What you’ll learn-50.5 hours course
- Grasp the core concepts of data science and its applications in various industries.
 - Set up and navigate the R programming environment effectively.
 - Master R programming fundamentals, including data types, structures, operators, and control flow.
 - Understand essential statistical and probability concepts for data analysis.
 - Collect data from diverse sources (flat files, databases, web, APIs).
 - Clean, manipulate, and preprocess data to ensure its quality and suitability for analysis.
 - Conduct exploratory data analysis to uncover patterns and insights using visualizations.
 - Analyze and interpret data effectively using R’s powerful statistical and visualization tools.
 - Build and evaluate various machine learning models for: Prediction (regression), Classification, Clustering, Association rule mining.
 - Apply dimensionality reduction methods like PCA and LDA.
 - Utilize ensemble methods (bagging and boosting) to improve model performance.
 - Build and deploy machine learning models using R to solve real-world problems.
 - Think critically about data and apply data science techniques in a variety of contexts.
 - Complete an end-to-end capstone project to solidify learning and demonstrate practical skills in data science and machine learning using R.
 
How to Enroll Data Science, AI, and Machine Learning with R course?
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