Machine Learning with R Course with Certification

Objective: Learn to implement machine learning algorithms in R for classification, regression, and clustering while mastering model evaluation and optimization techniques.

Total Duration of the training: 24 Hours of Live, Interactive, Trainer-Led Sessions

Additional Components: 50+ Hours of MCQs and Assignments | 16 Hours of Hands-on Training with R

This course introduces the core concepts of Machine Learning, including data preprocessing, exploratory data analysis, and model building using R. Learners will gain practical insights through real-life case studies involving predictive analytics, decision trees, clustering, and ensemble techniques.

Introduction to Machine Learning with R

• Overview of ML concepts, workflow, and use cases.
• Understanding R environment and setup for ML.



Data Preprocessing and Visualization

• Data cleaning, normalization, and feature selection.
• Exploratory data analysis using ggplot2 and lattice.



Supervised Learning Algorithms

• Linear and Logistic Regression models.
• Decision Trees, Random Forests, and Naïve Bayes.



Unsupervised Learning Algorithms

• K-means clustering, hierarchical clustering, and PCA.
• Dimensionality reduction and feature extraction.



Model Evaluation and Optimization

• Cross-validation, confusion matrix, and ROC analysis.
• Hyperparameter tuning and model selection.



Real-World Projects and Case Studies

• Predictive analytics for business and finance datasets.
• End-to-end project using R for ML model deployment.

• Data Scientists and Analysts
• Statisticians and Researchers
• Machine Learning Enthusiasts
• Developers aiming to transition into ML roles
• Anyone interested in R-based predictive modeling

Certification

• Upon completion, participants receive a Machine Learning with R Certification from Merit Global Training, validating their expertise in R programming and applied ML techniques.

The Machine Learning with R Course with Certification by Merit Global Training equips learners with the knowledge and hands-on skills to apply Machine Learning algorithms using the R programming language. Participants gain practical experience in supervised and unsupervised learning, model evaluation, and real-world data problem-solving using R’s most powerful libraries and tools.

Data Scientist and R Programming Expert with over 10 years of experience in analytics, predictive modeling, and developing end-to-end machine learning solutions for global enterprises.

By the end of this 24-hour course, learners will be able to: