Technologies / Artificial Intelligence

Data Mining and Machine Learning in R

The training provides practical knowledge of data mining and machine learning using the R language. The program covers both theoretical foundations and practical applications of data mining techniques and implementation of machine learning algorithms. Through workshops, participants learn to build and evaluate predictive models and discover hidden patterns in data. The classes are conducted in a workshop format using real data sets.

Issues

Data processing and cleaning
Exploratory Data Analysis (EDA)
Classification and regression algorithms
Data grouping techniques
Dimensionality reduction
Methods for assessing the quality of models
Cross-validation
Parameterization of models
Interpretation of results
Anomaly detection
Cluster analysis
Preparation of data for analysis

Benefits

Practical ability to apply CRISP-DM methodology to data analysis projects.
Ability to select and implement appropriate machine learning algorithms for different types of problems.
Master data preparation and cleaning techniques for analytics.
Proficiency in using advanced R language libraries for data mining.
Ability to build, evaluate and interpret predictive models.
Ability to detect and analyze hidden patterns in data sets.
Knowledge of practical methods for implementing machine learning models.

Who is this training for?

Data Scientists

Machine learning analysts

Data mining specialists

Predictive analysts

Researchers involved in data analysis

Machine learning programmers

Artificial intelligence specialists

Prerequisites

Basic knowledge of statistics and data analysis
Knowledge of the basics of programming in R
General knowledge of mathematics at the university level
Basic experience in working with databases
Understand basic data modeling concepts

Training program

Data preparation
Exploratory data analysis
Dimensionality reduction techniques
Unsupervised learning

Association rules

Dimensionality reduction
Supervised learning

Random forests
Support vector machines

Evaluation and implementation of models

Measures of model quality
Tuning hyperparameters
Implementing models

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Frequently asked questions

What are the prerequisites for this training?

For Data Mining and Machine Learning in R we recommend: Basic knowledge of statistics and data analysis; Knowledge of the basics of programming in R; General knowledge of mathematics at the university level.

What is the format and duration of this training?

The training lasts 2 days and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: Data Scientists; Machine learning analysts; Data mining specialists.