As I sat in my sophomore year production engineering classes, I couldn’t help but feel a nagging sense of uncertainty. My true passion lies in the AI/ML domain, and I’ve always dreamed of pursuing a PhD in ML from a top university in the USA, Germany, Switzerland, or elsewhere. But, I’m not studying computer science or a related field. Is it possible to make the leap from production engineering to an ML PhD?
The Concern
My undergraduate background is in Production (Industrial) Engineering, which doesn’t exactly scream ‘machine learning.’ I’m worried that my lack of direct experience in ML will hold me back from getting accepted into a PhD program.
But Here’s the Thing
While my background may not be traditional, I’ve been working hard to build a strong foundation in ML on my own. I’ve taken online courses, read research papers, and even worked on personal projects to develop my skills.
What Matters Most
It’s not about the degree you hold, but about the skills you bring to the table. If you can demonstrate a deep understanding of ML concepts, a strong work ethic, and a passion for the field, you can increase your chances of getting accepted into a PhD program.
Takeaways
- Build a strong foundation in ML: Take online courses, attend workshops, and read research papers to develop your skills.
- Gain practical experience: Work on personal projects or collaborate with others to build your portfolio.
- Network and seek guidance: Reach out to professionals in the field and ask for advice on how to increase your chances of getting accepted into a PhD program.
Final Thought
So, can you get into an ML PhD with a non-ML background? Absolutely. It may take more effort, but if you’re willing to put in the work, you can make it happen. Don’t let your undergraduate degree hold you back from pursuing your dreams.
Further reading: Machine Learning PhD programs