I’m in data science studies though I’ve heard demand is shifting. Should I continue or switch to computer science? Are ML engineers mainly deploying rather than developing models?
hey finn, i think data sciene is still quite valuable even if trends shift a bit. have you thought of blending cs skills to back up your work? how u balancing creative model building with practical deployment?
hey finn, data science still rocks even with evolving trends. cs knowledge adds value but ds remains in demand. sure, ml eng often deploy models, but creative dev is still key. ibelieve stick with ds and layer cs insights on the side.
hey finn, roughreadin your post. im wonderin if the creative side in data science still wins u over or if cs skills stole your interest. how d u see model creation vs deployment playing out? love hearin your thoughts on this journey.
honestly, i’d stick with data science. it’s not dying yet and you can easily pivot to ml or cs later. ml engineering is more about making models work than creating them from scratch. it’s all about learning and adapting, so follow your passion.
Based on my experience, data science still offers considerable value despite evolving market trends. The field requires a solid understanding of analytical methods and an ability to derive insights from complex datasets. Meanwhile, computer science skills enhance your programming and system design capabilities, which prove beneficial when deploying machine learning models. Although the emphasis in ML engineering might lean towards efficient deployment, innovative model development remains a critical skill. Committing to data science while augmenting your technical skills in computer science can provide a well-rounded foundation for tackling diverse challenges in the industry.