Who typically gets a Master of Science in Computer Science with an Artificial Intelligence Specialization? Later in this article, we’ll meet four distinct types of students you’ll likely encounter in this program, but for now, let’s focus on traits that most or all students share in common.
The problem is, the list of common characteristics among these students is pretty short. That’s because computer science spans so many specializations and interests that it attracts a broad range of graduate students. Some arrive fresh out of college; others return to the classroom after two, five, or ten years in the professional world. Some have a bachelor’s degree in computer science, electrical engineering, or mathematics; others come from different fields. Some have already been to graduate school and earned a master’s degree—or Ph.D.—in another area. Others are seeking their first graduate degree.
Their ambitions differ as well. Many seek to improve their competitive advantage in the professional world, knowing that a master’s can qualify them for more responsible and higher-paying jobs. Others hope to enter research or academia, using their master’s degree as a stepping stone to a Ph.D. program.
A commitment to lifelong learning is crucial in this field—advances arrive frequently and quickly, so AI professionals need to keep up-to-date on all developments.
It’s not even a given that they all have well-developed programming skills. There are computer science programs specifically designed for non-computer science majors who need to get up to speed on basic skills before they can attack more advanced content. SMU Lyle, for one, admits students with majors unrelated to computer science but requires them to complete articulation coursework (or test out) before beginning graduate-level courses.
What all these students share in common is:
- Aptitude for advanced mathematics
- Curiosity and a strong desire to solve problems
- Strong analytical skills
These traits are particularly critical in an artificial intelligence program, where statistics, mechanics, data mining and natural language processing all figure prominently. A commitment to lifelong learning is also crucial in this field—advances arrive frequently and quickly, so AI professionals need to keep up-to-date on all developments. It’s not easy work, but if you love it, you’ll feel more engaged than challenged or frustrated by the profession’s demands, and you will derive immense satisfaction from your accomplishments and victories.
Why get a master’s degree in computer science?
According to DataUSA, there are currently over two million computer science jobs in the United States, with the job market expected to grow almost 5 percent in the coming year. LaborInsight projects a 19 percent growth rate in the computer science job market over the next decade. LaborInsight also reports that nearly four in ten computer science jobs require a minimum of a master’s degree.
Drill down a little deeper, and the data are even more compelling. The US Bureau of Labor Statistics (BLS) predicts a 15 percent growth rate for computer and information research scientists, a group to which artificial intelligence professionals belong. The BLS indicates that these jobs—for which a master’s degree is the minimum academic requirement—return an average annual income of $122,840.
If you’re looking for job security and a comfortable income, computer science can deliver on both fronts. However, the best reason to pursue a computer science master’s is that you love computer science and want to excel in the profession.
How popular is an MSCS degree?
The National Center for Education Statistics reports that master’s degrees in computer and information sciences constituted roughly 5 percent of the more than 800,000 master’s degrees awarded in the US in 2017-18. That makes it the fourth-most-popular field of study (after business (23 percent), education (18 percent) and engineering (6 percent)).
You can earn a master’s degree in computer science from any one of 249 institutions in the United States, plus many more overseas. More than 11,500 students completed a Master of Science in Computer Science between 2015 and 2019, according to LaborInsight. That’s a lot, but is it enough to fill all available positions? According to LaborInsight, not really; employers posted more than 15,000 computer science jobs that required master’s-level training in the last year alone.
Why earn your MSCS-AI from SMU Lyle Online?
If you’re considering earning an Online Masters in Computer Science with Artificial Intelligence Specialization from SMU Lyle Online, you’ve likely already given the prospect of remote learning some thought. You probably find the convenience of learning anywhere you can access a computer and wifi appealing, as do so many online learners.
So, where to pursue your master’s? The number of online grad programs in artificial intelligence is relatively small, and not all degree programs are the same. For example, some programs deliver all academic content asynchronously, meaning students do not attend live instructor-led sessions. That’s convenient, but many students say they miss the give-and-take of live classroom instruction. SMU Lyle Online classes meet weekly in virtual classrooms (in the evenings or on weekends, to accommodate working students’ schedules), providing students ample face time with their professors and classmates. Virtual office hours further strengthen the bond between faculty members and students, while teleconferenced group study sessions and projects nurture camaraderie, collaborative work and valuable networking opportunities among students.
Online learning with the Lyle School of Engineering stands out in other ways as well. Its curriculum offers online students an unusual degree of academic freedom; the required core curriculum consumes only 12 of the 30 credits necessary to complete this master’s program. That means you can dedicate more than half your time here to courses of your choosing—in artificial intelligence or in related areas to develop your own subspecialization. The curriculum itself focuses on practical, hands-on learning with real-world applications. A holistic approach to content produces a broad understanding of AI’s essential principles and practices that can be applied across industries and situations. An emphasis on design thinking fosters creativity and innovation as well as project management skills.
SMU Lyle Online admission is competitive but does not require an extensive computer science background; the curriculum includes the programming training necessary to succeed here. Students with two or more years of relevant work experience may receive a GRE waiver, meaning they can apply without undergoing the hassle of standardized testing.
Four People you’ll meet in an MSCS-AI program
Every computer science graduate program has its ‘types.’ Who are the most common types you’ll encounter in an online Master of Science in Computer Science with an Artificial Intelligence Specialization? We’ve identified four:
- The career starter
- The career advancer
- The career changer
- The career reskiller
Let’s discuss each in a little more detail.
The Career Starter
The career starter is the youngest of the four types; they are typically 22 to 26 years of age, either fresh out of college or with only a few years of professional experience. If they’ve been working, their job title is probably something like:
- Help desk specialist
- HRIS analyst
- IT consultant
- IT service desk specialist
- IT technician
- Junior cybersecurity specialist
This student has likely already mastered some basic programming languages and has developed skills in big data analysis, coding, network troubleshooting and support, and quality assurance. They spend their spare time boning up on cybersecurity, cloud computing and machine learning, and they enjoy a good hackathon.
What drives this student? Primarily, a desire to advance beyond the early-career role they now fill at their jobs. They may dream of working for one of the big-name tech companies like Amazon, Facebook, Google, or Microsoft. A master’s provides a path toward that goal, especially if it includes a specialization in a hot, emerging field like artificial intelligence. They may aspire to a position as a software engineer to develop new products and processes. This student brings enthusiasm and ambition to the classroom.
The Career Advancer
The career advancer may be in their late 20s or early 30s, although some are older. They have already logged significant time in academia and/or professional life. They may hold a master’s degree in mathematics, statistics, engineering, data science or a related field. They work at jobs with names like:
- Automation engineer
- Computer scientist
- Data architect
- Data processing specialist
- Data scientist
- Lead data engineer
- Manager of data analytics
- Systems engineer
- Systems manager
The career advancer already performs high-level computing tasks at work, including:
- Deploying sophisticated analytics
- Engaging with those who implement programming, machine learning and statistical methods
- Overseeing data mining
- Producing analytical reports for company stakeholders
Their work requires some serious computer skills, such as Apache Pig, C++, Hadoop, Javascript, Python and/or SaaS. Through their work, they have developed interests in blockchain, big data, cloud computing, dark data, data mining, deep learning, GDPR, IoT, machine learning theory, predictive analytics, natural language processing and quantum computing. Perhaps already a manager, the career advancer hopes to ascend to the director or vice-president level. This student brings a lifelong commitment to learning and improvement to the classroom.
The Career Changer
The career changer is likely in their mid-20s to early 30s. They have a bachelor’s degree in a comp-sci-related field like statistics and may hold one of the following job titles:
- Business analyst
- Business intelligence architect
- Business intelligence consultant
- Business intelligence engineer
- Business intelligence manager
- Cybersecurity analyst
- Data analyst
- Data architect
- Intelligence analyst
As their job titles suggest, the career changer has expertise in a computer science-adjacent discipline that may involve analytics, data management or cyber security. They have aptitude in Amazon Web Services, business process analysis, Tableau, project management, SCRUM, SAS, SQL, Python, market research, data analysis and data visualization.
Their job regularly exposes them to many computer science opportunities and inspires them to learn more. This exposure fosters interests in augmented analytics, automation, business analytics, data governance, data security, data visualization, database managing and reporting, ethical data, GDPR and predictive analytics. The possibilities created by data mining and business intelligence excite them, and they are looking to develop skills that will allow them to better exploit their promise. They are particularly intrigued by the many opportunities opening in artificial intelligence. They bring to the classroom the drive to make a difference.
The Career Reskiller
The career reskiller has advanced skills in a specific computing area—they may be a software engineer or a web developer. They aspire to broaden their skill set to develop new career opportunities. They may be in their late 20s to late 30s, although some are older. Their job titles include:
- Applications developer
- Computer consultant
- Data architect
- Data engineer
- Programmer
- Software architect
- Software developer
- Software development engineer
- Software engineer
- Systems engineer
- Systems integration engineers
- Systems manager
- Web developer
The career reskiller sees artificial intelligence as a new frontier, ripe with opportunity for those who invest the time and sweat to learn it. They already have an impressive array of computing skills that may include C, C++, complex problem solving, development operations, Java, Javascript, Python, Ruby, Scala, software engineering and systems design. They hope to build new skills in algorithm engineering, application development, cybersecurity, data warehousing, e-commerce, edge computing, operating systems and system software, machine learning and virtual reality. This student brings to the classroom a capacity to capitalize on all past professional experiences.
Whether you are one of these four types of students or another type entirely, as an SMU Lyle Online student, you will learn from your classmates as well as from your instructors. Each student in this program adds value to the virtual classroom.
Ready to learn more about our Online MSCS-AI?