This article is intended for people who already have an undergraduate degree and are looking to switch careers to data science or who are otherwise interested in knowing the benefits of each educational option. With data science, machine learning, artificial intelligence, and deep learning emerging as popular jobs in nearly any industry, graduate programs have similarly boomed to keep up with the demand. Another option, a certificate in data science, may be more enticing for a variety of reasons, however. Below, I describe the differences between each, what to expect and the benefits of both graduate school and certification in data science.
Grad School Versus Certification
- Graduate school offers training from reputable, well-established university programs. You will be able to network with professors, classmates and industry professionals and will have the backing of a well-known institution behind your training. The downside is that these programs tend to be longer in duration, more expensive, and offer little flexibility in their curricula.
- Certifications are a more affordable option that can be completed much more quickly than a full graduate program. With so many available, however, the quality of education and prestige of each program can vary widely.
Graduate School: Pros and Cons
Graduate school can come in a variety of forms, whether a traditional, in-person experience, a fully online program or a mixture of both. This option requires more commitment from the student, but that rigor might inspire you to finish and reap the program’s many benefits.
Here are benefits of choosing graduate school for your data science education:
- You can meet your classmates in person in most programs, although even online programs offer a few in-person meetings.
- You will likely complete a complex capstone project that you can also present at summits or conferences in person, ultimately allowing you to network with reputable companies.
- They’re expensive. Although this expense is a disadvantage, as I discuss below, it also confers some advantage because you’re making a large, monetary commitment that will force you to study so you’re not wasteful.
- Graduate schools in data science offer built-in trust thanks to their affiliation with reputable universities.You can have confidence that their program structures are rigorous and accurate.
- Some companies prefer a graduate degree in data science over certifications.
Here are some disadvantages of choosing graduate school:
- It’s more expensive than most certifications.
- It also takes much longer to complete than most certifications.
- It can be overwhelming to have multiple courses per week on top of your current nine-to-five job.So, you may have to choose between working and school.
- The curriculum can sometimes lag behind data science trends.
- The programs can be too general sometimes.
- Because the schools operate on an academic calendar, sometimes you have to wait longer than you might want for the program to start..
As you can see, obtaining your data science degree from a graduate school offers many advantages. Although there are some disadvantages as well, it is ultimately up to you to decide if they outweigh the pros or not based on your circumstances.
Certification: Pros and Cons
Certification is a little tricky as a concept. It can involve obtaining many smaller certifications or just one bigger one. The program’s rigor is certified by the company that offers the certification. Numerous, reputable certifications exist out there, and they provide a great way to land a job in data science.
Here are benefits of choosing certification for your data science education:
- Certificates can be completed much more quickly than grad school, often a matter of weeks or months versus years.
- A certificate tends to be much cheaper than grad school.
- Because the programs are shorter, their curricula can change with the times. So, unlike grad schools, certification programs can quickly redesign their courses to account for trending data science packages and machine learning algorithms like CatBoost.
- More specialization is possible. For example, you can choose a certificate in only gradient-boosting algorithms. Graduate school, however, will tend to simply offer a general, holistic course on algorithms.
- They are more flexible. You can build your own program, choosing multiple certifications with courses you really enjoy.
- You can skip courses that you do not need that some graduate schools include and require like intro to SQL, intro to coding or intro to statistics. If you know these subjects already, you may be wasting a whole semester of your time.
Here are some disadvantages of choosing certifications:
- They can sometimes be less reputable than graduate schools.
- It’s hard to know if the certificate is actually teaching you the correct information. There are many more certificate programss than grad schools in data science, so it can be overwhelming to know which one to choose to enroll in to get a good education.
- Likewise, you may not know when you have reached the end of your education. In grad school, a clear endpoint signals the conclusion of your core studies. Of course, you can and should always learn more, but from your initial exposure to data science to landing a job, you have to decide for yourself when you’re ready if you go the certification route.
After writing about these relative advantages, I surprised myself with how much certification has to offer. Of course, there are still some disadvantages. Once again, ultimately, it is up to you to weigh the pros and cons of each based on what will work best for you.
Find a Program to Match Your Needs
I hope this article sheds some light on what makes these two educational options different, as well as the advantages and disadvantages of both. Both are great choices depending on your needs, and as long as you are learning and taking the time to build up your knowledge and experience in data science, you will succeed.
