Thanks for questions. Almost all of our students have prior knowledge of university-level mathematics or did some coding, data courses on the internet. Of course, we have several students without such knowledge; nevertheless, they are fast learners. We test this in our admissions and in the very first month of learning in Turing College. If students are performing poorly, we terminate their contracts. In this way, we keep only motivated and determined students in Turing College and ensure that they would get a decent market salary. From the employers' perspective - just a few entry data science positions require independently "recreate some paper that uses advanced stats." Our students become a part of established data science teams, where some do more data analysis while others data engineering. As well as our base curriculum is more generic, our students get concrete, hands-on skills relevant specifically for hiring partners in specialization modules, which companies themselves create. When students finish these modules, they have a strong understanding of the company's business problem and tech stack, which is a competitive advantage over other candidates.

The thing with data science that it is a pretty new field, and data scientist tasks differ from company to company. Partnerships with companies help us understand the maturity of data science in every company and prepare students accordingly.