Computer Science1 course

Computer Science

Computing concepts: binary, abstraction, the internet and the impact of computing.

About Computer Science

Computer science is the study of computation: how information is represented, how problems are broken into steps, and how those steps run on real machines and networks. An introductory principles course covers binary data, abstraction, algorithms, programming, the internet and the social impact of computing.

Many ideas are mathematical at heart. Binary is base-2 place value, so $1011_2 = 8 + 2 + 1 = 11$ ; $n$ bits can store $2^n$ different values; and an algorithm's efficiency is described by how its running time grows with the input. These ideas explain why some programs scale and others do not.

These principles apply well beyond programming jobs: understanding how data is stored and transmitted helps with privacy and security decisions, and algorithmic thinking helps organise any complex task. The course is also a strong foundation for AP Computer Science and university computing courses.

Computer Science Principles

Broad introduction to how computers and networks work. (High school)

Binary and Data

Computers store everything, from numbers to photos to this sentence, as patterns of bits, each 0 or 1. Binary is base 2: each place is worth a power of two, so $1011_2 = 8 + 0 + 2 + 1 = 11$ . Eight bits make a byte, which can hold $2^8 = 256$ different values.

The Internet

The internet is a network of networks that moves data in small chunks called packets. Each packet carries part of the message plus addressing information, and routers forward packets hop by hop toward their destination. Packets from one message may take different routes and arrive out of order; the receiving computer reassembles them.

Full Computer Science Principles course outline

How to study Computer Science

Trace small programs by hand, writing the value of each variable after every line.
Convert numbers between binary, decimal and hexadecimal until it is routine.
Describe an algorithm in plain steps before writing code.
For each technology topic, know a benefit, a risk and an example.

Before you start: Arithmetic and logical thinking; no programming experience required.
Where it leads: Programming, data structures and algorithms. Students who enjoy the data and networking units often continue into cybersecurity, data science or AP Computer Science A.

Key terms in Computer Science

Algorithm: A finite, precise sequence of steps that solves a problem, such as finding the largest value in a list.
Binary: Base-2 notation using only 0 and 1; each place is a power of two, so $1011_2 = 8 + 2 + 1 = 11$ .
Abstraction: Hiding detail behind a simpler interface, such as calling a function without needing to know how it works inside.
Boolean logic: Logic on true and false values with AND, OR and NOT, the basis of conditions in code and of digital circuits.
Big-O notation: A way to describe how running time grows with input size $n$ , keeping only the dominant term, for example $O(n^2)$ .
Data representation: How text, images and sound are stored as bits, for example characters as numeric codes and images as grids of pixel values.