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Technology> Artificial Intelligence Updated: 02 Nov 2018

How to get a job in Artificial Intelligence

Artificial Intelligence is no longer science fiction. In fact, it has begun to revolutionize the job market, providing opportunities for professionals with a solid foundation in STEM (science, technology, engineering an mathematics). Universities are responding with graduate programs and online courses in specific areas of AI.

What do you want to be when you grow up? A drone operator, nanorobot driver, smart factory engineer? Artificial Intelligence (AI) is starting to revolutionize the job market.  According to data from the Observatory for Employment in the Digital Age, 80% of Spanish people between 20 and 30 years of age will hold a profession during their careers that has recently been created or is still in gestation.

The current situation, however, is less optimistic and even worrisome. The global deficit in professions with higher education in this area will be 40 million in 2020. However, AI is a field in which there are increasingly more possibilities to receive both basic and  specialized education, in areas such as big data, robotics, and computer intelligence.

AI is a cocktail of disciplines and applications. The demand for professionals is so cutting-edge that a solid combined knowledge of STEM (science, technology, engineering and mathematics), which is practically evolving in real time, can help you carve out a spot in these recently formed positions.

People trained in different branches of science, with a good foundation  in mathematics, or people with a degree in technical engineering, have it easiest to guide their training.

The best education is provided by countries that have introduced computational thinking into their primary and secondary schools. “Students of the future need to know this language, even if they end up studying any other branch of science, like medicine, biology, architecture and economics,” says  Andrés Pedreño, the dean who converted the University of Alicante (UA) into a reference point for technology in the world of academics, and is also one of the leading Spanish experts on the digital economy. “It is important to complete the information with knowledge of computer science for programming and design,” agrees Manuel Martín Molina, professor of the Artificial Intelligence Department of the Technical University of Madrid.

For Martín Molina, who is also president of the laboratory of ideas, It&Is Siglo XXI, “The issue is of the utmost urgency and significance,” because from his point of view, “There is no future position for our country, nor training of human capital without a good educational base in computational thinking.”

He says it is also important to break some stereotypes associated with computer science. Certain images of computer scientists are unhelpful, as he pointed out, “For example, generalizing the image of computer scientists as being freaks, who are generally males, is damaging to this profession and may block people from participating who have great potential talent for artificial intelligence.”

Universities take the lead

Universities are already started to offer specific training in AI. But the first step is to get an undergraduate degree with an important basis in mathematics and engineering, such as computer science, mathematics itself, physics, telecommunications or industrial engineering. Later, it’s ideal to have a post-graduate specialization (master or doctorate) in areas of Artificial Intelligence. “For example, there are high-quality official master’s degrees at Spanish public universities related to artificial intelligence (to learn automation, robotics, etc.),” explains Martín Molina.

These studies tend to include content regarding knowledge and reasoning (in order to automatically  carry out planning or diagnostics), automatic learning, cognitive robotics, computational perception (for example, artificial vision or speech recognition) and processing natural language (such as text comprehension and text generation).

“In any case, mathematicians and computer engineers have an excellent basis for advancing toward the fields of machine learning, and deep learning,” Pedreño sayd. In his view, a hybrid of data and science will provide  a more competitive training.

Online education options

In parallel, online degrees and MOOC’s  (Massive Online Open Courses) provide excellent AI training. After completing the basic curriculum, one can specialize in a specific area: big data, robotics, computational intelligence.

Online training is highly recommended and in-person training has become a growing and increasingly competitive field. In the opinion of the experts, Udacity, Coursera and Edx, among other platforms, are offering excellent courses in the MOOC format.  These cover everything from automatic driving, introduction to AI, Machine Learning, Neuronal Networks and other AI techniques.  Systems such as TensorFlow, the AI library that Google has made open-source, and Microsoft’s Cognitive Toolkit, bring the learning platforms within the reach of practically anyone.

There is also officially regulated AI-specific training provided by remote universities on e-learning platforms. This is the  case, in Spain, of UNED (Master’s in Advanced Artificial Intelligence), or the most recent initiative promoted by the Spanish Association for Artificial Intelligence (AEPIA) and Universidad International Menéndez Pelayo (UIMP), a Master’s in AI research. Also, the University of La Rioja (UNIR), which has several courses and Master's programs, offers online training in AI.

“The faster we advance in quality education on all fronts, the better,” Andrés Pedreño says. “The important thing,” he pointed out, “is to be able to work and understand specialists in AI.” For this expert, the first step should pass through a conceptual approach to the matter, which contributes to breaking down the language barriers of this field.

Perhaps more than other discipline, continuous training is essential in this profession, where techniques evolve very quickly. Given the degree of innovation expected, future collaborators must be able to design a very solid training strategy. “Today, international networking is surprising. Apart from identifying the best talent, it provides very valuable networks for complimenting knowledge and designing new developments,” comments Pedreño, who has dared to undertake the challenge that universities have ahead of them in this regard.

“Professionals who work in AI should be capable of self-learning, efficiently handling publications in English such as technical and scientific reviews, and other online resources and social media.”

The year 2018 will be another very good one for AI. “80% of large organizations will invest in this area, 60% will carry out concept tests,” says Joseph Reger, Head of Technology at Fujitsu, “and all of them will suffer a lack of trained workers. This year will be the beginning of the end of the job market as we know it. AI is not just the future, it’s the immediate present."