10/08/2026
There were two kinds of students I observed during my days in secondary school.
The first group were students who read their notes and textbooks to understand the topics that had been taught before attempting to answer past questions.
The second group did not take the time to read through their notes. Instead, they went straight to the past questions and used their notes mainly to find answers to those questions.
So, what is the difference between these two groups?
If students in the second group unfortunately encounter questions they did not prepare for, that could be the end of the road for them. If the questions are also framed differently from what they have previously seen, they may struggle to answer them.
And this is exactly how I have observed many students and professionals using AI.
Many people want to learn data analysis but assume that AI can do everything for them. As a result, they believe they do not need to develop any fundamental knowledge of statistics and data analysis.
Whenever they encounter a data problem, they simply give it to AI and expect it to tell them everything.
Certainly, AI can read your data, suggest statistical tests and diagnostic procedures, and even write R or Python code for you to run your analyses.
But from my experience, you will do far better when you have a solid understanding of the subject and use AI to help you advance and build on what you already know.
You need to spend time developing important competencies, especially if you want to become genuinely competent in data analysis.
Understand this: software knowledge is different from statistical knowledge.
Yes, AI can generate results for you and even run much of your analysis. But the critical question is:
“Would you understand what you are reading from the AI?”
This is why we designed this course for you.
We do not simply teach you software or show you how to use AI to solve your data problems. We teach you the fundamentals of data analysis and help you understand why you should choose statistical method A based on the characteristics of your data rather than method B.
Once you have that knowledge, AI becomes a powerful assistant rather than a substitute for your understanding.
You will know exactly what to ask it, what to expect from it, and, most importantly, how to evaluate whether the results it gives you make sense.
Join our upcoming Data Analysis Using STATA and AI course and learn how to combine statistical knowledge, software skills, and AI to become a more confident data analyst.
See less
