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Practical Data Science with R Training

4.8
(4.8)

Practical Data Science with R (PDSwR) is the course to start with if you are starting as a data scientist or aspire to be one. If you already practice data science, PDSwR will fill in knowledge gaps and even give you a new perspective on the technologies you now employ.

  • Category : Data Science

Course Price : $2795 Per Participant

Course Description

Practical Data Science with R (PDSwR) is the course to start with if you are starting as a data scientist or aspire to be one. If you already practice data science, PDSwR will fill in knowledge gaps and even give you a new perspective on the technologies you now employ.

This course covers data science, a discipline that builds predictive models using findings from machine learning, statistics, and computer science.

Critical business data is being gathered, curated, examined, and reported more frequently by business analysts and engineers. Without much academic theory or complex mathematics, one can efficiently complete daily Data Science work using the R language and its companion tools.

You can learn how to use the R programming language and practical statistical approaches in ordinary business circumstances with the help of experimental data science with R training.

It demonstrates how to conduct experiments (such as A/B testing), create prediction models, and deliver results to audiences of different levels using examples from business intelligence, marketing, and decision support.

Microsoft Course Microsoft Course
500+

Courses

experience experience
20+

Years of Experience

learners learners
95K+

Global Learners

What you will learn

  • green-tick Business professionals' guide to data science
  • green-tick Utilizing R to conduct statistical analyses
  • green-tick Planning through delivery: the lifespan of a project
  • green-tick Many immediately recognizable usage cases
  • green-tick Effective data presentations: key elements

Prerequisites

  • Familiarity with SQL databases, statistics, and R

Who should attend this course?

  • Data Scientists
  • Data Engineers
  • Data Analysts
  • Business Analysts

Schedules

Oops! For this course, there are currently no public schedules available. Clicking on "Notify Me" will allow you to express your interest.

For dates, times, and location customization of this course, get in touch with us.

You can also speak with a learning consultant by calling 800-961-0337.

Curriculum

a. The data science process

  • The roles in a data science project
  • Stages of a data science project
  • Setting expectations
  • b. Loading data into R

  • Working with data from files
  • Working with relational databases
  • c. Exploring data

  • Using summary statistics to spot problems
  • Spotting problems using graphics and visualization
  • d. Managing data

  • Cleaning data
  • Sampling for modeling and validation
  • a. Choosing and evaluating models

  • Mapping problems to machine learning tasks
  • Evaluating models
  • Validating models
  • b. Memorization methods

  • KDD and KDD Cup 2009
  • Building single-variable models
  • Building models using many variables
  • c. Linear and logistic regression

  • Using linear regression
  • Using logistic regression
  • d. Unsupervised methods

  • Cluster analysis
  • Association rules
  • e. Exploring advanced methods

  • Using bagging and random forests to reduce training variance
  • Using generalized additive models (GAMs) to learn nonmonotone relationships
  • Using kernel methods to increase data separation
  • Using SVMs to model complicated decision boundaries
  • a. Documentation and deployment

  • The buzz dataset
  • Using knitr to produce milestone documentation
  • Using comments and version control for running documentation
  • Deploying models
  • b. Producing effective presentations

  • Presenting your results to the project sponsor
  • Presenting your model to end users
  • Presenting your work to other data scientists
  • Course Details

    • enroll enroll-green
      Enrolled: 1928
    • duration duration green
      Duration: 5 Days

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