Higher Education Pathways Into Data Science (FAQ 004)
The next two articles in my series will be about how you can take a “straighter” (although not without challenges and obstacles) approach for a career in data science so that when an opportunity presents itself for a job or internship, you’d have the necessary baseline skills to take advantage of the opportunity. Since there is no “right” path, consider how each one of these options may fit into your life. Each option will be more or less feasible depending on what you have going on in your life. Life situations like currently being a student, being well into your career, and/or having a spouse or family will all have different impacts on the feasibility of each path.
This first article focuses purely on educational or training programs offered by colleges and universities. The next article of the series will focus on non-university programs. University programs have very specific benefits based on your personal preferences and how you learn best or how well you can prioritize your own learning. As you read this article, you’ll need to take into account your learning style and preferences. Some people succeed better with the structure of a university program while some might fare better with the less time-structured options in the next article.
The most important thing I can leave you with (and a topic for another article) is that pursuing a higher education opportunity or self-education opportunity is not enough to get you a job in data science alone. You’ll need to have projects to show how you can take what you learn and apply it. You’ll also need to meet and network with data scientists to make your job hunt easier. Again, a topic for another article but stay tuned for that 🙂
Majors, and Minors, and Concentrations, Oh My!
Opportunities for DS and AI training at the undergraduate and professional school level are becoming more and more popular. 10 years ago, relatively few programs for DS and AI existed outside of the Master’s degree or PhD level of education. Now that undergrad and professional school opportunities are available, students can pursue careers in these fields sooner. Opportunities at this level can be grouped into a bachelor’s degree, a minor, and a concentration depending on your school. For context, a minor at my alma mater (Drake University) usually involved ~7–8 classes while a concentration was ~3–4 classes. Both of these allowed students to get a good base of understanding of the field without devoting their whole education to the topic. If your interested in one of these options after reading this section, please reach out to an advisor at your school to see if one of these programs might fit into your education.
These programs are even attainable by you pharmacy students out there, a data analytics minor was one way I got my start in data science!
Who is this route right for?
This route into data science is for students who are in their undergraduate studies or are in a professional school like pharmacy school. For you pharmacists out in practice or in residency, I would recommend checking out the other opportunities presented in this article. As a student, pursuing something like this in your undergrad or professional school career gives you the ability to see if you like AI/DS as a future career. If it turns out that you don’t see yourself making it a career or it isn’t what you thought it was, you can drop your minor or switch to another discipline without losing much ground. Better to find out you don’t like something when it’s not your livelihood!
Considerations
The 3 options under the undergraduate and professional school umbrella require a significantly different amount of effort. For pharmacy students, a bachelor’s degree is not feasible unless they would pursue an AI/DS bachelor’s degree and then apply to pharmacy school and plan that out far enough ahead of time. A minor or concentration can be achieved by a pharmacy student with proper planning. I was able to complete a data analytics minor while in pharmacy school based on a few unique situations. AP credits transferred from high school or taking gen ed classes at a local community college near you in the summers could give you the opportunity to take classes in an AI/DS discipline. If you’re considering this route, set up a meeting with a career counselor or academic advisor to see if this is an option for you.
One of the most important things I can emphasize here is how powerful a bachelor’s degree, minor, or concentration is when combined with another area of expertise. For the pharmacy students out there, the combination of pharmacy and clinical education with the addition of AI/DS education is invaluable. As AI/DS matures within industries, it’s becoming more and more important in jobs to have both an AI/DS background in addition to domain expertise in the industry you work in. AI/DS can be expensive from a labor and technology resource standpoint and organizations can’t afford to have people working on projects that won’t make quality or financial impact. In healthcare, a Data Scientist who has clinical training is likely to better understand the healthcare data landscape and what data resources might be available and have a better chance for success. That’s not to say you have to be clinically trained to be successful, but having a clinical background on a data science team is incredibly handy.
+’s (advantages)
The major advantage of a bachelor’s degree, minor, or concentration is how early it enables you to learn about AI/DS topics. You can take the skills you learned in school and apply it to your job right after graduation. If you’re a pharmacist for example and practice pharmacy for 10–15 years and decide to switch, not only are you out of practice of studying (if you would pursue a Master’s) but you also have less ability to take a pay cut which is something that will be required in the vast majority of cases when you switch to AI/DS. Unlike informatics, a pharmacist does not get paid a pharmacist’s salary just because they have a PharmD. Experience and education are taken into account in terms of your pay but this is important to recognize. Pursuing AI/DS earlier helps you avoid these potential issues. A bachelor’s degree, minor, or concentration allows you to meet different groups of people throughout your undergraduate and professional school career. When I took classes for my data analytics minor, there were no other pharmacy students in my class so I was able to meet others who didn’t think the same or have the same educational path.
-’s (disadvantages)
There are relatively few disadvantages to this path. The main one that I’d like to call out is that pursuing a bachelor’s degree, minor, or concentration might require you to go out of your comfort zone, academically and personally. Fitting extra classes into an already chaotic pharmacy school schedule can create a number of conflicts and late nights managing the workload. AI/DS projects in class will often be a different type of work than something you’re used to in pharmacy school. Pharmacy classes tend to revolve around understanding pieces of information (memorization) and how they fit together but then moving onto the next topic. AI/DS classwork will more likely involve larger homework projects that might involve group work as a significant portion of your grade.
Master(‘s) of the AI Universe
For those of you out there that are past your undergrad days or are already pharmacists, the undergraduate/professional school option above likely isn’t feasible. Luckily, there are many opportunities at the grad school level to learn about AI/DS. Like undergraduate degrees, there are a few types of Master’s degrees to consider that can get you to your end goal. I would recommend seeking out a Master’s in Analytics (most common), Master’s in DS (becoming more popular), or Master’s in Artificial Intelligence (rarer). Analytics programs tend to be more developed and trusted in the technology industry. Masters in DS or AI do not have the same track record because they are so new. Think of it similarly to today’s current pharmacy school openings where the new programs are generally stigmatized because some people see them as money-grabs by universities. You can certainly succeed and get a job after a Masters in AI/DS, but be aware that you might need to spend more of your time highlighting projects you worked on to show your skills.
Who is this route right for?
A Master’s program is for those who already have an undergraduate or professional degree and are confident that a career in AI/DS is for them. Before you sign up for a Master’s program, I would recommend talking to a number of people working in the AI/DS field to get an idea of what they do day-to-day to see if you’d enjoy it. I cannot stress enough how important that part is so that you don’t waste the investment you make in a Master’s program. For example, if you are not that interested in programming and coding, you probably shouldn’t be a data scientist. I spend a good chunk of each day programming in SQL, R, or Python so you should have some interest in programming. I promise that coding is not as difficult or scary as some might lead you to believe, I find that it uses similar critical thinking and problem-solving skills that I use as a pharmacist. Networking with Data Scientists is important to help you decide if you want to work in AI/DS but it will also help you break into the field and get your first job.
Considerations
If you decide to pursue a Master’s, there are a few things you’ll want to take a look at in addition to the type of Master’s (Analytics vs DS vs AI) discussed previously. Many Master’s programs in the AI/DS world have options for online learning. You’ll need to decide if you are fine with an online program that has less of the accountability that going to class on-campus creates. You may decide that a local program is a better fit because being in-person helps you learn and be accountable. Master’s programs are generally 1–2 years so you should also consider what other opportunities or projects that you’ll miss by enrolling in a program. If going back to school is an issue because of student loans or tight money issues, there is a possibility that you can defer your student loans while in school. This can also give you the ability to save for the Master’s program as you take it. You’ll have to look into the specifics but I was able to defer my loans while I was pursuing a Master’s in Analytics (that I did not end up needing to finish) as long as I was taking 5 credits. I was able to take that student loan money and pay cash for my classes then. If you can still pay any loans you have while in school, that would be ideal but this can be an option.
+’s
The main advantage of doing a Master’s program is the structured learning environment compared to AI/DS courses on websites like Udemy, etc, and the support system that a University has. A Master’s program is going to have a pre-set list of classes for you to take to learn the basics of AI/DS and likely many electives that you can tailor to you’re specific interest. The Master’s program I was pursuing even had a “Big Data in Healthcare” class which was particularly interesting to me based on my background and interests. Different Master’s programs have different sets of classes that they deem important to teach so a great way to both network and find programs that may be right for your career goals would be to talk with Data Scientists you know (or meet) and see their thoughts about how well the program would prepare you for a role on their team if their work is interesting to you. A curriculum would hopefully include main classes with info about machine learning models and when to use them, programming classes in R/Python/SQL, and visualization classes at a minimum.
Universities that offer Master’s programs also have benefits like career offices that can help you get placed in a job after you graduate. The Master’s program that I was a part of for a while was at a university that all the leading technology companies would come multiple times a year for recruiting events. These opportunities were able to be taken advantage of to increase the odds of getting a job. A university also allows you to build skills needed in AI/DS by being a TA and networking with other students and professors. This will allow you to improve your communication skills and also give you more potential job opportunities as your network expands.
-’s
I don’t want to make a Master’s program seem all rosy when there are a few things that you should carefully consider before enrolling. I mentioned this before, but you should do a significant amount of due diligence to make sure this is the path you want to pursue before enrolling. This will help avoid dropping out of the Master’s program and losing the investment you’ve already made. I decided to drop out of my Master’s program 4 classes in because I got a job in AI/DS. I did not see this as a loss though because I learned a lot and actually got a job in AI/DS before I finished the program. The program was relatively cheap though so I did get my money’s worth, something you’ll have to judge for yourself.
There is a wide variety of pricing structures for AI/DS Master’s degrees. The program I was in was the Master’s in Analytics Online at Georgia Tech. This program and the one at the University of Texas at Austin cost around $10,000 for the whole program. These schools have great reputations and $10,000 for the whole program is quite the steal. You can even get your work to pay for it potentially. Where you’ll want to be more judicious is programs like the Master’s in Data Science at the University of California-Berkeley, which runs $60,000 for the complete program. Other things to consider about a Master’s program is the speed at which coursework progresses and how much of your life it will take up. Semester-long classes are designed to progress at a certain speed so you might find yourself waiting for new content without the ability to progress on your own. You can help solve this by working on personal or portfolio projects. Master’s program classes also have deadlines that are more rigid than some of the self-learning opportunities out there. You may find at some points in a program that you need things to slow down as life happens. This is much more difficult to manage in a Master’s program.
Certified Data Scientist
A certificate program is great for those who already have a job or career but don’t have the 1–2 year time commitment for a 30+ credit hour Master’s program or those who aren’t sure that AI/DS is necessarily for them. A certificate program is much less of a time and money commitment since the programs generally are made up of ~ 4 classes. This is a much more feasible opportunity for those just starting out.
Considerations
When looking for a certificate in AI/DS, you should consider whether an online format or in-person format would be best for you because you will likely find that both options are available. You can take the first step by googling something like “data science certificate” or “artificial intelligence certificate” and start building a list of programs that sound interesting to you. This is also a great opportunity to connect with those data scientists that I recommended you connect with and see if they think the programs teach the necessary skills. Certificate programs are much less time-intensive than Master’s programs but also consider what you might have to give up to still take 3–4 classes in a certificate program. If you are married or have kids, weigh how the program will affect your time with your spouse and kiddos. If you don’t have a spouse or kids (or even if you do), weigh how a program will change your social calendar or what other opportunities you might have to put on hold.
+’s
The advantages of a certificate program are much the same as the Master’s program section. These programs are often taught by universities and offer a great deal of structure to your learning. You also will likely be able to use the university’s career planning services or at least get guidance in the program about how you might go about finding a job after. A university program also allows great networking opportunities with professors and other students. I keep mentioning networking but you won’t know how important it is to know people who can get you a job until you get a job through someone you know. That’s my exact path to the data science team I work on now, I knew the Data Scientist who led the team and reached out when I saw a position open on the team.
-’s
It shouldn’t come as a surprise that the disadvantages of a certificate program are pretty much the same as the Master’s program section, although just a little bit less severe. Certificates can still cost you a pretty penny even if it’s less than a full-blown Master’s. Harvard’s certificate costs around $11,000 for 4 classes and even Columbia University’s program runs more than $2,000. It will be important to weigh the benefits you get from these programs. The courses in a certificate program also will only let you progress at a certain rate so you’ll need to find supplementary sources if you want to learn faster. You’ll also need to think again about the time commitment, even if it is less than getting a Master’s.
Wrap Up
This article was the first of two articles about the educational opportunities that are available to learn the skills necessary to be a data scientist. We focused, in this article, on the options available within the higher education system whereas we’ll focus on non-traditional ways of learning data science skills in the next article. Either way, you’ll still need to develop skills like communication and time management that neither higher education nor a non-traditional education path will teach you.
Today, we highlighted three ways to get some of the needed skills for a AI/DS career by looking at undergraduate and professional school options, Master’s degrees, and certificate programs. Each option had its own advantages, disadvantages, things to consider, and types of people for which it was the best option to pursue. I’m glad to share this resource to help you better decide which option may work for you!
Is there other data science content that you would like to see? Let me know by reaching out on this article or connecting with me on LinkedIn!
