Postgraduate Certificate in Machine Learning Explainability
Published on June 19, 2025
About this Podcast
HOST: Welcome to our podcast, today I'm thrilled to have Dr. Jane Smith with us, an expert in Machine Learning Explainability. Dr. Smith is here to discuss an exciting course titled 'Postgraduate Certificate in Machine Learning Explainability'. Let's dive right in! Can you tell us what drew you to this field, Dr. Smith? GUEST: Absolutely, I've always been fascinated by the power of AI, but also concerned about its transparency and ethical implications. So, I focused on making AI models more interpretable and explainable. HOST: That's interesting. Could you share some current industry trends related to this course topic? GUEST: Of course. There's a growing demand for Explainable AI (XAI) as businesses aim to build trust in AI systems. Regulatory requirements are also pushing for more transparency in AI decision-making. HOST: That sounds significant. What are some challenges faced in this field or while teaching this subject? GUEST: Balancing depth and accessibility is a challenge. We want to equip learners with advanced techniques like LIME, SHAP, and counterfactual explanations, but also ensure the content is digestible for non-experts. HOST: I can imagine. Looking to the future, where do you see the field of Machine Learning Explainability heading? GUEST: I believe it will become a standard requirement across industries, as AI systems become more pervasive. This course is designed to prepare professionals for that shift. HOST: Fascinating insights, Dr. Smith. Thank you for joining us today and sharing your expertise on the 'Postgraduate Certificate in Machine Learning Explainability'. It's clear this course can enhance career prospects and empower professionals to navigate the complex world of AI with confidence and responsibility. GUEST: My pleasure. Thanks for having me!
