Overview
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Leverage Java in your data science career. Learn how to use Java for two components of data science—data engineering and data analysis.
Syllabus
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Introduction
- Welcome
- What you should know
- Using the exercise files
- Java, data science, and IMQAV
- JVM languages
- Downloading software
- Installing software
- Introduction to testing
- Types of tests
- Mock tests
- Code coverage
- Windows, views, and modes
- Projects
- Editor basics
- Refactoring
- Code execution
- Debugging
- Object-oriented principles
- Primitives
- Strings
- Classes and attributes
- Classes and methods
- Classes and constructors
- Exception handling
- Enumerations
- Casting
- Generics
- Annotations
- Program flow control
- Install and use libraries
- gson
- StringUtils
- Introduction to regular expressions
- Literals
- Metacharacters and representations
- Predefined character classes
- Regex quantifiers
- Regex boundaries and anchors
- Regex examples
- Introduction to reflection
- Introspect fields
- Introspect methods
- Introspect constructors
- Introspect annotations
- Introduction to design patterns
- Singleton patterns
- Decorator patterns
- Visitor patterns
- Introduction to magic squares
- Magic squares algorithm
- Adjacency matrix
- Magic characteristics
- Building magic cubes
- Next steps
