We have long stopped referring to the future when talking about artificial intelligence. The next decade will be crucial for the development of technologies that, together with 5G, will be central to a true revolution on a social, economic and industrial scale.
Why Study Artificial Intelligence?
This is due to the increasing demand for qualified professionals in artificial intelligence. The pandemic has accelerated the focus of industry sectors such as process automation, the nascent metaverse, and artificial intelligence. Infojobs, through its tool Job Market Insights, has recorded a 31% year-over-year increase in job openings related to artificial intelligence in 2022.
Readers may therefore be wondering what to study to work in artificial intelligence. Below, we share valuable information for those considering a career in this exciting world, as we did in our feature on working in cybersecurity. I’ll start with the assumption that you already know what artificial intelligence is and how it works, so let’s get straight to the point.
What skills do you need to work with AI?
The skills needed to work in AI can be divided into two parts: hard skills and soft skills.
Hard skills needed to work in AI
programming language. Developing programs based on artificial intelligence requires knowing different programming languages. For example, Python is used to understand machine learning and NLP (neuro-linguistic programming). C++. That library is used to create more complex code. Java is an object-oriented language with a virtual machine that lets you run your programs anywhere.
Math. To be able to develop models using machine learning, it is essential to have knowledge of linear algebra, calculus, algorithms, as well as probability theory, statistics and mathematical optimization, even at the beginner level. .
machine learning. One of the most important areas in artificial intelligence is machine learning. This is a technology that improves a computer’s ability to learn from data and make predictions and decisions based on that data. A simple example of machine learning is image recognition. The machine is presented with a series of images labeled “chair” or “table” and learns to identify what a chair and a table are, the difference between them, and so on. Another example is Netflix. Recommendations suggested by the platform analyze what users watch based on machine learning algorithms and recommend similar content based on this data.
Natural Language Processing (NLP). Working on projects like ChatGPT and other chatbots (such as those used in customer service) require natural language processing skills.
big data. Knowledge of big data technologies such as Hadoop, Spark, NoSQL, distributed databases (DBD).
cloud computing. If you want to work in artificial intelligence, you should have experience in cloud computing and know details about platforms such as Amazon Web Services (AWS), Google Cloud Platform (CGP), and Microsoft Azure.
robotics. A background in robotics is required to tackle automating processes or creating autonomous robots. And in fact, robots are doing more and more jobs in town.
Soft skills for working in AI
- Critical Thinking: Analyzing information objectively and questioning assumptions is essential to working with artificial intelligence.
- Good communication: Ideas and solutions should be communicated very clearly. This is important because we always work in teams with people with different knowledge levels.
- Continuous learning: AI is a continuously evolving field, so you need to be someone with an insatiable thirst for knowledge.
- Ethics and Responsibility: Artificial intelligence is having a profound impact on society on many levels. That is why good AI practitioners must consider the implications of their work and ensure that it is put to good use.
- language. English is mandatory to work in the field of artificial intelligence.
How to learn artificial intelligence from scratch
If you want to learn the basics of artificial intelligence engineering, in addition to the required learning, you can also train yourself with some free courses you can find on the internet. I will suggest some very interesting ones.
Google platform for learning AI. Written exclusively in English, this very complete platform consists of various courses, documentation, visual and interactive guides to give you an overview of machine learning and artificial intelligence.
machine learning. This highly acclaimed course is taught by Andrew Ng, Stanford professor and head of Google Brain. Knowledge of basic coding and advanced mathematics (especially arithmetic and algebra) is required to take this course. It lasts about three months with English subtitles. The course is free to follow through his Coursera platform, but costs around €70 to get the certificate.
Artificial intelligence that anyone can use. Another Coursera course taught by Andrew Ng will cover general AI terminology, all things AI can do, working with AI teams, finding opportunities to apply his AI to internal problems, and more. The journey time he is 10 hours and it’s free but costs about 50 euros if you want a certificate.
Best study options and programs for working with AI
Most industry experts agree that having a strong background in mathematics or engineering is critical to entering the world of artificial intelligence. Studying at university is highly recommended as it is a good way to acquire a scientific foundation. For example, the Technical University of Madrid offers his master’s degree in AI, while the International University of Valencia also offers a specialized master’s degree.
The best way is to browse the internet to find the best colleges and schools for artificial intelligence training and decide which one is the best fit for you.
