Skip to main content
5 answers
5
Updated 1099 views

Is a MS/MCS degree necessary to work in machine learning engineering

I've seen that quite a few #machine-learning job listings prefer or require graduate degrees. How important is it to get a graduate degree if I want to work in this field? Also, does the professional Master of Computer Science (MCS) degree give me as much of a competitive advantage as MS in computer science? #tech #computer-science #data-science

+25 Karma if successful
From: You
To: Friend
Subject: Career question for you

5

5 answers


0
Updated
Share a link to this answer
Share a link to this answer

Ben’s Answer

J.F. - good question. It's great that you're thinking ahead and looking at job descriptions online now. I would use what you're finding as the best answer to your question: if 75% of the programming positions you're interested in actually require (or even prefer) Master's, then that should tell you exactly how important it is by qualifying you for that many jobs!


From a compensation and career trajectory standpoint, I would strongly recommend at least finding a reputable 1-yr Master's program even though it's not "necessary". Not only will you give yourself an advantage over competing candidates when you apply for jobs, but you'll have a better opportunity to build a more diverse coding repository for your resume, and you'll be more effective when you start coding professionally.


As for the MCS vs. MS, I can't speak to how much that matters but my sense is that most positions you're looking at would be OK with either. I'd imagine that by the time you're applying for your 2nd job, whenever that is, your professional experience will matter more to whomever is reviewing your resume anyway. Though, when applying for Master's programs you might want to look at the alumni of the different programs and see if there is a trend among them that helps you identify your ideal path.

0
0
Updated
Share a link to this answer
Share a link to this answer

Zachary’s Answer

The short answer is that you absolutely do not need a MS/MCS degree to work in machine learning! There are a lot of great free resources available that can prepare you for a data science role. I would recommend completing some projects, as that will give you hands on experience with data science tasks as well as provide you with examples of previous data science work when it comes time to interview. A great resource to learn about machine learning and compete in machine learning competitions is Kaggle.

While a master's degree is not required to get into machine learning, I would say that there are some advantages to getting one. For instance, there are going to be some companies that will require a master's degree, and so not having one may reduce the number of potential employers. I would expect that this would become less of an issue for an individual as their years of experience increase. If you did want to pursue a master's degree, one recommendation would be to look for a job that would help prepare you for machine learning (ex. data analyst) at a company where your employer will have some form of tuition assistance. This has the advantage of being able to develop the skills required for machine learning in your day to day job while having a reduced master's tuition cost.
0
0
Updated
Share a link to this answer
Share a link to this answer

Vinay’s Answer

I have a slightly different experience that I'd like to share with you - I got a MS in Computer Science and most of my batch specialized in Machine Learning since its a super popular skill right now. However, majority of them ended up in a general software engineering role and did not end up working on Machine Learning. While a lot of people will recommend having a MS or a PhD degree, it won't necessarily guarantee you a job in this domain even if you specialized in it.

An alternate strategy that I have seen a lot of people use is to move into Machine Learning at their existing jobs. A lot of companies these days require to do some kind of Machine Learning and they are usually more than happy to support engineers who are keen to take on new roles in the company. That might be an interesting strategy that you could potentially explore.

Vinay recommends the following next steps:

Explore the possibility of moving into a Machine Learning role in your existing job or starting as a general software engineer in a company and then moving into a ML specific role after spending some time in the company
0
0
Updated
Share a link to this answer
Share a link to this answer

Ej’s Answer

While a Masters or even doctorate is not normally required to work in software development like Artificial Intelligence (AI) or Machine Learning (ML), any additional Certifications and Educational Degrees that you obtain will make you more competitive in the job market in general. There are many nondegree training programs and certifications that will prepare you for a career in software development.

Ej recommends the following next steps:

Investigate online resources for training courses in your area of interest
0
0
Updated
Share a link to this answer
Share a link to this answer

Luis’s Answer

It is not. It is helpful for sure as most studies, as academic experience is. However far more important in my experience are the projects you have been part, the code you have written, a good repo is always welcome. Some hiring managers and hr people will have valid reasons to hire only Ph.D' or masters, however as a whole the industry is looking for people that know how to do stuff, understand how it works and go and do it.


Than being said, it is highly advisable that:

  • You have good foundations on coding, be proficient (good) in at least one proficient in one programming language, feel at ease using it. You don't get to say I would Google it when you are writing a for loop, we all use Google as our API to Stackoverflow, but the simpler your queries the more evident you don't know your stuff.
  • Understand how machine learning works, you don't get to say you know machine learning because you have plugged a dataset to the sklearn API. You need to understand the data, the algorithm, the metrics, the validations, runtimes, big O and memory concerns, all them are important.


So no, it is not necessary as long as you know what you are doing and can prove (show) it.

0