vevor button maker thread making machine：Amazon com ： Five career tips from women leaders in machine learning
One big perceived barrier to ML and AI is the idea that you need to be highly qualified and accredited to work in this space, with a doctorate in math or statistics.
Schulze: When I knew I wanted to get into ML/AI, I decided I would do some further study. With my background in business, I just didn’t feel like I could do a master’s in mathematics. Instead, I found a course called “Big Data and Business Analytics,” which I studied for a year. It focused on the perspective of the customer, which I loved, and this has stood me well in launching my career as a data scientist.
Pant: I meet many people who think that they have to have a Ph.D. in statistics or math to start any role in ML/AI, which is just not true. It’s a total myth that you must go through a lot of courses and get a specific degree. You can get started without this. Any ML/AI organization has typical roles like product manager, technical program manager, and data analyst, which all require domain expertise but not a deep ML/AI background.
Shubha Pant, general manager and product head at AWS
Luna: As far as skill sets are concerned, transferable skills like communication and attention to detail will take you far in this field. If you’re really interested in launching an ML career, I would build an understanding of basic frameworks such as Python, Java, or Node.js. Understanding just one of these can be very helpful. The industry sits at a cross-section of a lot of different skill sets, so design and customer experience are super valuable too.
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