Module 1 – Historical context

A summary of the various industrial revolutions to date, with examples from various industries, specifically highlighting their key technological and knowledge elements, and their social and economic implications.

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Module 3 – Big Data

The evolution of cloud architectures, and of industrial data-driven decision making. We will cover subjects ranging from hypothesis-driven queries to opportunistic data analytics, while dealing with issues such as data inhomogeneity, poor labeling and the curse of dimensionality.

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Module 4 – Communications

The .com bust gave us cheap global communications that became the backbone of today’s “free” Internet. This was complemented by the explosion of universal mobile technologies, and new communication opportunities, such as 5G, with deep industrial implications.

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Module 5 – AI and Machine Learning

This will be presented as a natural evolution at the convergence of efficient computing, cheap storage and abundance of data. We will go through a primer of the most important concepts, and we will focus on industrial application examples in design, control, diagnosis and supply chain management.

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Module 6 – Industry 4.0

How all of the above come together to revolutionize the art of production. In this module we will go deeper into the platform technology paradigm and explain its impact on the various production chains. We will touch subjects including global (and even virtual) supply chains, and we discuss more detailed examples drawn from today’s semiconductor…

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Module 7 – The Future

The impact of DT in Health, Sustainability, the Future of Work and the future of workplace Diversity. We will also discuss how upcoming, disruptive IT approaches may lead to future transformations.

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