Teaching Artificial Intelligence with MATLAB

Date Time
4 Nov 2020
9:00 AM EST


Artificial Intelligence is a megatrend which is expanding in almost every sector, from automotive industry, to biomedical engineering, and event food science and manufacturing. Given this important and fast evolving trend, educational institutions see more and more need to incorporate Artificial Intelligence into their curricula.

With domain-specific toolboxes and apps, MATLAB makes it easy for educators to include AI into their courses. The instructors can benefit from a wide range of tools which allow them to design domain-specific tasks and activities involving all steps of the AI workflow and provide a hands-on experience to their students.

Using MATLAB, students have a steeper learning curve by interactively applying the theory into practical tasks, in particularly those with no programming background. Advanced students can programmatically develop customised models. MATLAB supports interoperability with open source deep learning frameworks, enabling students to apply TensorFlow, PyTorch, and other popular frameworks in their MATLAB AI projects.


In this webinar, you will explore:

  • How MathWorks tools can empower instructors and educators to incorporate AI into the syllabus
  • Ideas and examples of foundational concepts of AI in different domains
  • Interactive tools to create a hands-on experience for students, particularly for online teaching
  • How to teach domain experts, including ones with limited programming experience, to develop AI systems

Who should attend?

This webinar is aimed at all academic staff and instructors who are involved into teaching and who are interested in incorporating Artificial Intelligence into their curriculum.

About the Presenter

Dr Julia Hoerner is the EMEA Deep Learning Academic Liaison Manager at MathWorks in Cambridge/UK. She supports academics in European universities in implementing Deep Learning into the curriculum and provides general support in projects and research related to AI and in particularly, Deep Learning.

Julia holds a PhD degree in renewable energy and worked as a researcher at multiple universities in UK on applying AI to energy forecasts.

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