'If you're not using Machine Learning already,
you should be.'

- Harvard Business Review, 2016

The most influential general-purpose technology of our era is Artificial Intelligence. With the rise of computing power and tremendous growth of data storage, the field of AI is growing exponentially. Studies predict that Artificial Intelligence will fully automate 9 (OECD) up to 47 percent (Oxford) of all jobs.

We are here to make sure you are ready.


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Provide free theoretical and management ML content

  • AI Bible

  • Test your AI skills and knowledge: Free AI Test

  • Become a certified ML implementation expert

Present hands-on business solutions and insights

  • A helpful list of AI tools for every degree

  • Readiness test®, a fast and fun way to find out if your organisation is ready for ML

Build fast, working solutions in your production environment

  • Analysis of business case and discuss requirements, features and scope 

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The field of Artificial Intelligence

Artificial Intelligence (AI) is a broad, complex field, and filled with it's own jargon and definitions. So lets first define AI. We believe that whenever a computer is able to make autonomous decisions based upon predictions derived from statistical models, it classifies as Artificial Intelligence. 

AIcompany is interested in the impact of AI on business. We have found the most important themes in AI for you in order to help you recognise and find sustainable business opportunities.

Check out our Business Solutions page for more info and hands-on tools of all degrees of difficulty.

The line between science and business is fading. AIcompany distinguishes the borders of all these existing fields.

The line between science and business is fading. AIcompany distinguishes the borders of all these existing fields.

  • Read more about the field of AI [+]

    Originating from Computer Science, Machine Learning (ML) is considered a field within AI and Data (Advanced) Analytics that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. 

    Deep Learning (DL) is a subfield of ML and is responsible for the most exciting capabilities in diverse areas like natural language processing, image recognition and robotics.

    AIcompany will test your knowledge of machine learning techniques, practical (best practice) business views, and computer science techniques that help you create new innovative solutions. Our certifications will help you set that next step in your career.


See how AI innovates your industry
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4 Emerging trends will transform the field of artificial intelligence in 2018

Nowadays we see that technology alone is rarely enough to unlock sustainable business growth. When a new technology is combined with a ‘new way of doing business’, true value is created. Through our work and research, we have identified five emerging trends in artificial intelligence for 2018. Executives should learn to shape the outcome rather than just react to it.

  • Read about the 4 trends [+]

    1. Artificial Intelligence seen as commodity
    In recent years, many tech giants (Google, Microsoft Azure, IBM) invested heavily in the general-use of Machine Learning and Deep Learning. In 2018, more SME businesses will learn how to use their solutions and full service platforms. They have managed to optimize Computer Vision and Natural Language Processing in such a way that it will most likely outperform any other (smaller) player in this field. With help of API’s they will take over (market share up to 85%) the general-use machine learning industry in 2018.

    2. Democratisation of ‘Click’ Machine Learning
    In 2017 there has been an exponential use of so called ‘click – drag and drop’ tools. Usually highly specialised solutions are able to generate business value without any interference of writing code. It also has a great looks & feel and is very visualized.

    These tools allow users to model a solution without writing code (such as Orange, Dataiku, Exploratory). The threshold to start having fun with machine learning just decreased…

    3. “Guys, these geeks are infiltrating...”
    Many organisations started in 2015 and 2016 so called ‘AI labs’ and ‘Advanced Analytics’ teams. These teams used to operate in a highly centralised set up in order to ensure that they could learn from each other and operate across different departments. However, organisations learned that the actual best practice is to embed data scientists and analytic team members within individual business units.

    4. Predictive Analytics on the loose
    As mentioned, many organisations invested heavily in new ways to apply advanced analytics and predict certain outcomes. In 2018 we will see more and more autonomous agents that will use the outcomes of these predictive analytics tools to plan and interact directly with customers.

    In simple terms, The data and tools now available will not just convince someone to do something, but will actually do it themselves! Two examples,
    A) Customer data is used to identify which customers are most likely to unsubscribe and will be instantly offered personalised deals in order to keep them.
    B) Products that are connected to the internet, such as tires in the future, will not only provide the car and garage with information on their wear and tear, but also make and set appointments for maintenance and replacement.

AI Practice Exam

We've selected 15 practice questions for you to train for the Machine Learning Essentials . Check out our open assessment to test your knowledge for free!

Study Material

Download the Bible for free and expand your knowledge in the field of Machine Learning. Learn the essentials of ML and the managerial skills and frameworks to implement ML into businesses.

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Want help with implementation or fast advise on your AI solutions? We are here to help. Please do not hesitate to ask, our first conversation is free of charge!