The use of AI in data science brings about to the forefront of the data-driven paradigm. Before that, data was tackled primarily using statistical models which carried with them a set of assumptions that were not always valid.
The data-driven approach doesn’t have any such assumptions, making it more accurate and generally more effective, particularly when dealing with complex datasets, not following any particular distribution.
This approach to data, powered by machine learning and AI know-how, creates a new kind of role in data analytics, one that is geared more towards state-of-the-art systems. Statistics is still a useful skill to have, but it’s not as important since it is useful mainly for the data exploration stage. data science online certification All the heavy work in the data-driven paradigm is undertaken by specialized data models (usually AI ones) that require a different set of skills. However, this is not too different from the standard skill-set of a data scientist, so an AI specialist is not always the best option. Sometimes it is better to train existing employees on these new systems.
All this renders continuous education a necessity, so training courses and conferences ought to be included in the data science budget. Besides, most of the AI frameworks out there are free, so training someone to use them is usually a worthwhile investment. Get more details from data science training
