Data Science, AI, and Machine Learning with R - Gain practical experience in R for Data Analysis, Machine Learning and Artificial Intelligence. Become a Data Scientist.
What you'll learn
- 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.
- Explore re
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