Learn Data Science with Java
Topic: Data
Data science is an incredibly interesting field  not to mention lucrative, with “data scientist” regularly at the top of lists bearing titles like “hottest jobs of 2020”. The ability to use data science in the real world has profound implications for nearly every industry, and it is for this reason that a huge number of companies are looking for programmers who know how to do data science  and conversely, data scientists who know how to program. That’s where Java comes in. As you’ll see in this course, Java for Data Science provides a match made in heaven. Java’s power, flexibility, and popularity make it an incredible tool for the budding data scientist.
What you'll learnand how you can apply it
 Learn what data science is, how it can be used, and the basic datascience process
 Learn the basics of working with and manipulating data in Java
 Learn how to visualize data and some libraries that can help us do so
 Learn the most important datascience algorithms for turning data into information. This will cover things like Nearestneighbor, Bayes, Linear Regression, Decision trees, and more
This training course is for you because...
 You’re a Java developer who wants to advance your career by breaking into the datascience field
 You’re a data scientist who wants to see how to use Java in the field
 You’re neither a datascientist nor a programmer and want to dive headfirst into both
Prerequisites
 Java: Knowledge of basic Java syntax and ObjectOriented Programming concepts.
 Familiarity with mathematical concepts: Some experience with basic algebra.
Course Setup
 Download and install OpenJDK 11 from https://adoptopenjdk.net/
 Download and install your favorite Java IDE
Recommended Preparation
 Video: Core Java 11 for the Impatient LiveLessons, by Cay S. Horstmann https://www.informit.com/store/corejava11fortheimpatientlivelessonsvideotraining9780135235256
Recommended Followup
 Video: Functional Programming for Java LiveLessons, by Simon Roberts https://www.informit.com/store/functionalprogrammingforjavalivelessons9780134778242
 Video: Modern Java Collections, by Simon Roberts https://www.informit.com/store/modernjavacollections9780134663517
About your instructor

Shaun is a lifelong programmer and problemsolving addict. His goal is to help people build incredible software and solve meaningful problems by mastering the art of software development. He currently works as a Senior React Developer, but also has a lot of side gigs, including consulting, freelance development, and online education. Don’t hesitate to get in contact with him if you enjoy his materials.
Schedule
The timeframes are only estimates and may vary according to how the class is progressing
Day 1
Introduction (5 mins)
Learn the Basics of Data Science (55 mins)
 Learn what data science is
 See examples of what data science can do
 Learn the basics of modeling and machine learning
 Learn about the biasvariance tradeoff
 Learn about featureextraction and selection
 Learn the difference between supervised, unsupervised, and reinforcement learning
 Q&A
Break (5 mins)
Gather and use data (55 mins)
 Find and load data using Java
 Perform initial data exploration
 Learn how to clean data
 Learn how to rescale data
 Reduce the dimensionality of data
 Q&A
Break (5 mins)
Learn the KNearestNeighbors Algorithm (55 mins)
 Learn the basics of KNN
 Implement a KNN classifier in Java
 Apply our KNN classifier to data
 Q&A
Day Two
Introduction (5 minutes)
Learn the Naive Bayes Algorithm (50 mins)
 Learn the basics of Naive Bayes
 Implement a Naive Bayes classifier in Java
 Apply our Naive Bayes classifier to data
 Q&A
Break (5 mins)
Learn the Linear Regression Algorithm (55 mins)
 Learn the basics of Linear Regression
 Implement a Linear Regression classifier in Java
 Apply our Linear Regression classifier to data
 Q&A
Break (5 mins)
Learn about Clustering (55 mins)
 Learn the basics of Clustering
 Implement a Clustering algorithm in Java
 Apply our Clustering algorithm to data
 Q&A
Course Wrapup