Data science training for real projects

Data science and machine learning have become indispensable to almost every industry. While the work of DeepMind, OpenAI, and similar organisations is widely publicised, many companies still face the challenge of implementing machine learning projects.

This is hardly surprising on closer inspection, as successful ML projects require a wide range of skills, including exploratory data analysis, solid software engineering, visual communication, and software operation. In response, many companies are increasingly fragmenting job profiles, recognising not only data science and engineering, but also ML engineering and MLOps.

At Scieneers, we believe in valid specialisation based on a solid foundation of knowledge that transcends the divide between engineering and science. True collaboration and personal responsibility are necessary for successfully realizing data science projects, and this is the only way to achieve them. With our ‘Data Science for Real Projects’ training, you can select individual modules to close knowledge gaps and foster this shared team understanding.