Because artificial intelligence is a relatively new technology, myths about AI are pervasive. For example, many people believe AI is just another word for deep learning, which they further assume must be synonymous with machine learning. Some believe that artificially intelligent systems are already approaching human levels of intellect and represent an immediate danger to our way of life. And many conclude, based on their own limited understanding of the technology, that computer scientists don’t know why or how AI does what it does.
The reality of modern AI may be less exciting than movies and TV suggest but is far more exciting than many people realize. First and foremost, artificial intelligence is a widely applicable tool that lets people work more efficiently, more quickly and with fewer mistakes. PwC predicts that artificial intelligence could contribute up to $15.7 trillion to the global economy over the next decade by powering advancements in healthcare, manufacturing, technology, business, finance, retail and more.
This is only possible because qualified AI specialists are searching for ways to use artificial intelligence to tackle the world’s most pressing problems. These include not only business challenges and economic issues but also climate change, poverty and inequity. Can AI really make the world a better place? When this technology is wielded by professionals with a deep understanding of its present-day applications and its long-term potential, the answer is yes.
The challenge is that there aren’t enough skilled professionals with the expertise to use artificial intelligence for the good of their organizations and for the betterment of humanity. That’s where the Masters in Computer Science with Artificial Intelligence Specialization (MSCS-AI) from SMU’s Lyle School of Engineering comes in. Just like AI itself, artificial intelligence degrees are subject to many misconceptions. This article digs into the most common myths about artificial intelligence master’s programs to set the record straight so you can make an informed decision about whether your future lies in this growing and evolving field.
8 Myths About Earning an Artificial Intelligence Master’s
Myth 1: Specialized AI Degree Programs are More Expensive
Calculating the cost of an AI-focused computer science master’s is less straightforward than you might assume. Per-credit tuition is just one piece of the equation. You must also factor in opportunity costs – i.e., do you have to sacrifice income to earn an MSCS – and the wage premium associated with this type of degree.
As a baseline, earning an MSCS can give you the skills and credentials to transition into senior and technical roles that pay more than $100,000. Earning a Master of Science in Computer Science with an AI specialization can boost that baseline by roughly $30,000, leading to jobs that pay more than $130,000 on average.
Meanwhile, the 30-credit MSCS-AI program at Lyle School of Engineering costs $1,350 per credit hour, with a $100 distance fee per credit hour. All told, that’s a $43,500 total investment, which is right in the middle when it comes to the average cost of master’s programs and not more expensive than other computer science degrees. Because the program is offered part-time and online, you don’t have to sacrifice income to upskill in artificial intelligence and machine learning.
Myth 2: Artificial Intelligence Is a Niche Discipline
Many people think artificial intelligence master’s degrees are only applicable in the technology sector and that programs focus only on AI. However, programs such as SMU’s MSCS-AI acknowledge that AI has already moved beyond tech. Automation, deep learning and machine learning algorithms can advance workflows in business, increase efficiency and improve outcomes in healthcare, push hiring processes forward and expand access to clean energy. A computer science degree with an AI focus can prepare you for leadership and technical roles in many industries.
The artificial intelligence master’s curriculum is holistic and teaches the soft skills, problem-solving abilities and deep thinking capacity you’ll need to consider the ethical implications of AI implementation. You’ll use the same cutting-edge technologies in your online courses as students studying on campus and tackle projects that will give you real-world experience. Core courses cover the fundamentals of artificial intelligence and machine learning in Python. From there, you can choose from among several in-depth specialization electives that cover data mining, information retrieval, knowledge-intensive problem-solving, natural language processing and internet applications.
Myth 3: Only Computer Scientists Can Get In
You don’t need to be an expert in AI programming languages or have a technological background to succeed in a computer science master’s program. You should have basic coding skills in languages like Python or Java because that will help you succeed in your classes, but you can study artificial intelligence without a bachelor’s degree in computer science or a related field as long as you take articulation coursework or satisfy a competency requirement. If you are motivated, eager to learn and determined to succeed, there is a place for you in SMU’s MSCS-AI.
What are the specific prerequisites for earning an MSCS-AI at SMU?
MSCS-AI candidates typically have a bachelor’s degree in computer science, one of the quantitative sciences, mathematics or engineering with a GPA of 3.0 or higher on a 4.0 scale. The ideal applicant also has a background in tech, which might be professional experience, internships, research participation or other experiences that demonstrate an aptitude for computer science and AI. Applicants with two years of professional experience can request GRE waivers. Other applicants typically have a quantitative GRE score in the 80th percentile or better.
Myth 4: I Can Learn the Same Things in a Bootcamp
AI bootcamps are such an attractive alternative because they are short and relatively inexpensive when compared to master’s programs. However, they are also less comprehensive than master’s programs by several orders of magnitude. They’re often hyper-focused on specific technical skills and don’t teach students to adapt to the future of technology.
What the best AI master’s programs have in common is something bootcamps can’t replicate: the people. Bootcamps can’t replicate the depth of faculty experience, the networking opportunities and the supportive classmates you’ll get in a top MSCS program.
Keep in mind, too, that there is growing demand for AI master’s degrees in several industries, including healthcare, finance, retail and manufacturing. There’s also demand for AI skills in the tech sector, which has a reputation for being degree-neutral but actually rewards degree holders handsomely. Amazon, NVIDIA and Microsoft hire the majority of artificial intelligence degree holders.
What makes SMU Lyle’s online MSCS-AI different?
Lyle School of Engineering’s online MSCS-AI program takes an innovative, career-focused and forward-thinking approach to AI and machine learning. Students pursuing an artificial intelligence master’s degree online at SMU do more than just hone hard skills. Distance learners can take advantage of resources unique to the university, such as the AT&T Center for Virtualization – where researchers throughout conduct interdisciplinary research to address technical, economic and social issues – and the SMU AI Lab, where students are using natural language processing and SMU’s supercomputer to assist biologists with COVID-19 therapy research. Post-graduation, 88 percent of Lyle students are employed.
Myth 5: I’ll Feel Isolated in an Online Master’s Program
SMU Lyle’s artificial intelligence master’s program offers many opportunities for connection – it’s up to you to take advantage of them. You’ll attend weekly “sync sessions” with your instructors during which you can ask questions about coursework and receive one-on-one feedback. You’ll get to know your classmates, who will be an important source of support when you need help with coursework, advice about navigating the employment landscape or balancing full-time work and a part-time master’s program. And you can take part in faculty research in machine learning, cyber security, data mining, data science, electronic design automation and software engineering.
Myth 6: Online Programs are Watered-Down Versions of On-Campus Programs
The format of a graduate artificial intelligence program will matter less than how you approach your education. Today, the classes in most online degree programs are identical to that in on-campus programs – and so is the work. You can participate in labs, collaborate with peers on project work and participate in lively classroom discussions. The online artificial intelligence master’s program at SMU is as rigorous as any on-campus program. It provides hands-on, interactive experiences that meld the latest computer science technologies with education to recreate the classroom experience for distance learners.
Myth 7: I’ll Have to Quit My Job to Earn an Artificial Intelligence Degree
This may be true in full-time AI and machine learning master’s programs but is demonstrably not true of part-time programs. SMU’s MSCS-AI is geared toward working professionals who must maintain a work-life-study balance to succeed. The coursework includes synchronous classes – weekly meetings led by instructors – and asynchronous work built around videos, readings and quizzes. Working full-time while in graduate school isn’t easy, but it’s also not impossible.
Myth 8: Full-Time Programs Look Better On Resumes
There is no need to indicate on your resume how you earned your graduate degree. Most employers won’t care whether you earned a master’s degree in a part-time or full-time program. However, there could be benefits to letting potential employers know that you studied part-time. Online programs are not easier than on-campus programs. Part-time programs may even be more challenging. The fact that you successfully balanced work, school and a personal life while pursuing an artificial intelligence master’s is impressive. Your degree is proof positive you know how to juggle multiple responsibilities and are so committed to upskilling that you earned a degree while working. It demonstrates your determination and dedication, as well as your command of in-demand computer science skills.
Is an MSCS-AI the Right Master’s Degree for Me?
Before enrolling in a graduate program, consider your goals: do you want to advance in your current career by optimizing your company’s AI implementation? Do you want to launch a new career with higher salary prospects? Are you interested in conducting cutting-edge research that will leverage AI technology to benefit humanity?
If the answer to any of these questions is yes, then SMU’s online MSCS-AI program may be the right fit. World-class faculty will guide you through courses in data mining, programming in Java and Python, machine learning algorithms, training deep learning models, natural language processing, neural networks and more.
Looking forward, it’s unlikely artificial intelligence will take over the world a la science fiction. AI will render some job roles obsolete, but it will also open up opportunities for employers to create thousands more. “In addition to new types of workers who will focus on thinking creatively about how AI can be developed and applied, a new set of personnel will be required to build, maintain, operate and regulate these emerging technologies,” PwC asserts in the report linked above. If you want to be part of this AI-driven future, apply to earn your MSCS-AI today to master artificial intelligence in as little as two years.