The idea that human-made machines might be able to learn and develop in ways that only humans could had debated for years—most fervently in the 1950s, in the wake of mathematician and computer scientist Alan Turing's paper, "Computing Machinery and Intelligence," where he asked, "Can machines think?" It was a daring and exhilarating question—one that we now know the answer to. While the first artificial intelligence (AI) program was written in 1955, the limitations in computer processing and memory significantly hampered the field’s growth until technological advancements in recent decades allowed for the theoretical to become reality—and AI’s been rapidly developing by leaps and bounds ever since. In fact, so much so that artificial intelligence appears to be moving us into a fourth industrial revolution, where the unprecedented volume of data will fuel intelligent machines to learn and evolve without human intervention.
Machine learning and deep learning are enabling machines to problem-solve through trial and error with enormous data sets. We’re attempting to utilize this artificial intelligence to find patterns and solutions to critical medical, environmental, and theoretical questions that humans so far have been unable to do on their own. This means that AI is—or will be—present in every industry as we move rapidly forward. And it's just getting started.
As Bernard Marr wrote in a recent piece for Forbes, "...it's important to understand that; however you feel about it, AI cannot be ignored. Every business leader needs to come to terms with this fact and take action to prepare their company accordingly. This means working out how and where AI will make the biggest difference to your business, and developing a robust AI strategy that ensures AI delivers maximum value."
This newest industrial revolution brings with it what previous ones have—a boom in jobs. Career opportunities for AI researchers, developers, and engineers are widespread, and AI professionals are in high demand in almost every business sector. AI professionals also are very well compensated for their work.
It's safe to say that nearly every industry is utilizing artificial intelligence, and that this technology will continue to evolve. AI technology is not just for Microsoft or Amazon or Tesla's self-driving cars. Any business that relies on data analytics to perform is able to benefit from machine learning technology. In fact, the larger the data pool, the more accurate the algorithms and learning capabilities. So industries like healthcare and supply chain logistics benefit greatly from this technology.
Salary.com lists the average salary for jobs that require artificial intelligence skills at $118,466. This figure is higher if you live in California, New York, or other tech-heavy regions of the country. ZipRecruiter lists salaries for artificial intelligence engineers at $164,769, intelligence researchers at $149,704, machine learning research scientists at around $148,993, and senior artificial intelligence engineers at $148,136 per year.
The average pay for an an AI scientist is about $125,993 a year and a natural language processor is paid about $109,000/year. The average salary for a machine learning engineer is about $121,446, increasing to about $147,000 with additional years of experience.
The job market for artificial intelligence careers is vast, as AI and big data touches every industry. Top job postings in industries that rely on data analytics might be for artificial intelligence researchers and software engineers. Job titles might include user experience experts (UX), data analysts, data scientists, AI programmers, software developers, research scientists, software engineers, or big data engineers.
You don't have to have a master's degree to secure a job in AI, but you might find it essential for advancing your career. Computer science and artificial intelligence jobs are highly specialized (and well-paid), and an advanced degree that reflects your training and skill set will allow you to advance to top positions. While you may score an entry-level job with just a bachelor's degree or a certification, a master's degree or a PhD (and experience) will likely qualify you for the highest paid positions.
This question may be answered best by identifying what knowledge and skills you’ll need to further your career. Many artificial intelligence master's candidates are professionals in data science looking for a way to move ahead on their career path. Researching different AI master's programs will help determine where you should focus your time and energy—and whether you are able to attend classes in person after work or on weekends, or if an online program will give you the freedom to enroll in a program across the country.
Depending on your industry, a Master of Science in Computer Science (MSCS) with a concentration in AI might be your best approach, or a master's in applied artificial intelligence, a master's in machine learning, or other related specialized area of study.
Artificial intelligence master's programs are constantly evolving in order to remain on the cutting edge of information technology. Schools follow a number of approaches to their degree's design. They may be called an applied artificial intelligence master’s, or you may see them listed as a computer science master’s with an artificial intelligence specialization.
We'll look at how long you can expect it to take to earn one, what you'll need to bring to the admissions process, and what specializations you might consider.
In addition to attracting recent bachelor's degree graduates, artificial intelligence master's degrees are targeted and designed for working professionals who want to move forward in their AI career. Many programs are flexible, offering evening, hybrid, and fully online coursework to accommodate busy professional schedules. You can expect to be able to earn your master's in three years—or in two if you commit to an accelerated program.
Most artificial intelligence master's programs will expect an undergraduate degree in computer science, computer engineering, or a related field. Each program will be different, but you can expect to provide your full undergraduate transcript (with a minimum of a 3.0 GPA), resume, letters of recommendation, and possibly GRE or GMAT test scores. For working professionals, your years of work experience will probably be considered more strongly than your undergraduate coursework, especially if you have continued to stay current with industry certifications.
Over the course of your studies, you can expect to become fluent in software like Hadoop, Java, Python, and other programming languages. You'll develop an understanding of SQL and relational databases, neural networks, machine learning algorithms, and deep learning, as well as how to communicate data findings through strong visualization tools and techniques. You also can expect to graduate with very strong communication skills, programming expertise, and a deep understanding of software development—making you a strong and highly-trained candidate for positions in the field of artificial intelligence.
You may have the option to specialize in cyber security, business intelligence, or focus on industries like healthcare or bioengineering. The overlay of a specialization allows you to apply your skill set to an industry that interests you or shows potential for growth. You also might be interested in focusing on the use of AI in human-computer interaction, computer and network security, biocomputation, information management or others, depending on where you'd like to go with your career.
With so many unique specializations and areas of study to choose from, you'll have to do a lot of research to find the right place for you. Here are a few of the top programs in the US where you can pursue your master's in artificial intelligence:
Not only can you earn your master's in artificial intelligence online, there are a number of fantastic programs to choose from:
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