What is the Fastest Way to Learn Data Science?

There are times in life in which you need to pick up a new skill as quickly as possible. Of course, you can’t complete a data science PhD in the space of a week, but there are ways to assimilate some basic information rapidly, and even to have yourself ready to start out on a new career in less time than it takes an emperor penguin to incubate his egg. While that translates to fewer than 64 days, don’t expect the necessary time to be too much less than nine weeks. Data science is a highly complex field, and you shouldn’t get the idea that you can learn it in a weekend.

Free Samples: YouTube Tutorials

If your high school reunion is coming up and you need desperately to learn enough to be able to pass yourself off as a successful data scientist, you can probably cram enough information into your brain so as to deceive your teenage nemeses by using free YouTube tutorials. In reality, data science is a vast and highly technical field that calls for quite a bit of specialized knowledge, and you can’t expect to pick that up from a six-hour free tutorial on a free streaming platform. You will perhaps be able to get an idea of what data science is all about, but not much more than that. These tutorials aren’t a bad way to find out whether data science is suited to you (and vice versa), but you can’t expect them to jump-start a new career.

Test-Driving the Subject Matter: Introductory Classes 

A more reliable way to start yourself off on your travels to the Isles of Data Science is by taking an introductory course, perhaps one that will acquaint you with the basics of Python, unless you’re determined to make your life difficult and insist on learning R instead. You can follow that, if you like, with a Python for data science class and start to apply your small store of knowledge. You could similarly consider a class in SQL, since, even as the big data paradigm shifts to NoSQL databases, you’ll still need SQL to extract information from the structured databases that lie in your future. Those are only pieces of a complete data science toolkit, but they’ll be a helpful starting point for you in the event that you wish to continue your journey to a more in-depth course and professional application of your knowledge. Introductory classes are, bottom line, only an introduction, and the reality is that a little knowledge about data science won’t get you especially far, beyond priming you for further classes. These types of introductory classes usually last about a week.

Making a Career of it: Professional Bootcamps and Certificate Programs

A certificate program or a bootcamp—generally lasting somewhat longer than a month (full-time) or at least half a year (part-time)—is, apart from getting a college degree, the only serious approach you can take to data science, since there aren’t many reasons beyond starting a new career that would draw you to studies in the subject. There are no hobbyist uses for data science (even if you’re going to try to invent a program that handicaps horse races for you, you’ll still need the full toolkit, complete with machine learning, to construct an effective model for predicting the outcome of a race), so there’s not much you can do with it until you’ve gotten a solid education. A full-time bootcamp is by far the fastest way you’ll be able to learn enough to build a bridge to a new career. As with most bootcamps and certificate programs, especially the full-time ones, there’s going to be a lot of work involved in order to complete the program, but the intensity and immersive nature of most of these courses is the result of condensing a whole curriculum in what is a complex subject into often not too much more than a month’s time. 

Questionably Useful: On-Demand Courses

As another word for an on-demand course is a self-paced one, there is no real way to anticipate how long it will take the average individual to complete such a course, short of setting up a machine-learning model and letting it do the calculating. If you’re desperate to learn a particular skill, you can pay your money for your course and obtain instant access to the first tutorial, so you can, if you feel so inclined, binge-watch the whole thing and hope that some of the material will stick with you after you wake up from your post-binge stupor.

On the other end of the on-demand spectrum is the very real possibility that you’ll lose the impetus and good intentions with which you began the course, and find yourself with the clock ticking and your license for the class ready to expire. A frequent allotted length of time for self-paced tutorials is half a year, roughly the same amount of time a part-time bootcamp would take, so that figure can be fixed as the far end of the spectrum from the six-hour YouTube class you can follow before your high school reunion.

(This survey omits the much larger time commitments involved in a college degree program. For completeness’ sake, those can take anywhere from two years for an associate’s degree of questionable practicality to four years for a bachelor’s degree and another four years on top of that if you want to go for data science broke and get a doctoral degree in the subject.)

Learn Data Science with Noble Desktop

Whichever length of time you wish to afford your data science studies, Noble Desktop can provide you with a class to match (that’s excepting that six-hour whirl on YouTube.) At the brief end of the spectrum, you’ll find the Python For Data Science & Machine Learning Bootcamp. Coming in at a couple of weeks, the program will get you up to speed on the Python aspects of elementary data science, from an introduction to programming in Guido van Rossum’s multi-purpose language to how it can be employed to create machine-learning models. If your needs are more specialized than that, the course is divisible into two parts, the basic Python and the machine-learning part, each of which can be completed in around a week.

If, on the other hand, you have somewhat more time and want to get a more rounded education in data science, Noble offers you the choice of two certificate programs: the Data Science Certificate and the Data Analytics Certificate. Both take over a month to finish. Python remains at the core of either program, from its basics, through learning to use the NumPy and pandas libraries, and onto machine learning. Both programs also include instruction in SQL and creating dashboards and data visualizations. The Data Analytics Certificate’s curriculum also includes an introduction to data science concepts using Excel and appends a module on the data visualization tool Tableau for dessert.

All Noble Desktop classes include a free retake option and recordings of your classroom sessions that will allow you to refer back to something you failed to understand during the day. Noble’s state-of-the-art workbooks and learning materials will be yours to keep at the end of the class. All the above classes include a number of 1-to-1 sessions with an experienced mentor. (The longer the course, the more sessions included.) You can use these meetings however you like, be it for assistance on something technical you learned in class but aren’t sure you’ve fully understood, or you can use them to prepare your job-search materials, including your resume, online profiles (such as LinkedIn) and your all-important portfolio of work that you will exhibit to prospective employers.