China 高二 Information Technology
Chapters: 3
1. Sel.1 Data and data structures
Value of data · Data structures; arrays vs linked lists · Linear lists, stacks, queues, strings, binary trees · Iteration, recursion, sorting and searching
- The Value of Data – Data are recorded facts: numbers, words, images, sounds, measurements. Alone they are just raw records. Data become valuable in three ways. As a raw material they are processed into information, patterns and decisions, like ore becoming metal. As a means of production they guide machines, farms, shops and services to make more with less. As infrastructure they form a shared network that many services rely on, like roads and electricity. Value grows when data are correct, up to date, relevant, and combined with other data. It falls when data are wrong, old or misused, and privacy and fairness must be protected.
- Data Structures: Arrays, Lists, Stacks, Queues and Trees – A data structure is a way of organising data in memory so a program can use it well. Arrays keep items in numbered boxes for instant access by index. Linked lists chain nodes with pointers, so inserting is easy. Stacks work last-in-first-out, queues first-in-first-out. Dictionaries find values by key, and trees store data in levels so searching is fast. Choosing the right structure makes programs faster and simpler.
- Searching and Sorting Algorithms – A searching algorithm finds an item in a list; a sorting algorithm puts a list in order. Linear search checks items one by one and works on any list. Binary search halves a sorted list each time and is much faster. Bubble sort swaps neighbours pass by pass; merge sort splits the list and merges sorted halves, which is faster for big lists.
2. Sel.2 Network basics
Network types and media · TCP/IP, IP, DNS; devices; network OS; LAN security · Encryption, authentication, firewalls; sharing resources · IoT and innovative services; privacy
- Transmission Media and Network Devices: The Roads and the Traffic Police – Transmission media are the paths that carry signals. Wired (guided) media are twisted pair cable, coaxial cable and optical fibre. Wireless (unguided) media are radio waves, microwaves and infrared. Network devices connect and direct data: a modem changes digital data to analog and back; an Ethernet card (NIC) and RJ45 connector join a computer to a cable; a Wi-Fi card joins it without wires; a repeater boosts a weak signal; a hub sends data to every port; a switch sends it only to the right port; a router sends packets between different networks; a gateway joins networks that use different protocols.
- Computer Networks: Types, Devices and Topologies – A computer network is a group of devices connected to share data and resources. By area, networks are PAN, LAN, MAN and WAN. Devices do different jobs: a modem converts digital and analog signals, a repeater boosts a weak signal, a hub sends data to all ports, a switch sends it only to the right device, a router joins networks and chooses a path, and a gateway joins networks that use different protocols. Topology is the layout of connections: star, bus, tree and mesh, each with its own strengths and weaknesses.
- Cybersecurity: Threats and How We Stop Them – Cybersecurity protects computers, networks and data. It aims for confidentiality, integrity and availability (the CIA triad). Common threats are malware, phishing and social engineering, brute-force password attacks and denial of service. Defences include strong authentication, encryption, firewalls, anti-malware software, updates, access control and backups.
- Internet of Things (IoT) – The Internet of Things (IoT) is a network of everyday objects that have sensors, a small computer and a network connection, so they can collect data, share it over the internet and act on it. A sensor turns a physical change into data, a microcontroller processes it, the network (Wi-Fi, Bluetooth, Zigbee, 4G/5G, LoRa) carries it to a cloud server or app, and an actuator turns commands into action. IoT is described in three layers: perception, network and application. It brings convenience and saves energy, but needs strong privacy and security.
3. Sel.3 Data management and analysis
Data science · Requirements; collection; cleaning · Relational databases; SQL; backup · Analysis methods and tools
- Data Science: From a Question to a Tested Model – Data science is using data, maths and computers to answer questions and make predictions. A project follows a cycle: ask a clear question, collect data, clean it (fix or remove errors), explore it with charts and averages, build a model, test the model, and report the result. A model is a simple rule learned from data, such as marks ≈ 35 + 7 × hours. Prediction (regression) models give a number; classification models give a group. We test models on new data and measure accuracy or error, then choose the best one. Data science is used in health, sport, weather, shops and farming. Real projects often fail at first, so patience and checking matter.
- Data Analysis – Data analysis means turning raw data into answers. It follows a cycle: ask a question, collect data, clean it (remove errors, repeats and blanks), organise and transform it, analyse it with summaries such as mean, median, range and patterns, show it with a good chart, and draw a careful conclusion. Watch for outliers, small samples and bias, and remember that a correlation between two things does not prove that one causes the other. Data must also be stored safely and used with permission.
- SQL with MySQL: Create Tables, Change Rows and Ask Questions – SQL (Structured Query Language) is the language used to talk to a relational DBMS like MySQL. DDL commands (CREATE, ALTER, DROP) define tables; DML commands (INSERT, UPDATE, DELETE) change rows; DQL (SELECT) reads data. Each column has a data type such as INT, FLOAT, CHAR, VARCHAR or DATE. SELECT … WHERE filters rows using relational operators, BETWEEN, AND/OR/NOT and IS NULL.