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Machine Learning Scientist in R

A machine learning scientist researches new approaches and builds machine learning models.
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RMachine Learning65 hours2,618

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Track Description

Machine Learning Scientist in R

Master the essential skills to land a job as a machine learning scientist! You'll augment your R programming skillset with the toolbox to perform supervised and unsupervised learning. You'll learn how to process data for modeling, train your models, visualize your models and assess their performance, and tune their parameters for better performance. In the process, you'll get an introduction to Bayesian statistics, natural language processing, and Spark.

Prerequisites

There are no prerequisites for this track
  • Course

    1

    Supervised Learning in R: Classification

    In this course you will learn the basics of machine learning for classification.

  • Course

    In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

  • Course

    Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

  • Course

    This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

  • Course

    Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

  • Course

    10

    Machine Learning with Tree-Based Models in R

    Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

  • Skill Assessment

    bonus

    Machine Learning Fundamentals in R

  • Course

    Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

Machine Learning Scientist in R
16 courses
Track
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