What you’ll learn
- Data Science using R programming
- Become a Data Scientist
- Data Science Learning Path
- How to learn Data Science
- Data Collection and Management
- Model Deployment and Maintenance
- Setting Expectations
- Loading Data into R
- Exploring Data in Data Science and Machine Learning
- Exploring Data using R
- Benefits of Data Cleaning
- Cross Validation in R
- Data Transformation
- Modeling Methods
- Solving Classification Problems
- Working without Known Targets
- Evaluating Models
- Confusion Matrix
- Introduction to Linear Regression
- Linear Regression in R
- Simple and Multiple Regression
- Linear and Logistic Regression
- Support Vector Machines (SVM) in R
- Unsupervised Methods
- Clustering in Data Science
- K-means Algorithm in R
- Hierarchical Clustering
- Market Basket Analysis
- MBA and Association Rule Mining
- Implementing MBA
- Association Rule Learning
- Decision Tree Algorithm
- Exploring Advanced Methods
- Using Kernel Methods
- Documentation and Deployment
How to Enroll Data Science with R course?
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