Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization.

In this episode, we're joined by Jasleen Kaur, a graduate electrical and electronics engineer at Siemens Digital Industries, who shares her firsthand experience delivering industry‑led education through the Connected Curriculum initiative.

• How industry and academia can work together effectively through initiatives like Connected Curriculum to close the skills gap between university education and real-world engineering roles.

• The practical difference between condition monitoring and predictive maintenance, and why predictive maintenance adds real value by anticipating failures and reducing unplanned downtime.

• How AI-powered tools like Senseye (and its Copilot) help beginners and professionals alike interpret machine data, troubleshoot issues, and make informed maintenance decisions using natural language.

• What a real-world, hands-on predictive maintenance course looks like, including the use of synthetic data, staged learning over several weeks, and practical platform experience rather than theory alone.

• Why human judgment still matters in an AI-driven workplace, and how students are taught to combine critical thinking with AI insights rather than relying blindly on automated recommendations.

You can find out more about how Senseye Predictive Maintenance can reduce unplanned downtime and contribute towards improved sustainability within your manufacturing plants, by visiting: www.siemens.com/senseye-predictive-maintenance

Connect with Jasleen on LinkedIn:

https://www.linkedin.com/in/jasleen-kaur-907391268/

Previous episodes about Connected Curriculum

https://podcasts.apple.com/ca/podcast/hands-on-with-ai-bringing-senseye-to-the-classroom/id1589803102?i=1000724963690