With the severe shortage of people with analytics and machine learning skills it has become critical for organizations to think and plan for upskilling and reskilling of their workforce. According to a recent report by Gartner, the greatest opportunity in machine learning is through upskilling (Leading Upskilling Initiatives in Data Science and Machine Learning, 19 July 2019.)
People are coming to Data Science and ML from many different backgrounds. Rapid adoption of automation is impacting all kinds of jobs. All of this is resulting in pressure on people to learn and adapt new skills.
At A3 labs we see three groups of people who are well-positioned to upskill to ML:
- People with STEM background
- IT/Software professionals with data and programming knowledge
- Citizen data scientists with diverse domain knowledge and some analytics skills
Gartner defines a “citizen data scientist” as a person who creates or generates models that leverage predictive or prescriptive analytics, but whose primary job function is outside of the field of statistics and analytics.
Each group has its own strengths and weaknesses – all of which can be overcome by hardwork and effort!
Here’s a simple guide for those with some data/programming skills who want to get into ML.