What Is Computer Science? An Introduction to a Limitless IndustryWhat Is Computer Science? An Introduction to a Limitless IndustryWhat Is Computer Science? An Introduction to a Limitless Industry

Table of Contents

Behind every computer, tablet, and smartphone screen, at the heart of every digital device, and deep inside every piece of software is the work of generations of computer scientists. These professionals are responsible for inventing the technologies that shape our future.

The U.S. Bureau of Labor Statistics (BLS) forecasts that jobs for computer and information research scientists will increase by 16% between 2018 and 2028, which is much faster than the average growth forecast for all occupations.

Despite this, many people are unsure about what computer science is. This guide describes the training and experience required to become a computer scientist and the computer science skills that are in greatest demand. It also explores how computer science compares to computer engineering and information technology, and the many different career options available to computer scientists.

What Is Computer Science?

The birth of computer science dates back hundreds of years to the invention of the binary number system by Gottfried Leibniz in 1703, as the Visual Capitalist explains. The 0s and 1s that make up the binary system are the foundation of all modern hardware and software.

These are some of the technological seeds of today’s digital revolution:

  • The precursors to computer punch cards were the automatic fabric looms from the early 19th century that used wooden blocks with holes punched in them to specify the fabric’s weave pattern.
  • The first computer algorithm, which makes software possible, was created by the English mathematician Ada Lovelace in 1842; Lovelace is considered the first computer programmer.
  • The first “modern” computer was devised and built by Alan Turing during World War II; it was used to break the Enigma encryption used by the Germans to protect their messages.

Computer Science Definition

An offshoot of engineering science, computer science is the study of subjects related to the technology and principles of computers, including:

  • Algorithms
  • Data structures
  • Computer and network architecture
  • Data modeling
  • Information processing
  • Artificial intelligence

Computer scientists apply technology to solve problems. They create programs that power systems and applications. Computer scientist Amy J. Ko offers a human-focused definition of computer science as it relates to public education — the academic study of the human and technical aspects of many computer-related topics. Those topics include:

  • Computer use
  • Computational thinking
  • Programs and programming
  • Software design and engineering
  • Hardware design and construction
  • Information collection, processing, and storage
  • Computers and society

What Is Code in Computer Science?

The binary number system forms the basis for code in computer science. Computer code serves as the foundation of all computer systems, from the most sophisticated supercomputers to the simplest single-purpose applications.

Exactly what is code in computer science? Code is text written to the specifications of a programming language such as C, Java, or Python. Code is also used in HTML and other markup languages and in SQL and other database languages. The two types of code are source code and object code, as TechTarget explains:

  • Source code is made up of statements written in a specific programming language.
  • Object code is source code after it has been processed by a compiler to make it ready to run on the target computer.

The Five Generations of Programming Languages

Towards Data Science estimates that there are more than 600 programming languages in use, although only a few dozen of the languages could be considered mainstream. The most popular of these are high-level languages used to create systems and applications, query databases, display a webpage, or model sophisticated data analyses.

First Generation: Machine Language

Machine language is the binary code in a sequence of 0s and 1s that computers understand without an intermediate translator. All other program code is reduced to machine code for processing by the computer’s many components.

Machine languages are specific to a particular type of processor chip such as those sold by Intel, NVidia, and ARM. It is considered a low-level language because programmers must specify every action the program takes rather than relying on the prefabricated libraries of routines available in high-level languages.

Second Generation: Assembly Language

Assembly languages replace 0s and 1s with operation codes and symbolic addresses; the operation codes resemble natural language in the form of mnemonics. This simplifies programming, but assembly language is considered a low-level programming language because programmers must know the details of the processor that will run the program.

Processing assembly language code requires a translator program called assembler to convert the code to machine language. The benefit of assembly language is the level of control it gives programmers over the way their programs operate. Assembly language programs run faster than programs created with high-level languages, and they conserve processing power and storage space.

Third Generation: High-Level Languages

The primary benefit of high-level languages such as C, C++, Java, and JavaScript is the ability of their programs to run on various types of computers with little or no modification. The code generated by high-level languages looks like natural language and mathematical formulas. This makes it easier to design, maintain, and update programs.

Most high-level languages are procedural languages that list all the steps required for the computer to complete the desired action. They are noted for combining more instructions in less code and for allowing programmers to spend less time coding because programs require fewer overall instructions than with low-level languages.

Fourth Generation: Database Languages

These are sometimes referred to as very high-level languages because programmers have to specify only what they want the computer to do, not how the computer will do it. Fourth-generation languages such as the Structured Query Language (SQL) are application-specific: They are designed to run within a certain application domain and possess knowledge of that domain.

Key characteristics of fourth-generation languages include:

  • They make it fast and simple to develop programs.
  • They retrieve information from computers quickly with little or no programming required.
  • They are easy to learn and allow people without extensive programming knowledge to use applications.
  • They generate code with few errors that is easy to maintain and update.

Fifth Generation: Neural Networks

The latest generation of programming languages is used primarily for artificial intelligence, expert systems, neural networks, and other advanced systems. They replace code in the form of text and formulas with visual and graphical development environments, as software vendor Monitis explains. The source code these languages generate is typically converted to a third- or fourth-generation language before it is run.

One of the goals of fifth-generation languages is to create programs by dragging and dropping components in an object-oriented programming setting. This makes powerful program development tools available to people who have little or no programming experience. However, the systems that power fifth-generation languages are complex and resource-intensive.

Back To Top

Careers in Computer Science

The growing demand for professionals pursuing careers in computer science is driven by businesses’ increasing need for experts in data collection and analytics, as the BLS explains. A constant stream of innovative algorithms, hardware and software designs, and other information technologies drive company growth and enhance profitability in nearly all industries.

These are among the top computer science careers in software, hardware, management, and research.

Software-Focused Careers

Most of what computer science is revolves around programming and software design. Software is made up of algorithms that instruct the computer to perform specific actions. These algorithms grow increasingly complex and difficult to work with. By simplifying algorithms, computer scientists improve the efficiency of computer systems for machine learning, cloud computing, and other applications.

Software Developer

  • Software developers determine the features and functions that software users require.
  • They design, test, deploy, maintain, and upgrade application and systems software.
  • Developers explain to programmers what code will be required by an application via models, flowcharts, and other diagrams.
  • They document all aspects of the development and deployment process.

The BLS estimates that the number of software developer jobs will increase by 21% between 2018 and 2028, much faster than the average growth forecast for all occupations. Within this job category are specific roles such as full-stack developer, user interface designer, software tester, and software engineer. Application software developers earned a median annual salary of $103,620, as of May 2018, and systems software developers’ median annual salary was $110,000, according to BLS figures. Salary figures vary based on experience, education level, location, and industry.

Web Developer

  • Web developers are responsible for all technical aspects of a website’s structure and operation, including its performance and content.
  • They discuss with clients and managers the components and operations the site will require.
  • Web developers use HTML, XML, and other programming languages to design, test, deploy, and update the site’s features.
  • Developers work with other designers to create the site’s graphics and other visual and information design elements.
  • They are also responsible for monitoring the site’s performance and traffic.

The BLS forecasts that demand for web developers will grow by 13% between 2018 and 2028. This is much faster than the average growth projected for all occupations. The median annual salary for web developers as of May 2019 was $73,760.

Database Administrator

  • Database administrators ensure that business decision-makers have ready access to up-to-date and complete information.
  • They work with users to identify their data needs.
  • Database administrators design, test, and implement databases, and ensure that they operate accurately and efficiently.
  • They are responsible for securing, backing up, and restoring data resources to protect against loss.
  • Database administrators maintain and update database designs and access permissions.

The BLS projects that the number of jobs for database administrators will grow by 9% between 2018 and 2028, which is faster than the average growth projected for all occupations. Within this job category are titles such as database architect, data warehouse administrator, and database analyst. The agency reports that the median annual salary for database administrators as of May 2019 was $93,750.

Back To Top

Hardware-Focused Careers

Computer scientists are involved in all aspects of the creation, testing, implementation, and maintenance of hardware components, including processors, memory devices, network equipment, and complete computer systems.

Systems Analyst

  • Systems analysts consult with managers to determine the functionality they require in their computer systems.
  • They prepare cost-benefit analyses to ensure the organization has the infrastructure necessary to support its information technology (IT) systems.
  • They design, test, implement, maintain, and upgrade the systems.
  • They train end users in the system’s operation and write instruction manuals and other documentation.

Systems analyst jobs are forecast to increase by 9% between 2018 and 2028, faster than the average growth projected for all occupations, according to the BLS. The median annual salary for systems analysts as of May 2019 was $90,920.

Network Architect

  • Network architects design, test, and install various types of computer networks, including local area networks (LANs), wide area networks (WANs), and intranets.
  • They ensure the security of communication and computer networks.
  • They manage hardware and software upgrades to the networks, including network adapters, network drivers, and other support equipment.
  • They study new networking technologies that may improve the network’s performance and functionality.

The BLS estimates that jobs for network architects will increase by 5% between 2018 and 2028, which is the same as the average growth projected for all occupations. The median annual salary for network architects as of May 2019 was $112,690.

Cloud Computing Engineer

PayScale reports that the median annual salary for cloud solutions engineers was around $87,000 as of July 2020. TechRepublic notes that demand for cloud computing engineers is driven by companies’ migration to cloud services. Flexera’s “2020 State of the Cloud Report” states that organizations exceeded their public cloud budget by an average of 23% in 2019, a figure that they forecast will increase to 47% in 2020.

Management-Focused Careers

Many careers in computer science emphasize the management of technology over the design and use of hardware, software, and networking equipment. These are among the popular management-centered career options for computer scientists.

Business Analyst

  • Business analysts, also referred to as management analysts or management consultants, are charged with analyzing an organization’s information technology systems to identify ways to reduce costs, improve efficiency, and increase revenues.
  • Business analysts interview managers and employees, observe operations, and examine financial and other data.
  • They recommend new systems, procedures, and organizational changes via presentations and written reports.
  • They work with managers to oversee implementation of the changes.

Demand for management analysts is projected to increase by 14% between 2018 and 2028, according to the BLS, much faster than the average growth projected for all occupations. The median annual salary for management analysts as of May 2019 was $85,260.

Product Manager

  • Product managers are responsible for all aspects of a specific product’s development, manufacture, distribution, and marketing.
  • They lead diverse teams of workers and are often charged with training employees in the use of new technologies.
  • They manage the financial aspects of the product, including sales strategies, training materials, and production costs.
  • In addition to technical expertise, product managers must have leadership skills and organizational knowledge.

The median annual salary for product managers was approximately $84,000 as of July 2020, according to PayScale. Popular skills for product managers include product development, strategic planning, project management, and product marketing.

Engineering Manager

  • Engineering managers oversee the development and production of new products and designs, including the staff, training, and equipment required.
  • They work on budgeting for projects and programs, hire and supervise staff, and head research projects.
  • They are responsible for ensuring the technical accuracy of projects and programs and the effectiveness of production techniques.

The BLS projects that employment for architectural and engineering managers will increase by 3% between 2018 and 2028. The bureau reports that the median annual salary for architectural and engineering managers as of May 2019 was $144,830.

Information Security Analyst

  • Information security analysts devise and implement an organization’s strategy for protecting its hardware, software, data, and network resources.
  • They monitor all company networks and information systems to identify and defend against breach attempts and investigate the source of breaches that occur.
  • They perform penetration testing to ensure that all of the company’s digital assets are protected.
  • They research technologies and develop security standards and procedures.
  • They participate in training employees and managers in security best practices.

The number of jobs for information security analysts is expected to increase by 32% between 2018 and 2028, according to the BLS. This is much faster than the average growth projected for all occupations. As of May 2019, the median annual salary for information security analysts was $99,730.

Software Quality Assurance Manager

  • Software quality assurance managers, also called software quality assurance engineers, work in software development with a focus on ensuring that software works as designed.
  • They create test plans and test cases that confirm all functions, features, and components of application and system software are performing as expected.
  • They work with developers to identify and patch problems with software and ensure the functionality and uniform design of user interfaces.
  • They analyze and report on all aspects of a software system’s operation and communicate with development team members to promote the highest quality of software design.

PayScale reports that the most popular skills for software quality assurance engineers are test automation and planning, regression testing, and system testing. The site reports that the median annual salary of software quality assurance engineers was about $76,000 as of July 2020.

Research-Focused Careers

Innovation is central to all careers in computer science software, hardware, and management. However, innovation is essential to careers in computer science research. This field explores the foundations of computer technology, seeking insights to create new models and theories of computation and to solve complex computing problems.

Data Scientist

  • Data scientists are placed within the broader category of computer and information research scientists.
  • They work with other scientists and engineers to solve complex mathematical and computer problems.
  • Data scientists improve the software and hardware tools that programmers and engineers use to create software, systems, and networks.
  • They discover innovative ways to test new software.
  • They publish the results of research in software and information science, and present at conferences.

According to the BLS, the number of jobs for computer and information research scientists is projected to increase by 16% between 2018 and 2028. This field includes computer science professors and researchers. The median annual salary for computer and information research scientists as of May 2019 was $122,840.

Artificial Intelligence and Machine Learning Engineer

  • Artificial intelligence and machine learning engineers are computer and information researchers who focus on advanced programming, complex data sets, and algorithms used to train intelligent systems, as TechRepublic explains.
  • Machine learning software engineers devise new algorithms for innovative system designs.
  • Applied machine learning engineers create algorithms and libraries to train machine learning systems.
  • Core machine learning engineers develop and evaluate new data models for machine learning.

PayScale reports that the median annual salary for machine learning engineers was about $112,000 as of July 2020. Popular skills for the position are Python, deep learning, machine vision, and natural language processing.

Resources for Careers in Computer Science

Back To Top

Computer Science Topics

Technology changes so quickly that computer and information specialists must stay abreast of many different computer science topics. These are among the areas that receive the most attention from computer science professionals.

Machine Learning and Other Forms of Artificial Intelligence

Within the field of artificial intelligence (AI) are several specialties, including robotics, natural language processing, computer vision, and deep learning. Codebots describes six distinct areas of artificial intelligence:

  • Expert systems are made up of a knowledge base, an inference engine, and a user interface. The inference engine queries the knowledge base, applying if-then-else rules to find solutions to real-world problems.
  • Machine learning applies statistical techniques to improve the computer’s ability to execute a task based on what it knows. Deep learning is a subset of machine learning that can determine on its own when its learning algorithms are incorrect and apply corrections.
  • Natural language processing automates interactions between humans and computers by automatically understanding and generating human language. Chatbots and virtual assistants such as Amazon Alexa and Apple Siri are examples of natural language processing.
  • Computer vision applies AI techniques to allow computers to see the world as humans do by analyzing digital images and video in real time. Facial recognition systems rely on computer vision.
  • Automated speech recognition connects natural language processing with speech-to-text and text-to-speech systems.
  • Automated planning and scheduling, also called AI planning, studies strategies and the consequences of specific actions. This is the technology used in self-driving cars and autonomous robots.

Internet of Things

This far-ranging technology is finding uses in finance, manufacturing, health and fitness, nutrition, education, games, and other fields. The foundation of the internet of things (IoT) relies on intelligent devices in workplaces, homes, public spaces, and other environments. Network World cites a Gartner study that found there are 21 billion devices collecting data and performing other tasks, including smart speakers, watches, door locks, medical devices, and heating, ventilating, and air conditioning (HVAC) equipment.

The primary benefit of IoT to businesses is its ability to expand corporate networks and, thus, allow them to more easily reach customers and consumers. By bridging the digital and physical realms, IoT improves the accuracy of predictive models and allows more decisions to be made automatically, with no human intervention required. Questions of security and reliability, particularly in medical applications, have slowed adoption of IoT.

Cybersecurity

The more organizations rely on computer networks, the more important it becomes to secure the data that resides on those networks. Cybersecurity encompasses management of access controls and passwords, malware prevention, privacy protection, detection and prevention of data breaches, and mobile security.

Computer security firm Kaspersky Lab identifies five key trends in cybersecurity:

  • Ransomware attacks against banks will increase: There will be more attempts to take advantage of weaknesses in mobile banking systems and online payment processing services.
  • New digital currencies will be targeted: In 2018, bitcoin was a primary target of malware authors targeting financial institutions. Libra, ton, gram, and other new cryptocurrencies will likely face similar attacks.
  • Medical records are at increased risk: Digital criminals are trying to take advantage of the growing value of medical records and private information by attempting to breach healthcare networks.
  • Cloud networks become a bigger target: Many new threats to organizations’ cloud resources originate from inside the company as criminals bribe and blackmail employees.
  • Vulnerabilities will arise in 5G networks: Telecommunications carriers will be challenged to protect the privacy of customers using their new 5G cellular networks because of the data the systems collect about their private lives.

User Experience

Among the innovations in the way humans interact with computers are voice user interfaces, personal user interfaces, augmented reality, cross-platform app development, and material design. Adobe identifies five important trends in user interface design:

  • Inclusive design is becoming central to interface design principles rather than an aspect designers consider after the fact. More research and testing are being done that involves people who interact with computer technologies in different ways. Inclusive design also represents the social, political, and economic backgrounds of computer users.
  • Motion sense technology has the potential to transform the way people interact with products and services. Devices can sense when people are nearby and recognize and respond to specific gestures. However, developers face challenges in research, testing, and security.
  • Product ops is an extension of the DevOps (combining development and operations) principle in software development that mediates activities between sales, marketing, development, production, and other stakeholders regarding a specific product. The goal is to align product teams with users and the business’s overall strategies.
  • UX audits will be more common as user interfaces become the difference between successful products and failed ones. The goal of UX audits is to identify design flaws and usability problems in existing products and new ones.
  • Voice technology will continue to gain in popularity as people’s conversations with computers become more natural. Google and Amazon are leading the push to improve voice interfaces through their smart speaker products.

Computer Science Resources

  • Hour of Code Activities features one-hour programming tutorials suitable for all ages and available in more than 45 languages. Children’s coding activities are divided into four age groups, as well as all grades, beginner, and “comfortable.”
  • S. National Aeronautics and Space Administration’s STEM Engagement page provides a range of resources for students and educators, as well as an A-to-Z index of topics related to STEM education and a collection of computer science education resources.

Back To Top

Computer Science vs. Computer Engineering

When it comes to computer science vs. computer engineering careers, there is considerable overlap. Yet there are also clear distinctions between the two fields in terms of their focus, training, and responsibilities.

Software Focus vs. Hardware Focus

Computer science emphasizes innovations in algorithms and other software design. The goal is to solve complex problems in science, medicine, business, and other fields and industries. The algorithms are often applied to very large data sets to identify patterns in the data that indicate trends and provide other insights.

By contrast, computer engineers design, develop, and test circuit boards, memory and data storage devices, routers, and other computer and networking components. The profession is characterized by intensive testing of product designs to ensure they operate as intended. The BLS notes that many of the products that computer engineers work on are used in cars, home appliances, medical devices, and other internet-connected systems.

Computer Science Curriculum vs. Computer Engineering Curriculum

The software/hardware distinctions between the two fields carry over to a consideration of computer science vs. computer engineering curricula, as Field Engineer describes. Computer science students study innovative ways to create and apply algorithms to improve the performance of software, devise new capabilities, and troubleshoot problems. Computer science relies on programming languages such as Python, Java, C/C++, and HTML.

The curriculum for computer engineering more closely resembles that of electrical engineering. It emphasizes new approaches to hardware and software architectures via the application of modern physics. Computer engineers work in such fields as robotics, artificial intelligence, speech processing, and microprocessors.

Computer Science Careers vs. Computer Engineering Careers

The BLS reports on the largest employers of computer scientists:

  • Federal government (minus the Postal Service): 28%
  • Computer system design companies and related providers: 20%
  • Research and development entities in engineering, physical, and life sciences: 16%
  • Universities, colleges, and professional schools: 8%
  • Software publishers: 5%

A master’s degree in computer science or a related field is the minimum requirement for most computer science jobs, although jobs in the federal government may call for only a bachelor’s degree.

These are the largest employers of computer hardware engineers, according to the BLS:

  • Computer system design companies and related providers: 25%
  • Research and development entities in engineering, physical, and life sciences: 10%
  • Manufacturers of computer and computer peripheral equipment: 10%
  • Manufacturers of semiconductors and other electronic components: 9%
  • Federal government: 8%

Most computer hardware engineers have earned a bachelor’s degree in computer engineering, electrical engineering, or computer science. While their work is primarily hardware focused, they often need experience using programming languages because they frequently work on software.

Back To Top

Computer Science vs. Information Technology

When considering computer science vs. information technology, the distinctions primarily relate to the theoretical nature of the former field and the practical aspects of the latter.

Programming Focus vs. Systems-Management Focus

The software that computer scientists develop is intended for new computer architectures and technologies, such as neural networks and other forms of artificial intelligence. By contrast, information technology professionals are responsible for developing, implementing, and maintaining applications and system software for businesses, as Techopedia explains.

Computer scientists are perceived as engineers and scientists, and as such they typically have a more extensive educational background than IT managers. Conversely, IT professionals are considered technicians. For example, computer systems analysts are IT professionals who bring together the worlds of business and information technology, as the BLS explains.

Computer Science Curriculum vs. Information Technology Curriculum

As mentioned above, computer scientists generally have earned a master’s degree in computer science or a related field. For IT professionals, the most common degree is a bachelor’s in computer or information science. IT managers and analysts often take classes in business and management information systems to gain a better understanding of the needs of business managers.

Similarly, programming experience and other technical expertise is helpful for a career in information technology, but such skills are a prerequisite for jobs in computer science. However, in both fields professionals need to continue their education to stay abreast of technological innovations that affect their work.

Computer Science Careers vs. Information Technology Careers

As listed above, the largest employers of computer scientists are the federal government, computer systems design firms, scientific research and development companies, colleges and universities, and software publishers.

According to the BLS, these are the largest employers of computer systems analysts, the profession that most closely represents IT careers:

  • Computer systems design companies: 29%
  • Financial providers and insurance companies: 13%
  • Management service companies: 9%
  • Information service providers: 7%
  • Government agencies: 6%

The number of jobs for computer systems analysts is growing. The BLS notes that there were 633,900 computer systems analyst jobs in the U.S. in 2018, compared to only 31,700 jobs for computer and information research scientists in that year.

The Science That Drives the Modern Economy

Every industry, business, and field of endeavor has been affected — and often reinvented — by computer technology. This trend shows no signs of abating and in fact is likely to increase as organizations strive to capitalize on the latest technological innovations.

At the heart of those world-changing innovations is the work of computer scientists, whose contributions to artificial intelligence and other breakthroughs will reshape the world yet again. The future is waiting to be invented, and computer scientists are leading the charge.

Back To Top

Infographic Sources

Data USA, Computer Science

IoTDunia, “How Does IoT Work? Explanation of IoT Architecture & Layers”

Additional Sources

The Boston Globe, “Why Is Massachusetts’ Tech Sector So Lacking in Diversity? Take a Look Inside AP Computer Science Classes”

CIO, “10 Reasons to Ignore Computer Science Degrees”

Encyclopedia Britannica, Computer Science

Encyclopedia Britannica, Expert Systems

Entrepreneur, “10 User Experience Design Trends You Need to Know About in 2019”

GoodCore, “CS vs. IT — Which Is a Better Career Choice for 2020?”

Landofcode.com, “The Different Types of Languages”

MakeUseOf, “What Is Coding and How Does It Work?”

New Scientist, “What Is a Job in Computer Science?”

The New York Times, “The Hard Part of Computer Science? Getting into Class”

U.S. News & World Report, “What Can You Do with a Computer Science Degree?”

Zendesk, “Deep Learning vs. Machine Learning: A Simple Way to Understand the Difference”

Be Brave

Bring us your ambition and we’ll guide you along a personalized path to a quality education that’s designed to change your life.