Kotlin for Data Science

Course Outline

PART 1: From Data Science to Production, with Kotlin: The Basics

Why Kotlin?

What is Kotlin?
Why Kotlin for Data Science?
Comparison of Kotlin vs Scala and Python

Setup

JDK
Intellij IDEA
Maven Setup

Kotlin Basics

Your first Kotlin application
Variables
Types and Operators (+ - * / == !=)
Functions
Nullable Types
Project organization, navigation, and refactoring

Flow Control and Classes

if
when
Classes
Data classes
Singletons
Enums

Collections

Ranges and loops
Arrays
Lists
Sets
Maps
Collection Operators
Factory patterns

PART 2: Practical Data Modeling for Production, with Kotlin

Working with Data Sources

Reading text Files
SQL queries
Web requests and Lazy Properties

Functional Programming with Kotlin

Higher Order Functions and lambdas
Lambda Syntax
Generics
Sequences
let() and apply()

Adapting Kotlin to Your Domain

Extension Functions and Properties
Extension Operators
Leveraging DSL’s

Practical applications of Kotlin for data science

Ranking mutual friends in a social network
Using Kotlin with Apache Spark
Using Kotlin-Statistics
Doing matrix math with ND4J (Java's NumPy)
Interactive UI's with TornadoFX
Deploying your Kotlin project

Going Forward

Furthering your knowledge of Kotlin and the JVM