Applied Machine Learning Methods (Using R)

  • Course level: Intermediate  
There are no active Semester Schedule for this course   Pre-registar


This course is designed for data professionals in intermediate level who are interested to build machine learning algorithms and predictive models with R in real data analysis projects.


To improve your knowledge on machine learning and AI
To build the robust predictive analytics models
To improve the accuracy of machine learning models
To know how to choose the most related Machine Learning

model in real projects


Fundamentals of Machine Learning
Machine Learning pipeline
Underfitting, Overfitting and Generalization
Data preprocessing and visualization
Machine Learning - Statistics essentials
Supervised and unsupervised algorithms
All Regression algorithms
Decision Trees and ensembling methods
K-Nearest Neighbors (K-NN)
Support Vector Machine (SVM)
Naive Bayes
K-Means Clustering
Hierarchical Clustering
Dimensionality Reduction
Bias vs Variance Tradeoff
Model Evaluation and Performance
Introduction to Advanced Machine

Learning Reinforcement

Learning and Deep Learning

Registration fee :
€ 590

Target audience

  • IT professionals
  • Computer Science and IT Students
  • Data Scientists
  • Data Analysts
  • Technical managers


  • Basic knowledge of R and R
  • Studio
  • Basic knowledge of descriptive statistics and mathematics