Why Should Product Managers Understand Machine Learning?
With the ubiquity of Machine Learning techniques in solving almost any problem that uses lot of data being generated on continuous basis, it is imperative for Product Managers to have more than just basic knowledge of Machine Learning.
Below are the top reasons that come to my mind on why Product Managers should learn more about Machine Learning:
- Lots of problems will be solved using ML techniques. It will help brainstorm the solution possibilities with engineering if Product Manager can talk comfortably about possible ML approaches and can appreciate their advantages or pitfalls.
- It also helps if ML algorithm is considered not a black box that is best left to Engineering team to figure out. Product Managers are supposed to understand accuracy and error rates of a solution and weigh in when it comes to determining trade-offs acceptable.
- Product Managers being more closer to customers and market possess knowledge in terms of factors that should be considered in solving the product problems. This knowledge needs to feed into determining features that might be relevant to the problem.
That said, how do you get started?
Below are couple of courses in Coursera that I found pretty good for the beginners:
- Machine Learning Foundations: A Case Study Approach from University of Washington
- Machine Learning from Andrew Ng, Stanford University