In this module, we will introduce a data set containing details about earthquakes around the world. You will learn how to pull this data into a program, search through the data, and filter the data based on desired criteria. By the end of this module, you will be able to (1) write programs that include multiple classes and ArrayLists of class types, (2) find the maximum value in an ArrayList, (3) use a Filter interface to search through data, (4) implement interfaces with method signatures, and (5) combine several filters together.

In this module, you will continue using real earthquake data to explore several sorting algorithms. You will learn how to implement a selection sort and a bubble sort, then be introduced to a Java method Collections.sort, which sorts with much greater efficiency. By the end of this module, you will be able to (1) implement several sorting algorithms from scratch, (2) use efficient pre-existing sorting classes, (3) modify a class’s compareTo method to choose the criteria by which objects of that type are ordered, and (4) write classes that implement the Comparator interface to create interchangeable sorting criteria.

In this module, you will explore some of the underlying concepts of predictive text. The first lesson will introduce random character generation and then how to train the character selection based on an input text. The second lesson will extend this concept to complete words. By the end of this module, you will be able to: (1) base random text generation on the frequency of characters in a training text, (2) collect a set of characters that occur in a text after randomly chosen initial character(s) to create a semi-random text, (3) extend the predictive text generation to use whole words, and (4) implement your own .equals method to compare complex data types.