Specialization can improve your prospects in any professional job market by adding unique knowledge and skills to your resume. That’s particularly true in computer science, a field so vast and complex that specialization is practically the only way to achieve proficiency. You can’t master all of computer science, but you can gain a pretty good grasp on one of its many specialized fields.
Computer science master’s programs realize this. That’s why they offer various specializations (sometimes called concentrations). Students typically complete a required core curriculum and commit the remainder of their course credits to elective work, some (or all!) of which cover the specialization of their choice.
The Online Master of Science in Computer Science at Tulane University, a 30-credit 100 percent online degree program, offers at least six areas of specialization, including: computational geometry, computational biology and bioinformatics, algorithms and theory, systems, data science, and artificial intelligence and machine learning. The program offers students the flexibility to combine electives and specializations to best suit their needs and goals.
Each specialization offers unique opportunities to acquire valuable expertise and advance your career. How? This article explores that question below.
Computational geometry uses algorithms and data structures to recognize geometric patterns and solve geometric problems. Its goal is to create efficient, effective algorithms to process and utilize geometric data. The field’s numerous practical applications include any situation in which a computer interacts with the physical world.
3D modeling, computer graphics, computer vision, computer-assisted design, game design, geographic information systems, image processing, molecular modeling, robotics, software engineering, and virtual reality all utilize computational geometry. Future advances in data organization and computing power should open new vistas in this field, creating additional opportunities in sectors as varied as manufacturing, urban planning, and medicine.
Computational Biology and Bioinformatics
According to the Bureau of Labor Statistics (BLS), healthcare and social assistance constitute the fastest-growing part of the U.S. economy. Advancing medical capabilities and an aging population have combined to drive up demand for medical treatment and medical research.
Computational biology and bioinformatics exploit the capabilities of biodata-gathering devices, computing, and data science to improve diagnoses, develop new treatments and drugs, predict health outcomes at individual and population levels, and advance research in genetics, disease detection and prevention, and the human microbiome. The field uses machine learning and artificial intelligence to organize, analyze, and make predictions driven by health care big data. It offers essential contributions to enterprises across the health and biology spectrums, including DNA sequencing, pharmaceutical research, evolutionary biology, and agricultural research.
Algorithms and Theory
Algorithms are instructions that computing devices follow to execute a specific command or process identically every time. They range from simple operations like sorting lists to complex problem-solving processes, such as optimizing traffic flow for an entire city. They curate social media news feeds, drive search engines, recommend purchases, control self-driving cars, generate and continually adjust GPS navigation, manage investment accounts, enable virtual assistants, and automatically correct digital data transmission errors over networks and the internet. And that’s just the tip of the iceberg; algorithms are so ubiquitous in our daily lives it would probably be easier to list the areas in which we don’t engage them.
At a higher level, algorithms provide the theoretical framework for computational problem-solving. Computer scientists break complex problems down into discrete tasks that can be performed algorithmically, then optimize algorithmic sequences so that they perform efficiently and predictably produce the desired result. Algorithms and theory hold the key to future computing developments; experts in the field will develop the algorithms that drive future technologies. Because algorithms are integral to all computing, specialization in this field can offer a particularly broad range of career options.
The study of computer systems focuses on operating systems, computer networks, distributed systems, and other critical elements of computer architecture. You’ll learn to design, scale, manage, optimize, and secure the computer systems that underlie virtually every company and institution operating in the digital era. This degree prepares you to work as a database administrator, DevOps engineer, information security analyst, IT consultant, network engineer, research scientist, systems architect, or systems software developer. Like algorithms and theory, systems study has broad applications across computing, making this a highly versatile specialization.
The amount of data generated every day is truly staggering: by one estimate, it amounts to 1.7 megabytes of data per person per second. For obvious reasons, making sense of all that information requires powerful and sophisticated tools and processes. Data science provides those.
The Bureau of Labor Statistics projects a 36 percent growth rate in the data science labor market between 2021 and 2031, with over 13,000 positions opening for data scientists each year due to growth, attrition, and job turnover. This field is expanding rapidly in part because it applies to so many enterprises: data scientists provide crucial insights in manufacturing, retail, banking, technology, education, healthcare, construction, engineering, telecommunications, government, media, and much more. Data science has applications across computer science disciplines as well. Analytics, business intelligence, data mining, artificial intelligence, machine learning, predictive modeling, bioinformatics, cybersecurity, and robotics are only a few that rely on data science to achieve their aims.
A data science specialization develops skills in data organization, data cleaning, data warehousing, predictive analytics, critical thinking, and problem-solving. As a data scientist, you’ll be a gatekeeper to a vast store of invaluable information. It’s a role that tends to draw attention and can ultimately lead to a management or executive leadership position.
Artificial Intelligence and Machine Learning
Unquestionably, artificial intelligence and machine learning are changing the worldwide work landscape. According to Accenture, 40 percent of working hours across industries have been or will soon be disrupted by large language models (LLMs) and other manifestations of AI. That doesn’t mean 40 percent of all jobs will disappear, however. Rather, up to 40 percent of tasks currently performed by humans could be shifted to computers, freeing humans to perform less repetitive, more fulfilling work.
Some jobs will be lost in the process. Others will emerge. According to the World Economic Forum (WEF), new positions will favor professionals whose skill sets include analytical thinking, technological literacy, systems thinking, quality control, and creativity. That’s a pretty good inventory of the skills you’ll acquire with an artificial intelligence and machine learning specialization.
Prospects are predictably bright in this field; when it comes to career advancement, it’s hard to beat an emerging technology that most businesses and institutions plan to adopt. According to the WEF, AI and machine learning specialists “top the list of fast-growing jobs.” All told, the WEF projects the addition of one million new jobs for artificial intelligence and machine learning specialists in the next four years. Roughly 75 percent of companies will seek to integrate artificial intelligence into their operations by 2027. Most employers are optimistic about AI’s net effect on employment: while about one in five predict it will eliminate more jobs than it creates, nearly half believe it will create more jobs.
Develop Your Computer Science Master’s Specialization Online at Tulane
In today’s digital world, a computer science degree is more valuable than ever. A bachelor’s degree and certifications can help you launch your career, but upper-level jobs require advanced-level knowledge and expertise you can acquire through graduate study. A master’s degree in computer science can qualify you for higher-responsibility, higher-impact positions.
You don’t have to quit your job and enroll in a full-time program to benefit from a computer science master’s program. The MS in Computer Science at Tulane University is 100 percent online; no campus visits are required. You’ll earn your graduate credential from a nationally renowned university in 20 to 36 months. You’ll learn from industry insiders and thought leaders, and you’ll have the opportunity to develop an area of specialization in one of six emerging computer science fields. You can even mix and match electives to curate a program uniquely suited to your career goals.
If you’re ready to tackle the computing challenges of tomorrow, contact us to learn more about earning your master’s in computer science online.