Teaching Analytics in the Age of AI - Zoltan Toth

Privacy and the AI StackBuilding the right data infrastructure before you find product-market fit is a trap. So is delegating the thinking to AI before you understand the system it is building for you. The question AI in data engineering education must answer now is not how to teach more tools. It is how to teach students to know what is sufficient, and when to push back on AI-generated results. In this episode of our series, our guest explores how ten years of teaching at CEU has shifted his focus from courseware volume to hands-on depth, how AI has simultaneously delighted and concerned him in the classroom and what universities are getting dangerously wrong about how they try to regulate student AI use. Our host Eduardo Ariño de la Rubia is joined by Zoltan Toth, a Professor of Practice in the MSBA programme at Central European University. A data engineer and educator with twenty years of experience, he is a bestselling Udemy instructor with more than 60,000 courses sold and a board member of the Vienna Data Science Group.  THINGS WE SPOKE ABOUT- From web developer to CEU faculty: Zoltan's twenty-year journey into data engineering- Why hands-on practice outperforms courseware volume in data education- The AI hackathon moment that was both impressive and alarming- Why debugging skills are now worth more than implementation skills- What universities are getting wrong about regulating student AI use GUEST DETAILSZoltan Toth is a Professor of Practice in the MSBA programme at Central European University, where he teaches cloud computing, modern data platforms, and AI engineering. He is a bestselling Udemy instructor with more than 60,000 courses sold, a former solutions architect and instructor for Databricks, and a board member of the Vienna Data Science Group, which organises meetups for data professionals across Austria. QUOTES- "I think that there is a danger there. So if you integrate some code, you still want to understand it." - Zoltan Toth- "What we should meditate on is what is the kind of work that we delegate to AI, and what is the kind of work where we need to accept the cognitive pain of going through thinking and solving and just sweating it through." - Zoltan Toth- "What we need instead is to give students a great mental model about how everything is built, so that they can take a look at the problems from an architectural point of view." - Zoltan Toth- "We should embrace that we need to suffer through a few problems if we want to understand those problems." - Zoltan Toth- "I think we are underestimating how much AI our students use, and we are overestimating our power, how much we can regulate how much AI students should use." - Zoltan Toth KEYWORDS #DataEngineering #AIEducation #TeachingAnalytics #DebuggingSkills #HigherEducation