What this learning path covers

Module 1, Java for data science, this module takes an expansive yet cursory approach to various aspects of data science. A brief introduction to the field is presented in the first chapter. Subsequent chapters cover significant aspects of data science, such as data cleaning and the application of neural networks. The last chapter combines topics discussed throughout the book to create a comprehensive data science application.

Module 2, Mastering Java for data science, in this module we will see how we can utilize Java’s toolbox for processing small and large datasets, then look into doing initial exploration data analysis.

Next, we will review the Java libraries that implement common Machine Learning models for classification, regression, clustering, and dimensionality reduction problems. Then we will get into more advanced techniques and discuss Information Retrieval and Natural Language Processing, XGBoost, deep learning, and large scale tools for processing big datasets such as Apache Hadoop and Apache Spark. Finally, we will also have a look at how to evaluate and deploy the produced models such that the other services can use them.