Artificial intelligence is no longer just a concept for the future. Over the next decade, this technology, along with 5G, will lead a significant revolution with far-reaching impacts on society, the economy, and industry.
What are the reasons for studying artificial intelligence?
The demand for professionals with expertise in artificial intelligence is increasing due to industrial sectors like process automation, the emerging metaverse, and artificial intelligence gaining more significance, especially after the pandemic. According to Job Market Insights, a tool provided by Infojobs, job offers related to artificial intelligence have gone up by 31% in 2022 compared to the previous year.
If you’re interested in pursuing a career in artificial intelligence, you might be wondering which areas to focus on. In this article, we’ll provide some useful information to help you out, just as we did in our previous feature on working in cybersecurity. We’ll assume that you’re already familiar with the basics of artificial intelligence, so we’ll dive right in.
What are the required skills for working in the field of AI?
To work in AI, there are two types of skills required: Hard Skills and Soft Skills.
To work in the field of AI, you will need to have strong hard skills.
To develop artificial intelligence programs, knowledge of various programming languages is necessary. For instance, Python is utilized for machine learning and NLP comprehension, C++ for complex code creation utilizing its libraries, and Java is an object-oriented language that uses a virtual machine to enable the developed programs to run on different platforms.
Mathematics. To develop Machine Learning models, it’s crucial to have a basic understanding of Linear Algebra, Calculus, and Algorithms. Additionally, you should also have a beginner-level understanding of Probability Theory, Statistics, and Mathematical Optimization.
Machine Learning. Machine Learning is a crucial part of artificial intelligence. It enables computers to learn from data and enhance their ability to make decisions or predictions based on that data. For instance, image recognition is an example of Machine Learning. The machine is given a set of images labeled as either ‘chair’ or ‘table’, and it learns how to differentiate between the two and identify them. Netflix uses Machine Learning algorithms to analyze users’ viewing habits, and based on that data, suggests similar content as recommendations.
Natural Language Processing (NLP). To work on projects like ChatGPT or other chatbots used in customer service, you must possess natural language processing skills.
Big Data. You should have familiarity with Big Data technologies such as Hadoop, Spark, NoSQL databases, and distributed databases (DBD).
Cloud Computing. To work in artificial intelligence, it is recommended that you possess knowledge and experience working with Cloud Computing and platforms like Amazon Web Services (AWS), Google Cloud Platform (CGP), or Microsoft Azure.
Robotics. To work on process automation and the creation of autonomous robots, it is necessary to have a background in robotics. It is also true that robots are increasingly performing various types of jobs.
To effectively work in AI, it is important to possess soft skills. Here are some suggested soft skills for working in AI:
- To work in artificial intelligence, it is crucial to engage in critical thinking, which involves objectively analyzing information and questioning assumptions.
- Clear communication is essential for effective teamwork, as it ensures that ideas and solutions are understood by everyone, regardless of their level of knowledge.
- To succeed in the field of AI, it’s important to have a strong desire for learning since the field is always changing and advancing.
- Artificial intelligence is significantly affecting society, and therefore, ethical and responsible AI practitioners must thoroughly ponder over the impact of their work and ensure that it is utilized positively.
- To work in artificial intelligence, it is necessary to have proficiency in the English language.
What is the best way to start learning artificial intelligence from the basics?
To supplement your required studies in Artificial Intelligence Engineering, you can explore free online courses available on the Internet to learn the basics. We recommend a few interesting options.
The Google Platform for Learning AI is a comprehensive platform that offers various courses, documentation, and visual and interactive guides for Machine Learning and artificial intelligence. It is only available in English.
The Machine Learning course, taught by renowned professor Andrew Ng from Stanford University and head of Google Brain, is highly regarded. To enroll, you will need a fundamental knowledge of coding and a strong grasp of arithmetic, algebra, and other mathematical concepts. The course, which includes English subtitles, runs for roughly three months and is available for free on the Coursera platform. However, obtaining the certificate will cost around 70 euros.
The Coursera course “Artificial Intelligence for Everyone,” taught by Andrew Ng, teaches you about the terminology and capabilities of AI, how to work with an AI team, and how to identify opportunities to apply AI to address issues in your company. The course is 10 hours long and is free, but getting the certificate will require a fee of around 50 euros.
What are the best study programs and options to work in the field of AI?
According to industry professionals, having a strong background in mathematics or engineering is crucial to enter the field of artificial intelligence. Pursuing higher education is highly recommended as it provides a solid scientific foundation. For instance, the Polytechnic University of Madrid and the International University of Valencia offer specialized Master’s degrees in AI.
One effective approach is to utilize the internet to search for top-rated universities and educational institutions that offer artificial intelligence training. Then, evaluate each option to determine which one is the most suitable for your needs.