Best Part-Time Data Science Bootcamps

Data science bootcamps come in two genera: full-time and part-time. The first assumes you’ll be studying all day, every day, and probably have homework assignments that go beyond the roughly 40 hours you’ll be spending in the classroom. Anything requiring less attendance than that is, by definition, part-time. Part-time bootcamps generally meet on weekday evenings, several days a week, but only for a few hours, or, in some instances, for entire weekend days. The most immediate consequence of a part-time schedule is that you’ll need months rather than weeks to earn your certificate, but there are other distinctions between the two bootcamp flavors.

Why Learn Data Science Part Time?

The primary reason for which people enroll in part-time bootcamps rather than full-time ones is scheduling. A full-time bootcamp is, well, full-time: it’s going to meet during what most of the world considers working hours, and will conflict with any day job you may have, or with family responsibilities that call for you to be somewhere every day. These two scenarios account probably for a majority of the American population, and are the main reason that part-time bootcamps were instituted.

There are other reasons that might recommend a part-time bootcamp, even if you’re not constrained into taking one by scheduling obligations to work or family. Part-time bootcamps, because they don’t meet every day for eight hours at a go, move at a significantly more gradual pace than their full-time counterparts. That gives the information you learn in class more time to soak in between sessions. Full-time bootcamps are very intense and almost relentless in their presentation of new information. If you don’t thrive on that kind of intensity, you may make a better candidate for a class that doesn’t meet every day.

Drawbacks to Learning Data Science Part Time

The most sizable drawback to part-time data science classes is also one of their greatest advantages: the more manageable speed at which they progress through the material. The upside to that is that it has longer to soak into your brain between class meetings. The downside is that the days between classes give you time to forget what you’ve learned, whereas there is a certain amount of steady drilling involved in a full-time bootcamp.

A further shortcoming to the part-time learning style is that you won’t be going into the material as deeply as you do in a full-time class. Yes, the amount of hours spent in class is generally the same, but you don’t teach a three-hour class the way you teach a seven-hour one, and quite a bit of time is lost to latecomers, people getting settled in (regardless of whether they’re at home or in-person), and other vagaries of human beings needing to be in the same place (even if the place is virtual) at the same time.

Is a Part Time Data Science Bootcamp Right for You?

In reality, this question is better posed the other way around: full-time bootcamps place more demands on you and are right only for a relatively small group of people who have the time, money, and determination to undertake an intensive program. Logic would therefore dictate that, if you’re not in that group, you’ll be better suited to a part-time bootcamp.

That’s not meant to scare you off of a full-time bootcamp, but, instead, to urge you to consider whether part-time might not suit you better in the long run. Of course, if your schedule won’t permit you to take a full-time bootcamp, your choice will have been made for you. Even if you could conceivably attend a full-time bootcamp, you should be sure that you’re ready to sit at a computer for eight hours every day for six weeks and then to work on homework assignments so you can start all over again the next day and continue to give it your all, which is what it takes really to succeed at a full-time bootcamp. The part-time format gives you a slower pace at which to learn, and more time between classes so your brain can absorb the material at what may be a more comfortable pace for you. Both full-time and part-time are excellent ways to learn data science, but you’re probably better suited to one or the other. If you have the luxury of a choice, consider your learning style, and choose accordingly.

Ways to Make Learning Data Science Part Time Easier

If the biggest pitfall to a full-time bootcamp is potential information overload, the corresponding difficulty inherent in a part-time class is it not moving fast enough and giving you an infelicitous chance to forget what you’ve learned between online sessions. However, there’s nothing to stop you from ramping up the intensity by working on optional assignments so that you’ll be able to put in some work on data science every day. Many bootcamp programs include some type of optional homework, and, as you’ll get the most out of a bootcamp if you put in something like the mathematically impossible 120% into your studies, you should complete all the optional assignments.

There are other ways to keep yourself engaged in data science between class meetings. You can take advantage of free tutorials available on YouTube and elsewhere on the web, although these are usually pretty basic, and, as you advance in your class, you’ll outgrow them pretty quickly. You’ll do better (and run far less risk of getting mixed up by another teacher) to seek out online, or just buy, a book on data science, preferably one with practical exercises on which you can work. A good textbook will also give you a helpful reference and a chance to find further explanations of topics that may have eluded you in class.

Choosing the Best Part Time Data Science Classes or Bootcamp

One thing you want to look for in a part-time bootcamp is whether it really is an extended version of a full-time bootcamp, or whether the curriculum has been abridged to fit it into a part-time time framework. You want to make sure you’re getting the full bootcamp experience and not a slapdash, fast-tracked version that leaves out essential details. The easiest way to check this when one provider offers both full- and part-time bootcamps is to look at the number of classroom hours for each program: they should be the same, as they are at Noble Desktop. When the school has only part-time bootcamps to consider, the length of time the part-time program lasts can be an indicator of its completeness. While roughly six weeks is a fairly standard length for a full-time bootcamp, so is six months roughly the time a part-time data science bootcamp can run without unwarranted abridgments in the curriculum.

In point of fact, you should take a good look at the curriculum of any bootcamp you’re considering to make sure that it hits all the necessary bases. That means instruction in statistics, Python programming, Python for data science with NumPy, pandas and Matplotlib, SQL and structured databases, and a good, solid introduction to machine learning. If the provider finds room for Excel for data science and business intelligence software such as Tableau, so much the better. You want to make sure that your bootcamp covers all the above, since anyone considering you for a post-bootcamp job is going to expect you to know these things, and the last thing you want is to flunk a technical interview because your knowledge is incomplete.

Since scheduling limitations are more likely than not what got you to consider a part-time bootcamp, you should also make sure that the bootcamp’s schedule matches what time you have to devote to your studies. Conflicts can arise in the evenings just as much as they can arise during the daytime, and, thus, you should make sure your bootcamp doesn’t meet on your bowling night. And don’t forget to double-check that your class is in the right time zone. (Remember that you can use time zones to your advantage: if you’re on the East Coast and need a late-evening class, you can sign up for an early-evening class in the Pacific time zone, and you’ll be able to study starting at 9:00 p.m. in New York or Miami.)

Although based in New York, meaning that its weekday evening classes do indeed meet right after most people’s workdays have ended (you’ll get some leeway if you live in Halifax or Sint Maarten-Saint Martin), Noble Desktop’s data science bootcamps handily meet the above criteria. The school offers you the choice of a Data Science Certificate program, and a more extended Data Analytics Certificate, which incorporates additional modules in Excel and Tableau. Either can be taken either full- or part-time for the same total number of class hours

In addition to the courses being fully live online (there are no self-paced modules, so you’ll always be in touch with your instructors), Noble will provide you with a generous number of mentoring sessions that will put you into 1-to-1 touch with an experienced data science professional, who can offer counsel, explanations of difficult material, and, when the time times, assistance polishing your resume and portfolio. Your mentor can even stage mock interviews for you. You’ll get a one-year retake option, and you’ll be able to access recordings of all your classroom sessions, which are an excellent way of keeping yourself engaged with the bootcamp’s curriculum on your days off from class.