數據科學的編程培訓

Section 1: Creative code - Computational thinking

Understanding what you can do with ProcessingJS and apply the basics

to start coding with colour; Learn how to qualify and express how algorithms work.

Section 2: Building blocks - Breaking it down and building it up

Understand how data can be represented and used as variables and learn

to manipulate shape attributes and work with weights and shapes using code.

Section 3: Repetition - Creating and recognising patterns

Explain how and why using repetiton can aid in creating code and begin using repetition to manipulate and visualise data.

Section 4: Choice - Which path to follow

How to create simple and complicated choices and how to create and use decision points in code.

Section 5: Repetition - Going further

Discussing advantages of repetition for data visualisation and applying and reflecting

on the power of repetitions in code. Creating curves, shapes and scale data in code.

Section 6: Testing and Debugging

Understanding why and how to comprehensively test your code and debug code examples using line tracing techniques.

Section 7: Arranging our data

Exploring how and why arrays are used to represent data and how static and dynamic arrays can be used to represent data.

Section 8: Functions - Reusable code

Understand how functions work in ProcessingJS and demonstate how to deconstruct a problem into useable functions.

Section 9: Data Science in practice

Exploring how data science is used to solve programming problems and how

to solve big data problems by applying skills and knowledge learned throughout the course.

Section 10: Where next?

Understand the context of big data in programming and transform a problem description into

a complete working solution using the skills and knowledge you've learned throughout the course,

and explore how you can expand the skills learned in this course by participating in future courses.