Data science is one of the most demanded jobs nowadays and Big Data is becoming increasingly more important with time. As time goes by, more businesses are realising the importance and the potential impact that collecting and analysing customer data can have on their organizations. Thus, even without any knowledge or background in the Data Science world, I thought it would be very useful for my future. I also learned that Python is the most useful tool I could learn to get me closer to this goal. Python is the most used programming language by data scientists as it makes their lives easier with comprehensive libraries that help with tackling mathematical tasks, data manipulation, statistical visualization, and more. As a result, I was determined to learn and unlock all its potential when it comes to data science.
Nevertheless, during the learning process, I realised that what I enjoyed the most was analyzing data and not spending hours figuring out which lines of code I should write in order to obtain what I wanted. Even though there are many existing environments like Stack Overflow, I still found a bit daunting and tiring the process of having to go through the answers of other people. However, with the appearance of generative AI and specifically ChatGPT, my experience with using Python for Data Science turned way more pleasant. ChatGPT has allowed me to beat the ‘barrier’ or ‘hassle’ of having to memorize a bunch of code, which was to some point discouraging.
What you see below is a request I made to Chat GPT during my bachelor thesis. Even though this is a relatively simple piece of code, I have also used it for bigger tasks. The main point I want to make here is that I learned that I no longer necessarily need to know and memorize how to do a specific task, but it is sometimes it is sufficient to know what can be done with a tool like Python so that you can correctly ask a GAI tool like Chat GPT. What would take me 40 min to 1 hour, now would only take me 2 min to complete. It is important to clarify that I don’t mean that data scientists are no longer needed and that we can already rely 100% on GAI tools like ChatGPT. I rather mean that these tools are facilitating many of the tasks that data scientists have to do, making everything more efficient.
I relate a lot of my personal experience to that of Michael Wang, a data scientist who wrote about The Rise of ChatGPT. In his blog, he describes how the existence of AI might make data scientists become extinct. However, Michael clarifies that he does not mean that humans doing data science will become obsolete, but rather that “the data scientists of the future won’t be called data scientists, they will go by names like product managers, marketing specialists, or investment analysts.”
Bibliography:
- https://www.codewars.com/post/7-resources-to-level-up-with-python-for-data-science
- https://www.kdnuggets.com/2023/06/data-scientists-still-needed-age-generative-ai.html
