1.1.1 Definition and Scope

1. What is Computer Science?

1.1.1 What It Is and What It Covers

Computer Science is a lively and many-sided school subject that's much more than just writing computer programs. It's the careful study of how computers work, how information is handled, and how things can be made to happen automatically. This field has two main parts: deep ideas and real-world uses. It's basically the study of how to think about, design, build, and make computer programs and systems work well. It also looks at what computers can and can't do.  

The Association for Computing Machinery (ACM), a big group for computer professionals, says that Computer Science is about "design and new ideas that come from computer rules." They focus on the "basic ideas of computing, step-by-step instructions (algorithms), and programming skills". These basic ideas are then used in many areas like computer operating systems, artificial intelligence (AI), and how information is used. Computer scientists do many things, like creating and building software, solving tough programming puzzles, and guiding other programmers to help them learn new ways of doing things. They also figure out good ways to store information in databases, send data over networks, and show complicated pictures. To do this, they need to understand math ideas, how to look at data, safety rules, algorithms, and how computers think. The way new ideas and practical uses work together makes this field strong, helping it grow and change all the time.  

To really get what Computer Science covers, it's good to know how it's different from other computer-related jobs. The ACM puts computer jobs into five main groups: Computer Science, Computer Engineering, Software Engineering, Information Systems, and Information Technology. Data Science is also a separate but connected field.  

• Computer Engineering mostly focuses on building computer systems that have both computer parts (hardware) and programs (software), and how they talk to each other. It mixes electrical engineering with computer science to make things like cell phones, electronics, and medical devices. Unlike Computer Science, it's more about designing computer hardware and devices, not just software.  
• Software Engineering is all about designing, building, and carefully testing big, complicated, and often very important software programs. This job uses computer science ideas and engineering methods to build strong software for things like airplane controls, healthcare, and secret codes. It also sets up rules for how to use programs, including fixing problems, testing, making them safe, making them work for many users, and making them fast.  
• Information Systems (IS) uses computer ideas for business tasks. It connects computer knowledge with how businesses are run. It focuses on designing, building, and testing information systems for different business needs, like payroll, human resources, company databases, online shopping, and money matters. IS cares about using information smartly, with technology being a tool to create, process, and share it.  
• Information Technology (IT) focuses on setting up and taking care of computer solutions and helping users in companies. It solves everyday problems by creating hardware and software solutions for networks, security, and websites, and managing technology over time. IT cares more about the computer equipment itself than the information it carries.  
• Data Science is a mix of different fields. It uses knowledge about a specific area, computer science, and math tools to find useful information and insights from all kinds of data. It involves "digging" through huge, complicated sets of data, often called "Big Data," and needs strong skills in math, analysis, and predicting things.  

This shows that Computer Science is the main science behind all computing. It provides the core ideas—the basic rules, algorithms, and how computers think—that the bigger "computing" world is built upon. Because of this strong base, people who study Computer Science can often easily learn new technologies and ideas. They understand the main rules instead of just knowing how to use specific tools.  

The field of Computer Science is very wide, with many special areas. Theoretical Computer Science is a main part, looking at abstract algorithms, computer problems, and the basic ideas behind how computers work. This includes:  

• Automata Theory: Studying simple machines and what problems they can solve.  
• Computational Complexity Theory: Sorting computer problems by how hard they are to solve.  
• Information Theory: Figuring out how to measure information to find limits on how data can be handled.  
• Formal Methods: Using math to carefully describe and check if software and hardware systems work correctly.  
• Algorithms and Data Structures: These are key to theoretical computer science. Algorithms are the step-by-step ways data is processed and problems are solved, and data structures are smart ways to organize data. Examples include ways to sort lists (like QuickSort) or find things (like Binary Search), and ways to store data like Trees or Graphs.  

Besides these basic ideas, Computer Science has many practical specializations, which you can see in college courses. These include:

• Artificial Intelligence (AI): Making computers solve problems and predict things using natural language (like talking) and machine learning (where computers learn from data).  
• Computer-Human Interface (CHI): Looking at how people use computers on different devices.  
• Game Design: Using AI and machine learning to help players in games.  
• Networks: Dealing with how wired and wireless computer networks are built, managed, and kept safe.  
• Computer Graphics: Focusing on making and showing 2D and 3D pictures.  
• Information Security: Managing all parts of a company's safety.  
• Programming Languages: Understanding different computer languages and when to use them.  
• Systems: Making hardware, software, and services work their best.  

Even though it's foundational, the Theory area also goes into advanced math ideas used in computer science, like making secret codes (cryptography) and solving problems with many computers working together. This long and growing list of special areas, including fast-growing fields like AI and Data Science, shows that Computer Science is always changing. It keeps growing because new computer problems come up, technology gets better, and different fields work together. This constant change means people in this field always need to learn new things, do research, and adapt, making it an exciting and important area to study.  

The table below gives a quick look at important areas within Computer Science, showing how wide the field is, from its basic ideas to its practical uses.

Area	What It Is	Key Skills/Focus	Relevant Snippets
Theoretical Computer Science	Explores basic ideas about how computers work, including how hard problems are to solve, and ways to organize data.	Logic, math proofs, counting, graph theory, probability, algorithms, data structures, math theories, predicting, probability.
Artificial Intelligence (AI)	Making computers able to solve problems, predict things, or do complex tasks using natural language and machine learning.	Math and analysis, algorithms, predicting.
Data Science	"Digging" through large sets of data to find useful information, especially complicated or messy data (Big Data).	Math and analysis, attention to detail, predicting.
Software Engineering	Designing, building, and testing big, complicated, and important software programs; focuses on rules for using programs.	Coding, scripting, communication, teamwork, fixing problems, testing, security, making things work for many users.
Networks	How companies use wired and wireless networks to share information; managing how much data flows, traffic, who can access, and safety.	Finding and fixing network problems, designing network setups.
Computer Graphics	Deals with 2D and 3D pictures in software; making realistic images and showing them well.	Attention to visual and artistic details, teamwork, creativity.
Information Security	Manages all parts of a company's safety (software, networks, storage, devices); understanding weak spots and rules.	Communication, managing threats, following security rules.
Programming Languages	Understanding how different computer languages (like JavaScript, Python) are different and when to use them.	Coding and scripting in many languages, teamwork.
Computer-Human Interface (CHI)	Focuses on how people use computers (websites, phones, VR); making good interfaces that are easy to use.	Communication, people skills, attention to visual detail, understanding how users behave.
Game Design	AI and machine learning in how players move forward in games; teamwork between designers and programmers for a good game.	Attention to visual detail, teamwork, coding, scripting.
Systems	Makes hardware, software, and services work their best; dealing with speed, safety, and how productive they are.	Finding and fixing hardware/software problems, updating systems, designing system setups.