I am currently specializing in data-analytics and AI as part of my university education. The courses give me a comprehensive toolkit to model data and create machine learning solutions.
So far, as part of my education, I have learned development environments like Jupyter lab through Anaconda, development tools such as Pandas, as well as the different modules and tools provided by Sklearn library, with my education also covering how to utilize R, and deepening my experience with Python and SQL.
I have learnt the basics of preprocessing data, feeding the data to different models, reviewing and evaluating results, with plotting and visualization techniques used to present the results concisely. I have completed a dedicated course on preprocessing that, outside of the safety of Excel and XML sheets, also had me diving deep into SQL, JSON, APIs and Regex. On the dedicated machine learning course, I learnt different models, such as kNN, Naive Bayes, Random Forest & PCA. Additionally, I learnt how to compare the performance of different models and evaluate which is best suited for a given dataset.
I did not use generative AI when making this website. I believe that AI as technology can speed up workflows immensely. Having said that, I still believe you should understand the underlying concepts that you are working with. This portfolio website was always going to be an exercise for me to get comprehensive overview on full-stack development. That's a skill that is hard to learn. Utilizing generative AI to speed up parts of the process, when you know what can be sped up, it is easier in my opinion. Therefore, I'd rather spend my time learning what's hard and using AI tools to build on top of that solid foundation, rather than doing the opposite.