If you’re reading this, you’ve probably been asking yourself:

“How do I become an artificial intelligence specialist?”
“How long does it take to become an AI specialist?”
“Is a career in AI worth it?”
Well, you’re in luck because we can help you answer those questions and get a better idea of what to expect below. So let’s start at the beginning.

What is Artificial Intelligence

## And How Does AI Work?

It started in 1966 as Shakey: the first robot able to do things with purpose rather than just following instructions. The things Shakey could do were limited. It could turn lights on/off and push boxes around.

Artificial intelligence allows computers to mimic human intelligence and has empowered them with decision-making, reasoning and perception. And this newly developed capability to learn, plan and solve problems means computers can now quickly solve human tasks, thus freeing up more of our time.

What is artificial intelligence used for today? Well, in recent years, artificial intelligence technology has become present almost everywhere in our tech products. Think search engine query suggestions, image recognition and chatbots — you’ve even got smart compose for emails lately that suggests full phrases.

AI research has included applications in machine-assistant content creation, assisted communication and personalised learning helpers. With all the developments in text and speech recognition, AI is now in your pocket, smart speakers and smart home appliances. Even Shakey’s technologies like “bump detectors” and range finders can be found in today’s robot vacuum cleaners.
And with the massive amounts of data being collected all over the world, AI is getting smarter, more capable and more widely adopted. In fact, the AI market worldwide was valued at €91 billion last year. With new developments in autonomous transportation, medicine and even entertainment, the need for AI specialists is skyrocketing.

Working as an AI specialist

## Artificial Intelligence Career Paths

The Science of AI is made up of three major fields of expertise that deal with everything from machine learning to robotics. Yet there is one constant that links every artificial intelligence career path: data.

This is still very much an emerging field of work. The definitions and job titles can change dramatically depending on company size and the industry, but here’s a closer look at the fundamentals:

### AI Data Scientist

The job is to build theoretical learning models in a programming environment which prepare a neural network to solve real-life problems. AI data scientists interpret data. They use statistical models and machine learning techniques to measure and improve the intelligence of a certain network. They also use analytical methods to identify trends and patterns for the AI to correlate within the data they feed it.

### Machine Learning Engineer

Similar to the data scientist, a machine learning engineer handles large amounts of data. However, machine learning engineers focus on creating and managing AI systems and predictive models. Machine learning engineers and data scientists will work in close collaboration with each other — and both require sufficient data management skills.

### Big Data Engineer

Responsible for interpreting and correlating large sets of statistical data, the big data engineer does it all. From finding relevant patterns to quickly sort through huge databases to performing deep data mining searches. The big data engineer also analyses forecasting data and builds predictive models for future information gathering and interpretation.

### Computer Vision Researcher

As a Computer Vision Researcher, you advance the field by teaching machines to interpret visual data. Your work involves image analysis, object recognition, and scene understanding, impacting areas from autonomous vehicles to healthcare diagnostics.

### Developer - AI for Automotive

In AI for Automotive, you design, implement, and optimize AI solutions, enhancing vehicle safety and automation. This role shapes the future of transportation through AI integration.

### AI FinTech Developer

As an AI FinTech Developer, you create AI-driven solutions for tasks like risk assessment and fraud detection, revolutionizing financial services for increased efficiency and security. Your work shapes the future of banking and investment.

### AI Engineer

AI engineers are responsible for designing, developing, and optimizing artificial intelligence systems. They create innovative solutions, implement machine learning algorithms, and work on projects ranging from computer vision applications to enhancing automotive safety with AI. Their tasks involve data management, neural network design, and pushing the boundaries of AI to solve complex real-world problems, making them crucial contributors to the future of technology and automation.

Where your career in artificial intelligence will take you depends solely upon you. Given how quickly technology develops, you’ll have ample opportunity to keep adding to your digital skill set. But if you’re looking for a guide on how to become an AI specialist, there’s none better than your own curiosity.

The field of AI has been one of the fastest growing and best paid for the last half-decade. According to LinkedIn, data science is one of the most in-demand jobs in Europe, and Forbes named it the best job in America for the last five years in a row.

It’s clear we’re headed towards an AI-heavy future as every single device we use is getting smarter. The demand for AI specialists is currently so high that there simply aren’t enough people to fill the roles. In fact, Glassdoor says demand rose by 70% compared to 2021. You can be certain that the field of AI has room for you.

Talent and intelligence aren’t fixed traits people are born with. They can be your starting block if you see them through the right lens. All it really takes is hard work and perseverance to learn anything. Whether it’s machine learning algorithms or neural language processing, curiosity and courage can see you through.

Naturally, certain educational backgrounds can give you an initial advantage. And having experience in maths and computer science can certainly make the transition smoother.

But this isn’t necessarily a roadblock for everyone else. Many people with business, artistic and mechanical engineering backgrounds have made this jump — because there really isn’t a strict formula for how to work in AI. The idea is to teach computers to mimic human intelligence.

Therefore, how to work in AI and how to approach this challenge are up to you. Your skill set, however seemingly unrelated, can potentially be invaluable in the process of teaching AI how to think like a human. Artists are also certainly welcome in this new and exciting scientific field.

To become good at something, you have to be willing to be bad at it at first. Building your career in AI takes math skills, programming and an understanding of how to use data. However, if you’re willing to stick with it, you’ll be able to carve your own artificial intelligence career paths.

AI is still in its infancy and you could be an early adopter — a trailblazer in a scientific field that offers huge possibilities for career advancement, impressive salaries and job security. Few careers allow you to bring your skillset to nearly any industry.

Now, if you’re still uncertain if a career in AI is the right choice but you’d like to give it a shot, you have options. At IU, we’re offering a 4-week free trial for our AI study programmes. Just contact one of our for more details on how to get started

Your AI Career Roadmap

If your goal is to figure out how to work in artificial intelligence, there are a few steps you should be aware of before setting off.

How to Get Started

### How Do I Start a Career in AI?

If you've ever wondered how to learn AI, you're in the right place. Before delving into the intricacies of AI, let's begin at the very beginning. From understanding the basics to diving into the complexities, this section will guide you through the foundational knowledge and skills you'll need to pave your way into the world of artificial intelligence. Whether you come from a technical background or not, the journey starts with curiosity and a willingness to learn. So, let's explore the fundamentals and set the stage for your AI career path.

### The Fundamentals, from Basic to Complex

If your background involved statistics and computer science, you’ll have a head start. If not, you’ll need to brush up on your matrices, linear algebra and calculus. Knowledge of statistics and probability is a must because you’ll be working with relational and non-relational databases. And you’re only getting started.

You’ll also have to learn the basics of Python: expressions, variables, data structures, functions and packages such as pip. Next, you’ll need to learn some important data-handling libraries such as pandas, NumPy and Matplotlib. And then you’ll have to get your hands dirty with Virtual Environments effectively.

But there’s no need to get discouraged — you didn’t learn your current skill set overnight either. Therefore, rather than looking at it as one giant hurdle, recognise that you can approach it granularly.

### Hit the Books — Learn Online or On Campus

Before you figure out which of the three major AI career paths tickles your interest, you’ll first have to learn how to process data. This is the biggest step in figuring out your path and it involves:

- Principal component analysis

- Dimensionality reduction

- Normalisation

- Data scrubbing and handling missing values

- Unbiased estimators

- Features extraction

- Denoising and sampling

From here, you have your three directions: Machine Learning, Data Scientist, and Data Engineer. And you could learn all of this stuff by yourself. You can find some courses, books and a lot of content out there to get your career in AI started.
This may all seem like a tall order — and it is! However, if you’ve gotten your feet wet a little and you really want to learn how to work in artificial intelligence, you can. If you want to learn more about how AI compares to Data Science, check out our article on AI vs. Data Science.

Discover more about our AI degrees:

- BSc Computer Science with a specialisation in Applied Artificial Intelligence

- MSc Computer Science with a specialisation in Artificial Intelligence.

- MBA with a specialisation in Artificial Intelligence

### What Is the Best Degree for AI?

If you're determined to make your mark in the field of artificial intelligence and seek a structured path to success, pursuing a degree in AI can be a game-changer. At IU, we offer both Bachelor's and Master's degrees tailored to the diverse facets of AI.

Acquiring a recognized degree in artificial intelligence is an investment in your future, providing a solid foundation and invaluable practical experience that can significantly accelerate your career in this high-demand industry. So, if you're eager to shape the future of AI and explore the boundless opportunities it presents, considering a degree in AI might be the pivotal step toward your dream career.

### How to Become an Artificial Intelligence Expert

They say experience is the best teacher. What they don’t’ tell you is that the most data-rich point in any scientific endeavour is failure. And that’s why you should always be as hands-on as possible. When it comes to science or learning, failure is a primordial step that cannot and should not be avoided.
But you can’t fail if you don’t try stuff. You can’t see what works and what doesn’t if you don’t play around with the programming yourself.

So don’t wait until you graduate to start working on your own projects. It’s only by trying to implement what you learn that you figure out where you went wrong. Failure can be frustrating, but if you shift your perspective, failure — and the process of learning — can be one of the most rewarding parts of your day.

### Get That Paper

How to get an AI certification might not be a question you want to bother answering. And if you can prove that you can do the work, getting a job in the industry won’t be too difficult.
However, it’s hard to deny that a degree in artificial intelligence looks good on a résumé. It shows potential employers that you’ve got a firm grasp of the basics and that you’re ready to start. Getting certified could also fast-track your career because all the practical experience you get results in projects you can create a portfolio with.

So how long does it take to become an AI specialist? It can take considerably more without a well-structured learning programme.

### Make Networking Part of the Programme

While demand for AI specialists far exceeds the number of people in the field, your success necessitates some creativity. Sure, your degree and project portfolio will do a lot of the talk, you’ll still have to walk the walk yourself. And in order to be noticed, you’ll first need to build your crowd.

If you’re like most people, you probably don’t have a lot of AI specialists in your circles. And this is where online platforms come in handy.

You can search for people who work in AI on LinkedIn. Don't feel awkward about just adding them to your network out of the blue — people with similar interests tend to support each other.

From here on out it's all about being active in your community — make posts about your questions on AI, comment on other people's posts and don't forget to smash that like button!

Success is always built with people. You'll learn a lot faster too if you put yourself out there and ask for feedback on your projects. You never know, you might just impress the right person and land an internship!

### Career Prospects — Application of AI

How does artificial intelligence work to make life better and what does the future hold?
We’re not quite ready to bring Ultron or Vision into the world, but as with all technology, advancements are exponential. It didn’t take long to go from rudimentary lane-keeping assistance to self-driving cars. And that technology is now speeding up our agriculture with drones and self-driving tractors.

As AI is one of the fastest growing and best-paid sectors today. And you’ll need to keep developing your digital skill set to move your career forward. But on the flip side, your curiosities and passions can lead you to create technologies nobody ever dreamt of — tech that everyone might start using in the next 10 years.

AI is being deployed in virtually every sector — finance, infrastructure, naval engineering — you name it. It’s been helping doctors with imaging and drug discovery. Schools have been using AI to grade tests. There are even smart-sewer projects being developed to avoid flooding disasters. It’s this versatility that makes AI one of the best degree programmes for working adults.

Your future in AI really depends on how you choose to follow your curiosity. If you stay open and never stop learning new things, you cannot become obsolete — you may even scoop up a Master’s in Computer Science with AI. Once you’re ready, you can step up with an MBA degree and take the lead in a managerial role.

### Is AI a Good Career?

Now you know what a career in AI looks like, you know the artificial intelligence career paths and you understand how AI works. You’ve got a roadmap and know how you can start your career in artificial intelligence. Excited?

Is a career in AI worth it? Here’s a quick summary of why you should be looking forward to making this decision and sticking with it.

### It’s Future Proof

Simply put, this is the bleeding edge of computer science. For some, this technology will make their jobs a thing of the past. And, as with any situation, your perspective gives meaning to it. Some will choose to see this as a bad thing, to think that AI is their enemy.
But you can choose to see AI as an opportunity to free up more of your time so you can do less tedious and more interesting things. There’s no denying that intelligent machines are changing everything and creating countless job opportunities worldwide. You can be part of that change.

### Great Pay

We've already spoken at length about the market's demand for AI specialists. Data runs everything today. Thus, AI specialists have a direct impact on decisions and the way companies are managed.
Because AI is seeing eye-watering adoption speed in pretty much every industry sector, salaries are pretty impressive too.
In fact, the average pay for an AI specialist is around €100.000 per year. And if you're highly qualified and have a lot of experience under your belt, you can expect to make well above €250.000.

### Never Stop Learning

Countless opportunities and abundant income are staples of AI work. But what does the work really look like? Well, it’s as mundane or as exciting as you’re willing to make it.
AI’s been at the forefront of medical advancement — from mapping the human genome to the fight against COVID and revolutionising medical imaging analysis — and it’s directly changing outcomes. In Japan, there are already home robots that help the elderly with their daily tasks.
There isn’t any other limit to AI applications. How AI will change our cities and home appliances, and how it will free up more of our time hinges on your imagination as a specialist. And if you keep learning, it will to.

FAQs

## Career in AI

Companies are using AI for customer service, spam filtering, cyber security and fraud detection. Artificial intelligence is changing infrastructure and industry in more ways than we can count.

Machine learning engineers give machines the ability to learn and perform tasks as humans do. Artificial intelligence revolutionised assembly lines, manages inventories and fights disinformation. And the AI specialist is at the heart of all of it.

You could go it alone and learn all about a career in AI by yourself. How to get an AI certification might not be a question you want to bother answering. And if you can prove that you can do the work, getting a job in the industry won’t be too difficult.
However, it’s hard to deny that a degree in artificial intelligence looks good on a résumé. It shows potential employers that you’ve got a firm grasp of the basics and that you’re ready to start. Getting certified could also fast-track your career because all the practical experience you get results in projects you can create a portfolio with.

If your background involved statistics and computer science, you’ll have a head start. If not, you’ll need to brush up on your matrices, linear algebra and calculus. Knowledge of statistics and probability is a must because you’ll be working with relational and non-relational databases. And you’re only getting started.

You’ll also have to learn the basics of Python: expressions, variables, data structures, functions and packages such as pip. Next, you’ll need to learn some important data-handling libraries such as pandas, NumPy and Matplotlib. And then you’ll have to get your hands dirty with Virtual Environments effectively.

However, you could also dispense with the guesswork, save yourself a lot of time and use said time to get a recognised university degree. At IU, we offer both Bachelor’s and Master’s degrees in artificial intelligence.

You’re not born with a limited amount of talent or intelligence. You can always learn and grow.

So, yes, anyone can become an AI specialist. This may all seem like a tall order — and it is! However, there’s nothing to stop you from working hard and building your career in AI — even if it is from scratch.

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