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Ever wondered how AI works and how you can start your career in AI?

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

“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.

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.

Your roadmap to a career in Artificial Intelligence

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

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. You’re learning a new set of skills and your curiosity is taking your career into new and exciting territory.

Hit the books — study online

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. 

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 which you can study completely online.

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. You can always grow and learn new things. There’s nothing to stop you from working hard and building your career in AI — even if it is from scratch. 

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

As previously stated, 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.

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. And don't forget that your reach is global.

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. 

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 AI. Once you’re ready, you can step up with an MBA degree and take the lead in a managerial role. 

Why Artificial Intelligence is a great choice

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.

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