Computer science is a field of study that deals with the design, development and application of computers. It focuses on the theory behind such machines as well as the science and engineering of computer hardware and software.
You can study many different aspects of computer science, including artificial intelligence, networks, data science and quantum computing. These are just a few of the branches of computer science you might explore throughout your study.
Computer science is not a single field of study; instead it covers a wide range of topics and approaches to computing science. Some areas of computer science are concerned with the theory behind computation, including semantics, computability and complexity theory; other fields are more concerned with practical issues such as software engineering, human-computer interaction, computer graphics, artificial intelligence and machine learning; still others focus on the technical aspects of implementing computations.
The academic curricula for most computer scientists are generally broad and include two or more programming languages (often Java/C++/Python). Computer scientists also use tools from other disciplines such as abstract algebra or topology to solve problems they encounter while working on specific applications.
So what are the example of computer science branches?
Artificial Intelligence & Machine Learning
Artificial intelligence (AI) is the field of study dedicated to creating machines capable of performing tasks normally requiring human intelligence. AI researchers seek to develop machines that can learn from experience, develop new knowledge and solve complex problems. The goal is for these machines to exhibit behaviors characteristic of human intelligence, such as learning, reasoning and problem solving.
AI has been around for decades; however, recent advances in computing power have made it possible for scientists to build more sophisticated systems capable of performing complicated tasks like recognizing faces or playing chess against human opponents at a professional level.
Machine Learning (ML) is a subset of AI that focuses on creating machines that are able to use algorithms and programming to ‘think’ like the human mind.
The study of networks focuses on the analysis, design and implementation of networks that link computers or devices together such as the internet or 5G. Computer scientists study how to develop these links using different connections, like light signals or radio waves. They also work to develop protocols that establish limitations and protections for these networks.
Networks are everywhere, from your local network at home or work to the biggest online network in the world, the Internet. Computer scientists study all kinds of networks, large and small, and they have many different ways of looking at them. They can analyze their structure to determine how they are connected and what they can do with each other; they can look at how packets travel through a network so they can make sure that data gets where it needs to go; they can design algorithms that route traffic efficiently; or they can create policies to protect users' privacy.
A computer scientist who studies networks is called an "network engineer." Network engineers might work in telecommunications companies designing wireless communication systems or in software companies developing applications for mobile platforms such as Android or iOS (Apple).
Data Science is a field of computer science, statistics and mathematics concerned with the development and application of data analysis methods. The term "data science" has been in use since at least 1954, when Frederick E. Webster referred to it as a "new academic field," in a research paper titled "Data Science: From Information to Knowledge."
In Data Science the term “Big data” is used to refer to a large set of data that are collected from a specific source. Data scientists perform data mining to identify patterns and extract data in order to perform data analysis.
Today, data scientists are commonly associated with the volume of data they handle and their ability to quickly process that data. Many people believe that the skills required for this job are similar to those required for other fields like statistics or business analytics. But data science is different from traditional fields because it requires strong programming skills, sophisticated software engineering skills, as well as knowledge of statistics and Machine Learning (ML).
The demand for qualified Data Scientists is huge, with job postings over 3000 posts % in 2022 according to LinkedIn.com.
Quantum computing is an area of study focused on the development of computer-based technologies at the Quantum (atomic and subatomic) Level by applying the Principles of Quantum Theory. By harnessing the laws of quantum mechanics, quantum computing is able to solve problems that are too complex for classical computers.
Quantum computers are different from traditional computers in that they are made up of qubits (quantum bits). A qubit can be in multiple states simultaneously, in contrast to classical bits which can only be either 0 or 1. This allows quantum computers to perform parallel computations at once, unlike a traditional computer which cannot do this until it has been programmed for each step separately. For example, a quantum computer could calculate all possible moves in a game of chess at once, then choose the best move based on probabilities calculated by examining each choice's potential outcome.
In terms of raw processing power, a quantum computer would be millions or even billions of times faster than today's supercomputers.
In theory, quantum computers could solve some problems that are impossible or impractical to solve with conventional computers today.
Software engineering is a study of engineering to the design, development and maintenance of software. Software engineers develop and build computer systems software and applications software. A software engineer works on one or more products from conception to production release. The work of a software engineer may be technical or managerial, and may involve the use of tools, including computer-aided software engineering (CASE) tools.
Software engineering can be thought of as a sub-discipline within computer science that involves application of advanced mathematical, scientific and economic principles to the development of information technology (IT). It requires an understanding of core areas in computer science such as data structures, algorithms, programming languages and software architecture, but also overlaps heavily with fields such as electrical engineering and computer hardware design.
These are only a few branches of Computer Science, there are a lot more to explore out there. So, want to start your computer science journey with us? We are specialized in coding, so send your children to Telebort class now!
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