I can vividly remember creating my “MS in US” plan in my final year of university. GRE. TOEFL. Universities and their rankings. Statement of Purpose. Letter of recommendations from professors. Student loans.
When I started learning data science in 2017, I was made to believe I needed a Master’s degree despite finishing up a computer science undergraduate degree.
The standard plan was to either go for a software engineer role or do a Masters's abroad. Everyone I knew was doing one of these. I wanted to break into data science, so I made my mind to follow them too.
I would come back from lectures and prepare for the list of “MS in US” exams I’d have to take. I worried about the student loans but consoled myself that I’d earn it back all.
As I researched the popular master’s programs and the modules they offered, a simple fact was staring back at me.
I can learn what they teach during the master’s program, directly from them, at the comfort of my home for a fraction of the cost.
I wasn’t sure if it’ll work out, but I decided to follow my own path because going into debt was absurd when you can learn and acquire the same skills anyway. You can tell it worked out: I went from being a confused undergrad to a machine learning engineer.
Since many beginners are confused like I was and asked me the same question repeatedly, I decided to pen this article to settle the confusion once and for all. Read on. It’s time to get awe-struck.
Understand This About The Master’s Degree
“I’ve got a Master’s from a reputed university, but there are people in my team [at Google] who don’t, but perform equally good if not better. Master’s is one of the historically proven ways to demonstrate your expertise — there are other ways. As far as you can demonstrate your expertise, you’d be good.”
I was lucky enough to be mentored by a Google Engineer, and his words above gave me perspective.
Think about it. No, really, think about it.
It was never about the Master's degree. It was always about candidates demonstrating expertise and companies evaluating them.
If not Master’s, then what?
Alternative Ways to Showcase Your Expertise
It’s easy to say there are alternative paths, but it can quickly get overwhelming for beginners not knowing what to do next.
Here’s what you can follow next:
- Identify your strengths and weaknesses. If you’re coming from a different field, see how you can use your existing skills to your advantage.
- Outline what you still need to learn and focus solely on them.
- Rely on online courses from reputed universities to learn the concepts. Which courses? Which platforms? Here are the essential resources I’ve used and recommend.
- Supplement your online learning with these books.
- Apply those skills to create portfolio projects that demonstrate your expertise. Use this 21 step guide to implement your project idea.
- Share knowledge on platforms like LinkedIn. Your network can help you get opportunities.
It sounds simple, I know, but it works. You’ll not be the first to do this; many have already done it.
I understand; it’s hard to trust. There’s no way to be 100% sure unless you experience it yourself. But if you choose to look for examples in the world and talk to people already in the field, they will all tell you the same.
I want to credit Rachel Thomas, co-founder of fast.ai, who instilled the importance of blogging in my head. In my early days, she had written a fantastic guide outlining alternatives to a degree in deep learning, which inspired me. You should definitely check it out.
Gate Keepers are Dead. You Own Your Dream Career.
A couple of years back, we interviewed an applicant for a software engineering intern role. He showcased a live web application and explained to us how he structured and developed his project.
We were already on the lookout for a front-end engineer, and it turns out he had both the front-end and back-end programming skills. We gave the green light to the hiring manager, and he joined us the very next week.
Here’s the exciting part: Let alone a master's degree, he had no degree at all.
He had done some online courses and taught himself coding. Then he went on to take up some freelance projects and built himself a portfolio. And he showed us all of them in the interview. It’s that simple.
Within a year of joining our team, he was shipping computer vision projects for us. He was our MLOps guy. None of us cared if he had a degree or not, he had the skills, and we can tell.
Gone are the days where hiring managers analyze the university rankings and look for certifications to pick the best candidates. I’m not saying they don’t play a part at all because, at some places, they do. But there’s absolutely no point letting the traditional universities with humungous fees take ownership of your dream career.
If you want a Masters's — go for it. But please do it for the right reasons, not because you want to break into data science.
If I had taken the “MS in US” path, I’d only be left with student loans, visa problems, and a pandemic to deal with. I know it because I’ve seen my close friends struggle.
Nobody told me when I was in a dilemma, but I’m telling it to you now: You own your dream career. You can make it the way you want it. Really.
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