AI for engineers: experience of an engineering graduate
Hi there,
I often get asked about my transition from engineering to data science. Having made the leap, I’ve learned what works (and what doesn’t) and I thought it would be of value to share my insight to hopefully save you a lot of time.
I have a Master’s degree in Engineering (Material Science) and an Engineering Doctorate. I am self-taught in data science and have been practicing it for 5 years. Whether you’re looking to:
- Transition into a data role
- Leverage data science knowledge for your engineering work
- Or learn these skills out of curiosity
…this guide is for you. It’s based on my journey and will help you navigate your transition into the world of AI and data science with confidence.
Engineers have all the tools to be great machine learning practitioners. They are problem solvers, and they tend to be practical. They can cut through the noise and leverage what already works to build a solution to a problem. Without getting bogged down trying to code a new neural network from scratch.