Learn Machine Learning using R
Specialized instruction in statistical learning strategies employing the R programming language is provided in our Machine Learning with R course. With a focus on model interpretation and statistical rigor, you’ll learn how to use R’s extensive packages to implement machine learning algorithms.
Skills You’ll Gain:
- R programming fundamentals
- Data cleaning and manipulation
- Statistical hypothesis testing
- Regression and classification models
- Time series forecasting
- Data visualization
- Real-world project implementation
Module 1 - Introduction to R programming
- R Studio IDE
- Basic R Operations
- Variables and Data Types
- R Help Features
Module 2 - Data Handling in R
- Vectors and Matrices
- Data Frames
- cbind/rbind Functions
- Data Cleaning Techniques
Module 3 - Data Import Techniques
- Reading CSV/Excel
- MySQL Integration
- R Data Formats
Module 4 - Loops and Date Handling
- For/While Loops
- Date Conversion
- Date Slicing
- Time Differences
Module 5 - Exploratory Data Analysis
- Box Plots
- Histograms
- Scatterplots
- Multivariate EDA
Module 6 - Statistics and Machine Learning
- Hypothesis Testing
- Linear/Logistic Regression
- Decision Trees
- SVM
- Time Series Forecasting
Module 7 - Project Work
- 3 Real-time Projects
Earn a recognized credential that validates your technical expertise and opens doors to new career opportunities.
Why Learn Machine Learning using R?
- Strong statistical foundation
- Excellent for data exploration
- Good visualization capabilities
- Comprehensive collection of packages
- Strong in academia and research
- Reproducible research capabilities
- Good for statistical modeling
- Active community in data science
- Integration with other languages
- Good documentation
Whatspp Contact
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