Every Engineer Should and Can Learn Machine Learning - KDnuggets

To mark the occasion, we sat down with course designer and software engineer Sourabh Bajaj (previously Neeva, Google, Coursera) to talk about the evolution of the ML role, how he designed the course to connect with today's business needs, and how he thinks students can apply the covered topics at the end of each course! Sourabh: A few big changes that have happened in the space is that early on, ML engineers were spending a ton of time in model development. And in some sense, the ML engineer role itself didn't exist--it was more common that you could find a ML researcher role, where you would be responsible for cleaning data, productionizing your models, and building models and iterating of them. This role was primarily driven by a lack of infrastructure, where there was not great tooling for ML. And, even if the tooling existed, it was much harder to productionize these models.