AI Foundation

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Estimated time20-24 hours
Next stepsData Driven Growth

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.

Note that we have added some elements that we believe are essential to learn and apply AI to the BCS syllabus. This is highlighted in the Materials section (e.g. Importance of data, Big Data, Building a model and Managing Data for AI). The BCS exam does not cover these additions.

Version History:

  • Version 2.0 – Updates being incorporated on the basis of feedback (During Jan/Feb 2023):
    • Indication of Mandatory or Optional versus syllabus (in each lesson)
    • Rationalisation of modules to reduce overal time commitment
    • Enable EN/NL Captions, chapters and accelerated playback in videos
    • Enable auto-translate to non EN language starting with NL
    • Add module(s) on recent developments (Open AI, ChatGTP)
  • Version 1.0 – Original version launched in October 2020


EXIN BCS Accreditation Documents and Course Guidelines

Suggested Reading

  • Human + Machine - Reimagining Work in the Age of AI
    Paul R. Daugherty and H. James Wilson,
    Harvard Business Review Press Publication Date: 2018
    ISBN: 1633693869.
  • Ethics Guidelines for Trustworthy AI - download
    High-Level Expert Group on Artificial Intelligence, 2019
  • The Fourth Industrial Revolution - download
    Klaus Schwab, World Economic Forum, 2016
  • Artificial Intelligence, A Modern Approach (3rd edition)
    Stuart Russell and Peter Norvig,  2016
    ISBN 10: 1292153962
  • Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
    Aurélien Géron, O’Reilly 2017
    ISBN 1491962291

Course Content

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Introduction - Applications of AI and their benefits
Data, Robots and Artificial Intelligence
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Predictions, Algorithms, Machine and Deep Learning
Building and Assessing an AI Application
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Managing Data for AI
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Ethics, Risks and Human Centric Purpose
Human and Machine Coexistence
The Future Developments of AI
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