AI Foundation

This learning journey is designed to prepare you to work in AI and to make decisions in relation to the application of AI in your working environment.  It is also accredited to the EXIN BCS AI Foundation level professional certification.  We don’t just help you pass the exam – we get you started in the world of AI, including understanding the concepts, opportunities and threats of AI and building and assessing your own AI models.

Discover what AI is (and is not) possible with AI and learn the basics such as Data Analysis, Robotics, Machine and Deep Learning, Algorithms and assessment of Trustworthiness.  We cover a range of application areas such numerical models, classification systems, chatbots, voice and image recognition, natural language processing and expert systems.

In this journey, we assume the participant has a basic awareness or starting knowledge of data.  The “Data Driven Business I – Foundation” is ideal for this but not mandatory.  You can follow this journey first and fill in your knowledge gaps with the data driven business journey later.

The learning objectives are:

• Acquire the competence level as defined in the EXIN BCS AI Foundation Professional Certification
• Understand why Data and Artificial Intelligence are vital capabilities for now and the future
• Apply the EU Guidelines for Human Centric, Ethical and Sustainable AI
• Explore what Data Science and Artificial Intelligence are and how they create disruptive change
• Discover Intelligent Agents and different levels of Robotics
• Learn what algorithms and machine learning are and how these are used
• Build your AI Toolbox including Auto ML and common open source software tools
• Understand how humans and machines will work together now and in the future
• Become aware of the key risks and dilemma’s and learn how to build Trustworthy AI Applications
• Learn how to get started with an application

During this course you will learn to use (free or open source) AI tools and build your first applications using provided data.  You can then proceed to build models with your own data and assess their Trustworthiness.