sletten's Data Science with R Workshop

Join this workshop on Data Science with R to gain the skills you need to get started with data science, including statistical and numerical methods and R. You will also learn about visualising data, big data environments and how to interact with linked data in R. Upon completion of this Data Science workshop, you will have an understanding of relevant languages and tools.

As there is a rush to hire data scientists these days, there is a coincident rush to update resumes to include the term "Data Scientist". Unfortunately, like most types of science, it is less a single topic and more a multi-disciplinary way of thinking, inquiring and communicating. Individuals do not need to know everything about the field, but teams should be composed of individuals who collectively do.

Attending this workshop won't make you a data scientist overnight, but you will learn to be one in time and will have a study plan for moving forward in this field.

About the Author

Brian Sletten

Brian is a liberal arts-educated software engineer with a focus on forward-leaning technologies. His experience has spanned many industries including retail, banking, online games, defense, finance, hospitality and health care. He has a B.S. in Computer Science from the College of William and Mary and lives in Aubrun, CA. Brian has been a speaker at numerous renowned conferences, worldwide, and teaches courses and workshops on subjects from Web Security to Data Science and Machine Learning.

Audience

The course is intended for anyone who works as a developer, DBA, manager or business-oriented role with a technical leaning. It will be an engaging, hands on exposure to a wide variety of new skills as well as a path for moving forward in these various disciplines.

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Learning Objectives

Learn how to:

Apply the following skills to start your progression to become a Data Scientist:

  • Maths
  • Statistics
  • Machine learning
  • Visualization
  • Programming languages (R, Julia, Python)
  • Open source Data Science Tools
  • Big Data
  • Linked Data

Pre-Requisites

Prerequisites

The course is intended for a wide audience and assumes only general programming skills.

Bring your own hardware

To participate in this course you are required to bring your own laptop so you can develop with your own tools and languages.

Course Content

  • Data Science as a field
  • Basic statistics and numerical methods for dealing with data
  • Doing Data Analysis in Spreadsheets
  • The R programming language, its environment and online ecosystem
  • R's visualization packages
  • Interacting and visualizing data with D3.js
  • Interacting with Big Data environments in R
  • Interacting with Linked Data in R
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PRINCE2 Foundation & Practitioner
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APMP Certificate
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