- The IMQAV model
- Downloading software
- Installing and setting up a Java coding environment
- Mock tests
- Code coverage
- Using windows, views, and modes in IntelliJ IDEA
- Creating classes and attributes
- Creating constructors
- Casting variables
- Matching literals with regular expressions
- Regular expressions
- Design patterns
Skill Level Intermediate
- [Charles] This course explains how you can use java for two components of data science, data engineering and data analysis. This course is not an exhaustive treatment of every facet of java. Rather, it is a selection of valuable topics to help you in your data science career. The focus of the course is object-oriented java. A guiding principle for the course is test-driven development. Throughout the course, I'll use the free community edition of IntelliJ from JetBrains to present java examples including java classes, methods and operations, libraries, regular expressions, reflection, and design patterns.
I'll conclude the course by illustrating how you can apply the data science skills that you will learn in the course to an interesting problem, using java to create magic squares and Sudoku puzzles. I enjoy using data science in my work, designing guidance centers for robotic vehicles. I hope that you will enjoy java and data science as much as I do, let's get started.
Java: Database Integration with JDBCwith David Gassner2h 51m Intermediate
NumPy Data Science Essential Trainingwith Charles Kelly3h 54m Intermediate
1. Getting Started with Java
2. Test-Driven Development
3. IntelliJ IDEA
4. Object-Oriented Java
6. Regular Expressions (Regex)
8. Design Patterns
9. Applying Data Science
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