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A degree in computer science ensures you have the necessary skills to stay current and remain a marketable employee in the US’s second fastest growing industry. Choose a degree level to learn how you can become a graduate.
As the world becomes more interconnected through the internet, businesses and organizations experience a growing need for qualified computer science professionals. Those planning to work in the booming computer science field can choose between associate, bachelor’s, master’s, and doctoral degrees. Each degree can lead to lucrative career options, but continuing education and advanced credentials increase graduates’ chances of earning high-paying positions.
Computer science professionals enjoy steady job growth. According to the U.S. Bureau of Labor Statistics (BLS), computer and information technology professionals can expect a 12% job growth rate from 2018-2028 — much faster than the national average growth rate for all occupations.
This resource introduces the field of computer science and explores the various types of computer science degrees. It also covers different types of computer science careers; job outlooks for each career; and how to secure those positions through education, experience, licenses, and certifications.
What Is Computer Science?
Computer science covers all things computers, including computational systems, computer engineering, and data science. Many computer science professionals find careers programming new software, managing information technology (IT) systems, or assessing security for complex digital networks.
Career outcomes for computer science students depend on education, experience, and certification status. Students who complete associate degrees in computer science might pursue careers as web developers. According to the BLS, web developers earn a median annual salary of $73,760.
Students who complete master’s degrees in computer science can work as computer and information research scientists. According to the BLS, professionals in this career earn a median annual salary of $122,840.
Computer science graduates with all levels of education enter a rapidly growing field with strong salary potential.
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Types of Computer Science Degrees
Students can choose from associate, bachelor’s, master’s, and doctoral degrees in computer science. Lower levels of education take less time to complete and typically cost less than advanced degrees, but more advanced levels of education often lead to better-paying jobs with more responsibility. Prospective computer science students should consider their personal goals before enrolling in a program.
The following sections cover each of the four degree types, the benefits of completing each degree, and courses learners might take while pursuing their degree.
Associate Degree in Computer Science
Usually consisting of around 60 credits, an associate degree in computer science takes most students two years to complete. Community colleges and some four-year institutions offer these degrees.
Graduates with an associate degree can pursue entry-level positions in areas like computer programming, web development, and data science. They can also transfer to a computer science bachelor’s program. Typically, graduates with an associate degree can earn a bachelor’s degree in just two additional years of study. The following list outlines several common courses found in associate in computer science programs.
Principles of Computer Networks
Commonly offered as one of the first courses in an associate in computer science program, principles of computer networks introduces intranets and extranets and demonstrates how businesses implement intranets to process information quickly. This course also covers fiber optic technology, satellite networks, and unbounded transmission media.
Because many businesses use computer networks, some programs target this course toward current or future business professionals. Students may need to complete principles of computer networks before moving on to more advanced topics.
Database Management Systems
Database management systems introduces the various types of database systems and teaches students to manage them. Topics covered in this course include data modeling, data manipulation, and data architecture.
Other subjects learners might explore include the development of new database environments, modern trends in data storage and warehousing, and various approaches to solving data-based problems. Students learn how databases develop and techniques for managing databases to achieve system goals.
Calculus courses cover the functions of variables, graphing of mathematical equations, and changes to algebraic equations due to additional factors. Topics include limits, the mean value theorem, and maximizing/minimizing functions. Computer science students use calculus equations in various programs.
Before enrolling in calculus, students must complete a college-level algebra course, though community colleges allow some recent high school graduates to bypass this prerequisite.
Cybersecurity fundamentals serves as an introductory course to advanced cybersecurity topics. It provides computer science learners with a foundation in computer network defense, analyzing various types of digital attacks and exploitations. After covering methods of protecting networks, students might learn to look for and exploit weaknesses in networks through ethical hacking.
Some programs focus on the applications of cybersecurity to business or government information. This course serves as a foundation for learners interested in cybersecurity bachelor’s or master’s degrees.
Learners earning associate degrees in computer science usually take software engineering toward the end of their program. This course builds off of foundational courses, like calculus, and introduces complex topics, like lifecycle models; the design and testing of programs; and techniques for creating programs, models, and software. Students also learn to analyze and maintain existing programs and software to improve performance.
When offered with a business focus, software engineering also emphasizes cost estimation. This course serves as a springboard to higher-level degrees and teaches critical skills for most computer science careers.
A bachelor’s in computer science requires 120-128 credits and takes four years to complete for full-time students. These programs explore advanced topics like engineering, complex mathematics, and niche computer science sectors.
Most bachelor’s in computer science graduates find entry-level positions in computer science, computer engineering, or software design. Potential job titles include database administrator, computer programmer, and software developer. The BLS reports that software developers earn a median salary of $105,590 and projects a 21% job growth rate from 2018-2028.
In this course, learners study the design, implementation, and analysis of algorithms and data structures. Learners use data structures to solve computer engineering problems through programming language.
Learners discover ways to use algorithms to influence and manipulate structures. They also use data structures to solve real-world computer science problems. Students should complete introductory IT courses before taking this course.
Comparative Programming Languages
An upper-division course taken after introductory programming classes, this course teaches students to analyze problems and situations to determine the best programming language to use. This course covers the benefits and shortfalls of each language and applies these traits to sample scenarios.
Another upper-division computer science course, this course examines the protocols, standards, and programming languages used to develop powerful web programming platforms. Students then learn to create content through various languages and interact with databases and XML documents.
Data Mining and Machine Learning
At the undergraduate level, data mining and machine learning introduces the core concepts behind big data, algorithms, and the creation of actionable insights from data. Learners examine concepts like k-means clustering and clustering algorithms.
Toward the end of the course, students use what they learned and apply the fundamental concepts to real-world examples using live algorithms to visualize data. Learners also use pseudocode to create their own programs. Data mining and machine learning courses provide an excellent foundation for students interested in master’s degrees.
Advanced Java Concepts
Taken after students complete an introductory Java concepts course, advanced Java concepts courses introduce topics like event handling, file input and output, and database connectivity. Students also learn about multi-threaded applications and programs, user events, and event handling.
While not always offered as an upper-division course, advanced Java concepts builds off previous associate degree concepts. Before enrolling in this course, students must understand the Windows operating system, graphical user interface design concepts, and Java programming fundamentals.
After completing a bachelor’s degree in computer science, learners can pursue a master’s or Ph.D. in computer science. Individuals may complete both options, but many programs recommend that applicants select one or the other. Both master’s and Ph.D. programs in computer science offer benefits.
A master’s in computer science requires roughly 45 credits to complete. Full-time students can often graduate in 1.5-2 years. The specific subject matter of a master’s in computer science depends on the specialization students choose. Most students complete master’s degrees in computer science to advance their current careers, so individuals should select specializations that best suit their career goals.
Analysis of Algorithms
Typically required as a foundational course and taken before specialization courses, analysis of algorithms introduces the design and analysis of algorithms. Students learn about various classical algorithms and their complexities.
Students learn how to use intellectual tools to design, implement, analyze, and evaluate their own algorithms. By the end of the course, learners can explain basic algorithmic design and analysis concepts and processes.
Computability and Formal Languages
As a prerequisite course for many master’s in data science programs, computability and formal languages takes place during an undergraduate degree or early on during a graduate degree. The course covers the theoretical side of computational models and analysis, teaching students to identify the benefits and limitations of various models.
Early on in the course, learners discover unsolvable problems in computational models, then apply theories to investigate the effectiveness of different models in these situations. Later, students examine more complex theories, including pushdown automata, finite automata, and Turing machines.
Offered as a required course for software specializations, compiler construction introduces the foundational techniques of compiling. Learners study topics like compiler construction tools, advanced theories, and the translation of programming languages into executables codes.
Toward the end of the course, students learn about more complex topics, including dynamic memory allocation, recurring, object orientation, and concurrency.
Artificial Intelligence Programming
Required in some intelligence specializations, artificial intelligence programming builds off of concepts covered in introductory machine learning courses. Students learn about knowledge-based interfaces and systems, particularly extensible systems and maintenance. Topics include frame, pattern matching, semantic networks, and deductive inference.
Most programs teach this course through hands-on projects, meaning students must complete several written programming assignments. By the end of the course, students can design and implement intelligent components for various industries through maintainable code.
Advanced Computer Game Design
Offered to students specializing in gaming, advanced computer game design teaches practices for programming computer games. This course usually focuses on 2D and 3D gaming creation, including the rendering of sprites and animations. Students also create artificial intelligence for computer games; program other gaming functions; and test, analyze, and adjust individual functions.
This course emphasizes individual gaming developments and requires hands-on learning. Some programs require students to work in groups to reflect real-world computer game design teams. Students must complete prerequisite data structures and machine learning courses before taking advanced computer game design.
The highest level of education available to computer science students, a Ph.D. in computer science builds off of introductory computer science concepts and focuses heavily on research. Students might prefer to complete a Ph.D. in computer science after earning their master’s, though some Ph.D. programs allow those with bachelor’s degrees in computer science to apply.
Course and credit requirements for a Ph.D. depend on the program and specialization, but most programs take 4-5 years to complete. Because a Ph.D. in computer science focuses on research and theory, most careers following doctoral programs consist of research, writing, and teaching.
Introduction to Computer Vision
Introduction to computer vision covers the fundamentals of camera imaging geometry, image formation, motion estimation, feature detection, and scene understanding. In this course, students learn to create applications that undertake various computer vision tasks.
Before taking this course, students should complete high-level mathematics courses, machine learning or artificial intelligence courses, and introductory courses to computer graphics or robotics. Skills learned in this course apply directly to applications and programs like facial recognition, fingerprint scanning, and item recognition in 3D spaces.
Usually taken in programming systems concentrations, security engineering covers the principles of cybersecurity systems engineering and design. The course begins with cybersecurity theories and the importance of effective, reliable security measures. Students then learn to analyze and assess the effectiveness of existing cybersecurity measures and conduct audits to improve processes.
The course later covers advanced topics, such as cybersecurity situational understanding and command. By the end of the course, students can analyze cybersecurity programs and methods, analyze potential risks based on current systems, and develop new security architectures to mitigate risks.
This course covers fundamental techniques for creating architectures used in high-performance processors. Learners examine topics including superscalar, multithreading, caches, virtual memory, pipelining, and out-of-order execution. More advanced topics include compilers, operating systems, and other issues affecting architecture.
Some Ph.D. programs emphasize hardware and software uses related to architecture. Upon completing the course, students can design and analyze various CPU performances. While some specializations require computer architecture, many programs offer this course for all Ph.D. students.
Also known as software systems engineering, software systems covers the basic principles of software engineering and approaches to developing software systems. Students learn about the alignment of software systems in relation to software design; software engineering constraints; and the analysis, design, testing, implementation, and maintenance of architecture. Some specialized courses might also emphasize network security and performance.
Learners explore modern trends in technology and how software engineering changes over time. Before taking software systems, learners should complete a management of systems or systems engineering introductory course.
An advanced course focused heavily on theory, computational geometry examines topics like nonlinear solvers, intersection problems, interval methods, and boundary element discretization methods for mechanics problems. This course also uses scientific visualization to create 3D models of various shapes.
Before enrolling in computational geometry, learners should complete data visualization and mathematics courses. Computational geometry also builds off of introductory topics in machine learning, randomizations in queries, and data structures.
Benefits of Earning a Computer Science Degree Online
In most cases, completing computer design degrees online leads to the same positive outcomes as on-campus degrees, but with the added flexibility of online learning. Thanks to the digital nature of computer science, some students prefer completing computer science degrees online. Specific benefits of earning online computer science degrees include:
Current computer science professionals must often complete additional education to move into roles with more responsibility. For example, professionals interested in leadership positions should earn master’s or Ph.D. degrees in computer science. Some professionals without backgrounds in computer science use degrees to learn new skills and find new career opportunities.
High Average Wages
Computer science professionals earn high wages across several industries. The BLS reports that software developers earn a median annual salary of $105,590, with the top 10% of earners making more than $161,290 annually. Other computer science professionals earn similar wages.
The BLS also projects strong job growth for many computer science positions. For example, the BLS projects jobs for software developers to grow 21% from 2018-2028. Other positions could see even faster growth rates — the BLS projects 26% job growth for software application developers in the same time frame.
New Skill Development
Current professionals might need new skills to secure specific positions. Completing an associate or bachelor’s degree in computer science teaches in-demand skills that can lead to niche positions. Other students learn skills for personal development or projects, such as developing websites or apps.
Computer science teaches many in-demand skills, and learners interested in the subject matter can benefit from studying topics they love. Anyone interested in computer science should research programs to find ones that fit their goals and needs.
Computer Science Licenses and Certifications
Offered by computer science organizations, professional certifications demonstrate an understanding of complex topics and industry skills. Computer science professionals can choose from dozens of professional certifications. Each helps with employment, but computer scientists particularly benefit from field-specific certifications. See below for some of the most popular certifications for computer science professionals.
Offered by CompTIA, an industry leader in training, continuing education, and certification, the Cloud+ certification demonstrates that professionals can maintain and optimize cloud infrastructure services. Best for professionals working in data centers, the Cloud+ certification covers skills and subject matter required of system administrators, focusing on vendor-neutral, cloud-based infrastructure services.
To earn this certification, CompTIA recommends that individuals possess 2-3 years of system administration experience. They must also pass a 90-minute, performance-based, multiple-choice exam.
ISACA Certified Information Systems Auditor
ISACA’s CISA certification serves as a foundation for early-career IT professionals. This certification shows that individuals can develop risk-based approaches to planning, execute on reporting, and perform during audit engagements. To earn the certification, applicants register for and take the CISA exam.
After passing the exam, applicants must complete at least five years of relevant professional experience. To maintain certification, professionals must undergo 20 hours of continuing education each year. ISACA reports that this in-demand certification leads to higher salary potential and boosted job performance.
Amazon Web Services Certified Solutions Architect
Designed for computer science professionals working in architecture, the AWS certified solutions architect credential demonstrates that individuals can effectively design and deploy applications through AWS’s platform. As an industry leader for online solutions, AWS’s influence reaches across all industries, and many companies require AWS-certified architects.
Candidates need at least one year of experience designing and managing scalable systems on AWS. AWS also recommends that applicants have hands-on experience with AWS tools.
Microsoft Certified Solutions Associate: SQL 2016 Database Administration
Created for professionals who work closely with SQL, the MCSA SQL 2016 database administration certification demonstrates that individuals possess excellent IT skills. Best for those pursuing careers in database administration or infrastructure, the MCSA certification tests applicants’ all-around IT skills.
Candidates must pass multiple exams to secure this certification. They must also complete at least one Microsoft-certified exam each year to satisfy continuing education requirements. Microsoft plans to retire this certification in 2021, though anyone who secures the certification now may hold onto the certification indefinitely.
Another well-respected certification created by CompTIA, the Linux+ certification validates the skills of IT professionals working with various types of computing systems. To earn this certification, professionals must pass an exam that covers all major tasks associated with Linux. Exam topics include Linux command line, networking, basic maintenance, and workstation configuration. CompTIA recommends that applicants first earn CompTIA A+ certification.
Many Linux+-certified professionals work in mobile application development, web administration, and cybersecurity. A Linux+ certification leads to job titles including network administrator, technical support specialist, and systems administrator.
Career and Salary Outlook for Computer Science Graduates
Computer science covers a broad range of topics, and the fast-growing field continues to introduce new topics, skills, and job titles. Overall, computer science careers are projected to experience high growth rates. Some careers experience faster growth and higher salaries than others. To reach the highest-paying, fastest-growing careers, students should complete higher levels of education.