- Type Validation
- Level Foundational
Machine Learning and Predictive Modeling in R
The Machine Learning and Predictive Modeling in R credential demonstrates an earner's understanding of machine learning and predictive modeling concepts and how to perform related analyses in R, including Linear and Logistic Regression, PCA and Nearest Neighbor Algorithms, Clustering Methods, Decision Trees and CART Modeling, Naïve Bayes Classification, Natural Language Processing, Market Basket Analysis, and Neural Networks and Support-Vector Classifiers.
- Type Validation
- Level Foundational
Skills
- Algorithms
- Artificial Neural Networks
- Bayesian Statistics
- Clustering Methods
- Decision Tree Learning
- Decision Trees and CART Modeling
- Linear and Logistic Regression
- Logistic Regression
- Machine Learning
- Market Basket Analysis
- Naïve Bayes Classification
- Natural Language Processing
- Natural Language Processing (NLP)
- Nearest Neighbor Algorithms
- Neural Networks
- PCA
- Predictive Modeling
- R (Programming Language)
- Support-vector Machines
Earning Criteria
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8 coding and analysis projects were completed with an 80% or higher. Participants were assessed on the submission of code that correctly performed each task for a given dataset and assessment of predictability of the fitted model. Participants were provided with all necessary datasets. Participants may have been asked to visualize model output as part of the coding project. All coding projects required the submission of code and the submission of a document that described the output.