We have long since stopped referring to the future when we talk about artificial intelligence. The next 10 years will be important for the development of a technology that, together with 5G, is set to take centre stage of a true revolution on a social, economic and industrial scale.
Why study artificial intelligence?
This is because more and more professionals qualified in artificial intelligence are in demand. In the wake of the pandemic, industrial areas such as process automation, the still nascent metaverse and artificial intelligence have accelerated their prominence. Infojobs, through its tool Job Market Insights registered a 31% increase in job offers linked to artificial intelligence in 2022 compared to the previous year.
So, the reader may be wondering what to study to work in artificial intelligence. Below, and as we did in the special feature on working in cybersecurity, we are going to share valuable information for anyone considering a career in this exciting world. We start from the assumption that the reader already knows what artifical intelligence is and how it works, so let’s get straight to the point.
What skills does it take to work in AI?
We can divide the skills needed to work in AI into two parts: Hard Skills and Soft Skills.
Hard Skills needed to work in AI
Programming language. In order to develop programmes based on artificial intelligence, we need to know different programming languages. For example, Python is used for machine learning or NLP (Neuro Linguistic Programming) comprehension; C++, whose libraries are used to create more complex codes; Java, an object-oriented language with a virtual machine to run the developed programs anywhere.
Mathematics. In order to be able to develop models with Machine Learning, it is essential to have knowledge of Linear Algebra, Calculus and Algorithms, as well as Probability Theory, Statistics and Mathematical Optimisation, even at the beginner level.
Machine Learning. One of the most important areas within the field of artificial intelligence is Machine Learning. This is a technology that allows computers to learn from data and improve their ability to make predictions or decisions based on that data. A simple example of Machine Learning is image recognition. The machine is provided with a series of images labelled ‘chair’ or ‘table’ and it learns to identify what a chair and a table are, what differentiates them, and so on. Another example could be Netflix: the recommendations suggested by the platform are based on Machine Learning algorithms to analyse what users watch and, based on this data, recommend similar content.
Natural Language Processing (NLP). You need to have natural language processing skills to be able to work on projects such as ChatGPT or other chatbots, e.g. those used in customer service.
Big Data. Knowledge of Big Data technologies, including Hadoop, Spark, NoSQL and distributed databases (DBD).
Cloud Computing. If you want to work in artificial intelligence you should have experience in Cloud Computing and know the ins and outs of platforms such as Amazon Web Services (AWS), Google Cloud Platform (CGP) or Microsoft Azure.
Robotics. You should have a background in robotics to work on process automation and the creation of autonomous robots. And the fact is that robots are doing more and more jobs on their town.
Soft Skills for working in AI
- Critical thinking: analysing information objectively and questioning assumptions is essential for working in artificial intelligence.
- Good communication: ideas and solutions must be communicated very clearly. This is important because you are always working in a team with people who may have different knowledge levels.
- Continuous learning: you must be a person with an inexhaustible thirst for knowledge, as AI is a continuously evolving field.
- Ethics and responsibility: Artificial intelligence is having a profound impact on society at different levels. That is why good AI practitioners need to consider the implications of their work and ensure that it is put to good use.
- Languages. English is mandatory to work in artificial intelligence.
How to learn artificial intelligence from the ground up
If you want to learn basic Artificial Intelligence Engineering, in addition to the mandatory studies, you can train on your own with some free courses that you can find on the Internet. We suggest some very interesting ones:
Google Platform for learning AI. Only in English, this very complete platform consists of different courses, documentation and visual and interactive guides to get an overview of Machine Learning and artificial intelligence.
Machine Learning. A very reputable course, taught by Andrew Ng, professor at Stanford University and head of Google Brain, for which you will need to know some basic coding and a high level of mathematics (arithmetic and algebra, above all). It has English subtitles and lasts about three months. The course is free through the Coursera platform, but the certificate costs around 70 euros.
Artificial Intelligence for everyone. Another course on Coursera taught by Andrew Ng in which you will learn the common terminology of AI, everything it can do, working with an AI team, spotting opportunities to apply AI to issues in your company, and so on. It lasts 10 hours, it is free, but if you want the certificate it will cost you about 50 euros.
Best study options and programmes to work in AI
Most industry professionals agree: it is important to have a strong mathematics or engineering background to enter the world of artificial intelligence. Studying at university is highly recommended, as it is now a good way to acquire a good scientific foundation. For example, the Polytechnic University of Madrid offers a Master’s Degree in AI as well as the International University of Valencia, which also offers a specialised master’s degree.
The best thing to do is to consult the internet to find the best universities and schools for training in artificial intelligence and decide which one suits you best.
