South 고등학교 2학년 Informatics

Chapters: 5

1. Computing systems

Wired and wireless networks · Internet of Things · Physical computing systems

How Networks Grew and How Data Travels – A computer network is a group of connected devices that share data. Networking began with ARPANET (1969), grew into NSFNET (1980s) for universities, and joined with other networks to become the Internet, a network of networks. Every data communication has five parts: sender, receiver, message, communication media and protocol. Bandwidth is the range of frequencies a channel can carry (in Hz); data rate is how many bits travel per second (bps). Every device on a network has an IP address. Data can move by circuit switching (a fixed path is booked first) or packet switching (data is cut into packets that travel on their own).
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.
Physical Computing: Making Code Sense and Move – Physical computing joins code to the real world. Sensors measure something (light, temperature, distance, button presses) and turn it into a number. A microcontroller runs a program that decides what to do with that number. Actuators (LEDs, buzzers, motors, screens) act on the world. This input–process–output cycle runs again and again in a loop. Using thresholds, conditions and feedback, we build night lights, smart plant waterers, wearables and interactive art.

2. Data

Data compression · Encryption · Big data · Analysing big data

Data Compression – Compression makes a file smaller so it uses less storage and travels faster. Lossless compression (RLE, Huffman, dictionary methods, ZIP, PNG) gives back exactly the original data. Lossy compression (JPEG, MP3, MP4) removes detail people hardly notice, so files get much smaller but the lost detail cannot return. Compression ratio = original size ÷ compressed size.
Cryptography: How Secret Messages Keep Data Safe – Cryptography is the science of keeping messages secret and trustworthy. A normal message (plaintext) is mixed with a key to make a secret message (ciphertext); this is encryption. Turning it back with the right key is decryption. Old ciphers like the Caesar cipher shift letters. Modern systems use symmetric encryption (one shared key) and asymmetric or public-key encryption (a public key to lock, a private key to unlock). Hashing makes a fixed-length fingerprint of data to check it was not changed, and digital signatures prove who sent a message. Your phone uses all of these every time you open a website with https or send a chat message.
Big Data – Big data is data that is too big, too fast or too mixed to store and process on one ordinary computer with normal tools. We describe it with Volume (how much), Velocity (how fast it arrives) and Variety (how many kinds). To handle it, the work is split across many machines that run at the same time (distributed processing, for example MapReduce). Big data is often stored as simple facts or as a graph of nodes and links, and it is used for weather forecasts, maps, health, shopping and training AI. It also raises questions about privacy and fairness.
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.

3. Algorithms and programming

Decomposing complex problems · Sorting algorithms · Searching algorithms · Data types · Standard and file input/output · Multidimensional data structures · Complex control structures · Classes and objects · Programs for real problems · Program performance

Sorting Algorithms – A sorting algorithm puts a list in order. Bubble sort swaps neighbours, insertion sort slides each item into a sorted part, selection sort picks the smallest each time, and merge sort splits the list and merges sorted halves. Merge sort needs far fewer comparisons on long lists (about n log₂ n instead of about n²/2).
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.
Python Basics: Modes, Variables, Data Types and Operators – Python runs in interactive mode (one line at a time) or script mode (a saved .py file). Blocks are shown by indentation. Variables are names tied to values; every value has a data type, and some types are mutable. Operators build expressions that Python works out by precedence. input() reads text, int()/float()/str() convert types, and debugging fixes syntax, runtime and logical errors.
File Handling in Python: Save Data That Lasts – Variables vanish when a program ends; files keep data on the disk. A text file stores characters in lines, a binary file stores raw bytes (such as pickled Python objects), and a CSV file stores table rows with commas. You open a file with open(path, mode), using an absolute or relative path and a mode such as r, w, a, r+, rb or wb. The with statement closes the file for you. Text files use write, writelines, read, readline and readlines. seek moves the file pointer and tell reports where it is. pickle.dump and pickle.load save and load objects in binary files, letting you search, append and update records. The csv module's writer (writerow, writerows) and reader handle CSV files.
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.
Flow of Control in Python – Flow of control is the order in which statements run. Python has three kinds: sequential (top to bottom), selection (if, if-else, if-elif-else) and repetition (for and while loops). Blocks are marked by indentation (usually 4 spaces after a colon). range(start, stop, step) gives numbers from start up to but not including stop. while repeats as long as a condition is true. break exits a loop at once; continue skips to the next turn. A loop inside another is a nested loop and is used for patterns; loops with an accumulator are used for series sums.
Control Statements in Python: if-else, while and for – Normally Python runs lines one after another (sequence). Control statements change this flow. if-else chooses one of two paths; if-elif-else picks the first true condition from many. while repeats a block while a condition is true; for repeats once for each item of a sequence such as range(start, stop, step).
Object-Oriented Programming (OOP) – Object-oriented programming builds a program out of objects. A class is a blueprint that lists the data (attributes) and actions (methods) its objects will have. Each object is made from a class and keeps its own data. The four big ideas are encapsulation (hide data behind methods), inheritance (a new class reuses an old one), polymorphism (the same method call behaves in the right way for each object) and abstraction (show only what is needed).
Programming Basics: Sequence, Selection, Loops and Functions – A program is a set of exact instructions a computer follows. Every program is built from three structures: sequence (steps in order), selection (if/else choices) and iteration (loops). Variables store values. Functions group code into reusable, named blocks, which makes programs modular and easier to test, debug and maintain.
Algorithm Complexity: How Fast Does an Algorithm Grow? – Many algorithms can solve the same problem, but some need far more steps. We measure an algorithm by counting its basic steps as the input size n grows, not by stopwatch seconds. Big O notation names the growth: O(1) constant, O(log n) logarithmic, O(n) linear, O(n log n), and O(n²) quadratic. Linear search is O(n), binary search is O(log n); bubble sort is O(n²), merge sort is O(n log n). Memory used is space complexity.

4. Artificial intelligence

Intelligent agents · Machine learning types · Solving problems with ML

Artificial Intelligence: How Machines Learn to Think – Artificial intelligence (AI) is the skill of a computer system to do tasks that normally need human thinking: seeing, understanding speech, deciding and learning. An AI system is an agent that senses, thinks and acts. Old AI followed rules written by people. Modern AI mostly uses machine learning: it finds its own rule from many labelled examples (data). Neural networks are layers of simple units whose link strengths (weights) change during training. AI is used in maps, translation, health, farming and games. It can be wrong or unfair when its data is one-sided (bias), so people must check it, protect privacy and stay responsible.
Machine Learning – Machine learning (ML) is a way for computers to learn a rule from examples instead of being told the rule. We give data made of features (inputs) and, in supervised learning, labels (answers). The machine fits a model: regression predicts a number, a decision tree asks yes/no questions to pick a class, and k-means clustering groups unlabelled data. We train on most of the data, test on data it never saw, and measure accuracy or error. A model that only memorises (overfits) fails on new data.

5. Digital culture

Digital technology and society · Protecting and sharing information · Information security

Digital Society: How Information Technology Changes Our Lives – A digital society (also called an information society) is a society where making, sharing and using information with computers and networks is a main part of life, work and government. Information moves fast, reaches everywhere and can be copied at almost no cost. Software has changed shopping, banking, health, school and friendship. New jobs appear (app developer, data analyst) while some old jobs shrink. Every online action leaves data, so privacy matters. Not everyone is connected (the digital divide), and too much screen time or gaming can harm health. A good digital citizen uses the benefits and manages the risks.
Digital Footprints and Netiquette – A digital footprint is the trail of data we leave online. Active footprints are shared on purpose (posts, comments, forms); passive footprints are collected without us noticing (cookies, browsing history, location, IP address). Footprints are hard to erase and can be seen by others later. We live in a digital society where learning, banking, shopping and government services are online; a responsible user of it is a digital citizen (netizen). Net etiquette means being ethical (respect copyright, share reliable information), respectful (privacy, diversity, no bullying) and responsible (avoid oversharing, don't feed trolls). Communication etiquette asks us to be precise, polite and credible; social media etiquette asks us to choose passwords and privacy settings wisely, think before uploading, and verify before sharing.
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.