Computer Science vs. Computer Engineering: You Can’t Have One Without the Other

A computer-focused degree can open a lot of doors: not only in the tech world but in healthcare, retail, entertainment, and other industries as well. The market for computer scientists is growing much more quickly than the aggregate job market; the same is true for jobs in cyber security, information systems management, and niche tech fields like machine learning and robotics. Computing jobs may no longer be the number one source of new wages in the US, but qualified computer experts remain in high demand. And, all those jobs in computer science and computer engineering are among the most lucrative out there.

Filling roles in technology jobs often means specializing in computer science or computer engineering. While there is some overlap between these disciplines, there are also ways in which they are very different.

The same is true for computer science and computer engineering degree programs—and the jobs they prepare you for. Computer science is a broad discipline that encompasses programming, architecture, and computing theory. In contrast, computer engineering focuses primarily on computer hardware and software systems, and how they align in form and function.

If you love computers, choosing between these two disciplines can be tough. The key to making the right choice is understanding the difference between them. In this article about computer science vs. computer engineering, we cover:

• What is computer science, and how does it differ from computer engineering?
• Is there any overlap between these disciplines?
• Do computer science and computer engineering degrees lead to the same careers?
• How do the skills associated with computer science and computer engineering differ?
• Do computer scientists or computer engineers earn more money?
• Is the job outlook better for computer scientists or computer engineers?
• How can you decide which career path is the right one for you?

What is computer science, and how does it differ from computer engineering?

The difference between computer science and computer engineering isn’t as simple as many think. The popular distinction—that computer science is software-focused and computer engineering is hardware-focused—is overly simplistic. After all, the design of computer systems hardware is part of computer science, and computer engineers write software. Let’s dig deeper.

Computer science (CS) focuses primarily on computational theory, information processes, and software design, with applications across a broad spectrum ranging from cyber security to robotics. There’s a lot of math and complex programming involved. It tends to segment into theoretical and practical silos: theoretical computer science is abstract and heavily rooted in mathematics and algorithms, while practical computer science deals with things like computer performance, network management, and security. Artificial intelligence might seem to fall on the theoretical end of the computer science spectrum, but it’s actually practical.

According to computer scientist and researcher Peter Denning, the fundamental question that drives computer science forward is, “What can be automated?” The fundamental question pushing innovation in computer engineering, on the other hand, might be, “What tech can we build for automation?” Like computer science, computer engineering is concerned with solving real-world problems, but it does so primarily with hardware rather than software. Computer engineering, or CE, is a hands-on, research-oriented field where computer science, electrical engineering, and physics come together. It is a broad discipline because even relatively simple computer components are now incredibly complex compared to those regarded as leading-edge just a few decades ago. Computer engineering does involve writing code, but when computer engineers code, it’s often because they’re building entire systems from the ground up.

Is there any overlap between these disciplines?

Computer science and computer engineering are distinct disciplines, but they’re inexorably linked—neither can exist without the other. Hardware and software are essential elements of all computer systems, from the phone in your pocket to the robotic arm that assembled your car’s chassis. Both fields focus on data, automation, and discovering computers’ capabilities. Computer scientists and computer engineers alike use computers to solve problems and power modern technology. Programming is part of both computer science and computer engineering. And both fields are concerned with optimizing human-computer interaction.

Professionally, computer scientists and computer engineers work on the same problems because both areas of expertise contribute to the design, manufacture, maintenance, and optimization of computer-driven technology. This may come as a surprise if you’re currently researching computer science degree programs or computer engineering degree programs. Different departments offer these disciplines at many colleges and universities, and students in each program don’t collaborate at all. However, according to the University of Houston, this is a quirk of history more than anything else. “The disciplines,” the school writes in its Computer Engineering FAQ, “are broad enough that you have to separate them somewhere.”

Do computer science and computer engineering degrees lead to the same careers?

Sometimes, degree programs for computer science majors and computer engineering majors at both the bachelor’s degree and master’s degree level overlap. Still, the focus of these degrees tends to be quite different.

Core courses in computer science master’s degree programs focus on topics like:

Advanced Algorithms
This coursework will cover classic and modern algorithmic ideas, focusing on how to design algorithms and measure their efficiency. It delves into advanced topics like graph algorithms, dynamic programming, greedy algorithms, and approximation algorithms. Students will learn about the theoretical underpinnings of algorithms, their complexity, and practical applications in solving complex computational problems.

Advanced Mathematics
Topics in this course will cover formal logic notation, integer congruences, discrete probability, asymptotic notation, and growth functions. It will also explore advanced topics such as combinatorics, graph theory, and number theory, which are foundational in computer science for understanding algorithms and data structures.

Advanced Programming
This class should introduce tools and techniques for professional software construction, scripting languages, and web programming. It goes beyond basic programming to cover advanced topics like multithreading, network programming, and database connectivity. Students will also learn about best practices in coding and software maintenance.

Advanced Software Development
This course will expand on component model frameworks, code inspection, stress testing, and unit and integration testing. It will also explore software architecture, design patterns, and advanced aspects of software engineering processes, including agile methodologies and DevOps practices.

Computational Problem-Solving
The emphasis here will be on cooperative and collaborative work in creative problem solving in computer program development. The course will cover algorithmic thinking, computational modeling, and the development of software solutions to complex problems, encouraging teamwork and innovative thinking.

Data Security and Cybersecurity
Classes will focus on definitions of ethics and privacy, legislation and legal implications, network design, penetration and vulnerability testing, and risk mitigation strategies. This includes learning about encryption, cybersecurity frameworks, incident response, and the latest trends in cyber threats and defenses.

Data Structures
Coursework here will outline data types and structures including trees, sets, arrays, stacks, linked lists, and graphs with techniques for processing and storing. It will also cover advanced data structures like hash tables, heaps, and balanced trees, and their applications in various computer science domains.

Human-Computer Interaction
Topics in this class may include exploring speech and vision in computer interaction, natural user interface, intuitive media authoring, language learning, and the design behind HCI interfacing. The course focuses on designing user-centered interfaces and understanding the interaction between humans and computers.

Information Science
This class will study the principles of information problem solving, human-computer interfaces, digital information representation, and searching and organization of information on the web. It includes topics like information retrieval, digital libraries, and data mining, emphasizing the role of information in human-computer interaction.

Network Architecture
This course will look at the foundations of the internet – protocols, security, performance evaluation, and algorithms for routing and congestion control. It covers network design and architecture, including the study of LANs, WANs, and network protocols, as well as emerging trends in network technologies.

Operating System Design
Topics in this class will include memory management, interrupt handling, process synchronization, interprocess communication, virtual memory, and file systems. It provides an in-depth understanding of how operating systems function, manage resources, and provide services to application software.

Software Theory
Coursework will cover software design principles, families and hierarchies, pattern-oriented design, modeling, and analysis. The course focuses on theoretical aspects of software development, including formal methods for software specification, verification, and quality assurance.

User Interface Design
This class will focus on both the theory and practice of interface design, including interaction styles, dialogue design, software infrastructure, and human factors. It teaches principles of designing effective and user-friendly interfaces, with a focus on usability, accessibility, and aesthetic aspects of design.

Computer engineering focuses more on hardware. Students in CE programs take core classes in:

Artificial Intelligence
Topics here will include learning, automated reasoning, natural language processing, knowledge representation, game playing, and computer vision. The course will delve deeper into AI methodologies like machine learning algorithms, deep learning, and neural networks. It will also explore the application of AI in various fields, such as autonomous systems, AI in healthcare, and intelligent agents.

Computer Architecture
This coursework will focus on data representation, specialized processors, performance evaluation, and memory hierarchies. It will also include advanced topics like parallel architectures, instruction set architectures, pipeline processing, and the role of caches in modern computing systems.

Digital Design
This classwork will include number representations, logic minimization, arithmetic circuits, and asynchronous circuits with coding, troubleshooting, testing, and documentation of design. Additional topics might cover VHDL or Verilog for FPGA design, system-on-chip (SoC) design, and the application of digital design principles in real-world scenarios.

Digital Signal Processing
Material here will cover the memory architecture, data compression technology, and the digital signal processing algorithms used to measure, compress, and filter analog signals. It will also explore Fourier transform, discrete-time systems, filtering techniques, and applications in areas like audio and image processing.

Electronic Circuit Design
This class will deal with engineering in frequency response, semiconductors, diodes, field effect transistors, operational amplifiers, and transformers. The course will also cover advanced topics like power amplifiers, oscillators, and mixed-signal circuits, combining theoretical knowledge with practical lab work.

Embedded Computer Systems
This work will focus on rapid prototyping and design methods, testing within an operating system, and network communication with mobile devices. It will also involve learning about microcontrollers, real-time operating systems, and interfacing with peripherals and sensors.

Essential Software Engineering
Material will include software configuration management, object-oriented programming, project organization, and prototyping. The course will further explore software development methodologies, testing strategies, and the management of software projects.

Microprocessor Design and Interfacing
This work will focus on the design of digital logic circuits like combinational and sequential circuits, and how to combine them to create, implement, and interface microprocessors. It will also cover microprocessor architecture, assembly language programming, and interfacing techniques.

Principles of Physics
Study here will include electricity, light and magnetism, and their application in electrical circuits. The course will provide a foundational understanding of the physical principles underlying electronic systems and their practical applications.

Robotics
Studies will include path planning, human and machine interface, kinematics, sensors, and control of manipulator and mobile robots. The course will also focus on robot design, actuation, sensory feedback, and algorithms for robot motion and intelligence.

VLSI Principles
This class will cover theoretical analysis techniques and standard modern circuit design, advanced logic synthesis, datapath, and arithmetic circuits and memory design. It includes understanding the design of very-large-scale integration (VLSI) systems, chip layout, and fabrication processes.

Wireless Communication Technology
Material will cover both current and future wireless technology with the study of path loss, inter-symbol interference, spread spectrum, and adaptive modulation. The course will also delve into the principles of mobile communications, network architecture, and emerging technologies in wireless communication.

Given the pronounced differences in the nature of the coursework in these programs, you’ve probably guessed that Master of Science in Computer Science graduates and Master of Science in Computer Engineering graduates usually go on to work in very different tech areas. Tufts University, which has highly-rated on-campus and online computer science master’s degree programs, has a list of possible computer science jobs on the program website that includes roles like:

Information security manager

Analysts and managers at this level design and install software to protect data, monitor an organization’s networks for breaches, research trends. and recommend enhancements. Median wage: $152,480 .

Principal software engineer

These positions manage software developers and testers and take a broad approach to a company’s software needs. Median wage: $127,880.

Senior hardware design engineer

This job sees to the design, development, testing and application of hardware, and how it works with existing software. Median wage: $132,360.

Senior product manager

This position manages the software planning needs for organizations including security, technology upgrades, and the direction of other IT professionals. Median wage: $164,070.

Senior software engineer

This position broadly manages a system’s current and future software needs, and may oversee other designers and analysts. Median wage: $127,260.

Senior systems engineer

This position manages software development and implementation within the company network. Median wage: $124,200.

Software architect

Job positions like this oversee the design and connectivity between systems within the company network. Median wage: $126,900.

Software development manager

This position oversees the complexities of company software, and the teams of IT professionals who design and develop it. Median wage: $127,260.

Solutions architect

This job deals with testing and solving software problems and solutions and how to integrate current and future technologies. Median wage: $124,200.

Vice president of information technology

This executive level seat oversees all other positions in the department, managing both technology and personnel in planning, design, testing, and implementation. Median wage: $211,600.

Computer engineering program graduates, on the other hand, might work in roles like:

Computer engineer

This position oversees the design, testing, and development of computer hardware components and systems. Median wage: $143,640.

Computer systems analyst

This job functions as the liaison between business and information technology, building computer systems that meet the needs of both. Median wage: $102,240.

Electrical design engineer

An electrical design engineer oversees the manufacturing, as well as the design and testing of computer hardware. Median wage: $103,320.

Embedded software engineer

This position oversees the relationship between the code writing for software, and the hardware schematics that software runs on. Median wage: $124,200.

Firmware engineer

Similar to an embedded software engineer, this position creates the device-control software like microcontrollers and processors. Median wage: $124,200.

Hardware engineer

Hardware engineers ensure that hardware and software work together, creating schematics for new equipment and overseeing production. Median wage: $132,360.

Network architect

Computer network architects design and build large and small data communication networks to work within and between businesses. Median wage: $126,900.

Network engineer

This position is similar to network architect, and focuses on the design, building, manufacturing, and troubleshooting of communication networks. Median wage: $132,360.

System validation engineer

This position oversees the development of protocols and test scripts, identifying the gaps and planning for corrections and upgrades. Median wage: $124,200.

It might look at first glance like there’s no overlap between job opportunities for computer science students and computer engineering students. That’s often true when it comes to titles, but not when it comes to where professionals work. Remember, you can’t have hardware without software, and vice versa. According to the US Bureau of Labor Statistics (BLS), most computer engineers work in computer systems design or in the sciences, while most computer scientists work for the federal government or in computer systems design.

How do the skills associated with computer science and computer engineering differ?

The simple answer is that computer scientists are good at abstract thinking, while computer engineers tend to be better at analyzing what’s in front of them. The reality is, of course, much more complicated than that. To succeed in computer science, you’ll need skills related to:

Algorithm Development
Use logic and reasoning to create and fix code. This skill involves designing step-by-step computational procedures to solve problems or perform tasks. It requires an understanding of various algorithmic concepts, efficiency, and optimization techniques. In computer science, developing efficient algorithms is key to ensuring that programs and systems run quickly and effectively.

Data Structures
Organize, store, and manage databases, allowing for efficient indexing and modification. Data structures are essential for organizing and managing large amounts of data efficiently. This includes understanding different types of data structures like arrays, linked lists, trees, and graphs, and knowing when and how to use them to optimize data retrieval and manipulation.

Programming Languages and Their Applications
Understand the strengths and applications of top computer programming languages. This involves learning languages like Python, Java, C++, and others, and understanding their syntax, semantics, and best-use scenarios. Different programming languages are suited to different tasks, and proficiency in them is crucial for a wide range of computer science applications.

Computational Theory
Be familiar with the capabilities of computers and what problems can be solved through algorithms. This field deals with the fundamental capabilities and limitations of computers, exploring concepts like automata theory, computability, and complexity theory. It forms the theoretical foundation of computer science.

Computer Network Management
Use software and hardware to analyze data and search for ways to improve performance. This skill involves the design, implementation, and management of computer networks. It requires knowledge of network protocols, topologies, hardware devices, and software tools used in network configuration and troubleshooting.

Cybersecurity and Cryptography
Understand encryption and decryption of coded language, and its impact on securing data. Cybersecurity is about protecting systems and networks from digital attacks, while cryptography focuses on secure communication techniques. This includes understanding encryption algorithms, digital signatures, and security protocols.

Information Management
Acquire, organize, dispose, and/or distribute information to and from multiple sources. This skill involves the effective management of information, ensuring it is accessible and usable. It includes data governance, data lifecycle management, and knowledge of various information storage and retrieval systems.

Operating System Design and Maintenance
Keep computer systems running efficiently through comprehensive design and modification. This includes understanding the architecture of operating systems, their functionalities, and how they manage hardware and software resources. It also involves troubleshooting, updating, and optimizing these systems for better performance.

Software Design and Testing
Apply code to develop software, and test applications rigorously. This skill covers the entire software development lifecycle, from conceptualizing and designing software to coding and testing it. Testing is a crucial part, involving various methods to ensure software functionality, reliability, and efficiency.

Software Production
Design and manufacture software for real-world use. This involves not just the creation of software but also understanding the market and user needs, maintaining software post-release, and managing the overall software production process.

Communications Technology
Use technology to transfer information between computer systems. This skill involves understanding and implementing technologies for data transmission, including protocols, media, and devices used in network communication.

Computer Architecture
Use the structure of rules and methods to design data flow within computer systems. This includes knowledge of how different parts of a computer and its peripherals are organized and interconnected, and how they process data.

Device Drivers
Apply specific driver programs to operate devices attached to a specific automation. This involves writing and maintaining low-level software that controls and allows communication between the operating system and hardware devices.

Electrical Engineering
Oversee the design, development, and manufacturing of communications systems. This requires an understanding of electronic circuits, signal processing, and electromagnetics, crucial for the development of computer hardware and communication systems.

Hardware Design
Outline and document circuits and modules in the schematics of computer hardware systems. This skill involves designing and testing various hardware components and ensuring their compatibility and efficiency.

Integrated Circuits
Use transistors, condensers, and resistors to store and create amplification for circuitry. This involves designing and developing microchips used in a wide range of electronic devices, from computers to smartphones.

Microprocessor Design
Aid in the efficiency and reduction of steps and cycles to execute tasks. This skill involves the design and development of microprocessors, focusing on optimizing their performance and efficiency.

Network and System Security
Protect network data integrity and usability with both hardware and software solutions. This includes implementing security measures to safeguard information and systems from unauthorized access, cyber-attacks, and other vulnerabilities.

Physics in Electronics
Use physics to study the connections and transistors within circuits. This involves applying principles of physics to understand and design electronic circuits and components.

Programming Languages
Understand the languages behind machine code output and the differences between them. This skill involves not just coding, but also understanding the theoretical aspects of how programming languages are constructed and how they operate.

Wireless Technology
Apply the technology of radio frequency and infrared waves to transfer information without physical restriction. This includes knowledge of wireless protocols, network topologies, and the design and implementation of wireless networks.

Do computer scientists or computer engineers earn more money?

The average computer scientist’s salary is higher than the average computer engineer salary, though it depends on where you source your information. According to Indeed, computer engineers earn about $107,543, while computer scientists earn about $109,591. The BLS, on the other hand, reports that computer engineers earn about $132,360, while computer scientists earn closer to $136,620. These figures suggest you can earn good money in either discipline, so it makes more sense to make career decisions based on your interests, talents, and passions if you’re trying to choose between them.

Is the job outlook better for computer scientists or computer engineers?

Right now, software is a much bigger business than hardware—computer science jobs are being created at a much faster rate than computer engineering jobs—but as robots and autonomous systems evolve and their use becomes more widespread, hardware may become king and the ratio may flip-flop. Until then, there are probably more ways to advance in computer science than in computer engineering, whether your interests lie in information management, cryptocurrency, or AI.

Keep in mind that plenty of employers treat CS and CE degrees as interchangeable, so your specialty area may not have as much of an impact on your earning potential as you might imagine. There are plenty of hiring managers out there who will only pay attention to the ‘computer’ element of computer science and computer engineering. You may be able to slip into a computer science job with an engineering degree or a computer engineering job with a comp sci degree.

How can you decide which career path is the right one for you?

If you’re passionate about computers, chances are you’ll do well no matter which path you choose. Computer science and computer engineering are both fascinating, well-paying fields that will likely keep growing as technology evolves, and your prospects will be similar in each. Choosing between these related disciplines can be especially tough when you’re looking at university programs. It might be helpful to think about whether you’re more excited by mathematics, puzzles, and abstract problem-solving or by tangible computational challenges and hands-on work. If you’re a conceptual thinker, you may derive more satisfaction from a computer science program. If you love building gadgets and playing with circuitry, a computer engineering program might be the better fit.

Of course, there’s a third option to consider. Many computer engineering majors make time to earn computer science minors, so they acquire the kinds of programming skills that will qualify them for jobs in both fields. You also can choose a double major that encompasses both CS and CE if you’re as passionate about hardware as you are about software. After all, these disciplines can’t exist alone. As one Quora commenter put it in a thread about choosing between computer science and computer engineering, “Computer engineering without computer science turns our machines into primitive tools. One could argue they are junk without it. Computer science without computer engineering is gibberish because the one thing that can compile and execute it wouldn’t exist… neither can advance without the other.” You may discover that’s true not just in theory, but also in your career.

(Updated on January 4, 2024)

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