R Ultimate 2024: R for Data Science and Machine Learning

R Basics, Data Science, Statistical Machine Learning models, Deep Learning, Shiny and much more (All R code included)

Created by: Bert Gollnick
Data Scientist

What Will I Learn?

• learn all aspects of R from Basics, over Data Science, to Machine Learning and Deep Learning
• learn R basics (data types, structures, variables, and more)
• learn R programming (writing loops, functions, and more)
• data im- and export
• basic data manipulation (piping, filtering, aggregation of results, data reshaping, set operations, joining datasets)
• data visualisation (different packages are learned, e.g. ggplot, plotly, leaflet, dygraphs)
• advanced data manipulation (outlier detection, missing data handling, regular expressions)
• regression models (create and apply regression models)
• model evaluation (What is underfitting and overfitting? Why is data splitted into training and testing? What are resampling techniques?)
• regularization (What is regularization? How can you apply it?)
• classification models (understand different algorithms and learn how to apply logistic regression, decision trees, random forests, support vector machines)
• association rules (learn the apriori model)
• clustering (kmeans, hierarchical clustering, DBscan)
• dimensionality reduction (factor analysis, principal component analysis)
• Reinforcement Learning (upper confidence bound)
• Deep Learning (deep learning for multi-target regression, binary and multi-label classification)
• Deep Learning (learn image classification with convolutional neural networks)
• Deep Learning (learn about Semantic Segmentation)
• Deep Learning (Recurrent Neural Networks, LSTMs)
• More on Deep Learning, e.g. Autoencoders, pretrained models, ...
• R/Shiny for web application development and deployment

Requirements

• no prior knowledge required - just be passionate to gain new skills

Target audience

• R beginners interested in learning R
• data science practitioners who want to deepen their knowledge
• developers who want to learn different aspects of Machine Learning