Can I Learn Data Science For Free?

The answer here depends mostly on how much you want to learn. If you’re curious about what makes data science tick, and all you need is a casual understanding of the topic so you can carry on a conversation about it at a cocktail party, you probably will do fine with such free resources as are out there. On the other hand, if your goal is to develop knowledge of data science on a professional level, then you’re going to have to look beyond what you can get through the usual free channels to a more structured course, although, even in this case, free online resources can still be of some use to you.

What Free Resources are Available for Learning Data Science?

The most obvious free resources available are to be found on the platform upon which everyone has come to depend for any kind of free video content, be it for a tutorial on how to make an icebox cake or for videos of rides at Disneyland you can screen for your children to make sure that they won’t be (too) scared when you all get to Anaheim: YouTube.

Google’s video-sharing platform features 114 million channels and a total number of videos that may well reach infinity one of these days. While 82% of YouTube users use the platform for entertainment, some 7% of users avail themselves of it for professional help. That 7% is the reason why there are so many YouTube classes on all manner of business topics, data science being no exception. 

On YouTube’s menu of data science specialties, you’ll find everything from little canapés of information all the way up to main courses the size of the side of ribs in the opening of The Flintstones. Some of these classes are, admittedly, designed to get you to spend money for an advanced class, but that shouldn’t keep you from enjoying the free part of the course. Other YouTube videos don’t try to sell you something, and, thus, are free in every sense of the term. There’s a lot to explore, and there’s a probability that you’ll find something you don’t mind watching too terribly. If you really do mind watching these YouTube videos, you may well have learned the valuable lesson that data science isn’t for you.

Beyond YouTube, a number of IT schools make their introductory live lessons available to the general public. This includes schools that specialize in live online instruction, such as Noble Desktop, which offers a free seminar about Getting Started in Data Science that will introduce you to the core aspects of the field as well as give you a feel for what the school’s learning platform and teachers are like.

A further, if a bit more complicated, way to test the free waters is the seven-day trials that self-paced learning platforms Coursera and Udemy offer. These platforms offer complete data science curricula, and they give you a week to poke around their offerings. (If you choose to give the Udemy trial a whirl, you’ll be able to take advantage of its catholic assortment of other courses.) Again, this won’t teach you everything you need to know to become a professional data scientist, but it will give you a fair idea of what it’s like to learn to become one.

A final type of free material on the web for learning data science is the wide assortment of available print media. This, which extends to free copies of arcane codices that run close to 800 pages, is often genuinely free with no strings attached or credit card numbers to surrender. If you learn well by reading, these may be valuable resources that will spare you having to buy what tend to be expensive textbooks: you’re not going to find The Elements of Statistical Learning: Data Mining, Inference, and Prediction discounted on Amazon because it’s on the bestseller list.

How to Make Use of Free Data Science Resources

Probably the best way to approach the wide assortment of free resources on the web is something like the way you’d approach a smörgåsbord: start off by filling your plate with little helpings of whatever strikes your fancy, and then go back for a second round of the dishes you really liked. It’s all free, so you risk nothing by peeking under the chafing dish covers and trying smoked eel for the first time in your life.

You probably should start off with one of the data-science-in-five-minute videos, just to get yourself oriented, especially if you only have a vague picture of what data science actually is. From there, you can take a plunge into one or more of the free YouTube classes, and take a nibble here and a nibble there. You’re not married to any of these courses, so you shouldn’t feel too bad about skipping around.

If you’re still interested after that, you can proceed to the free webinars that will give you a taste of what live learning across the internet is like, and how it stacks up against self-paced tutorials such as can be found on YouTube or the Udemy or Coursera seven-day trials. (Don’t forget that the Udemy trial will give you a crack at things like tarot reading courses that will teach you that, if you’re looking for professional success, the Sun and the 10 of Pentacles are the two most propitious cards in the deck.)

Especially if you enjoy reading, you could also consider some of the free print media that are available online. You can flip through a book a lot more quickly than you can a video tutorial, and, therefore, you can get an overview of the kinds of advanced topics that will await you if you decide to commit to a course of data science study.

Once you’ve completed an entire circuit of the smörgåsbord table, you can go back and get more of the dishes you liked. You’ll have an idea of what the field is like, and you’ll know which resources appealed to you the most. That should set you up for being able to make an informed decision when it comes time to select a course in earnest.

Limitations of Free Resources

While the best things in life are free, data science video tutorials must not be among the absolute best things, as the free ones can leave something to be desired. The biggest drawback you’ll encounter with free online video tutorials is their currency. Data science is a rapidly expanding and changing field, and online tutorials don’t magically change to keep up with evolving trends. Indeed, and this is truer on YouTube than it is with paid on-demand courses, video tutorials can very quickly go past their best-by dates without anyone taking the time either to update them or to pull them from the platform. So be careful about getting too deeply involved with a course that’s been up for five years. Those, alas, are free in the worst sense of the term, like the flat screens people leave on their lawns with a “free” sign taped to them because the trash collectors won’t take them.

The other shortcoming of all these online resources is that they don’t give you a teacher with whom to interact. Thus, if you should have a question, you won’t be able to ask it. A good researcher can probably hit the indices of various books and eventually come up with the answer, but that can take a lot of time and be very frustrating. It isn’t foolproof, either. The inability to ask questions is probably the single greatest shortcoming of all these free resources.

Learning on your own, be it using free resources or an on-demand program of video tutorials, has a further defect: the lack of someone to supervise your progress and encourage you to complete your course. When you have a live teacher on your side, you’ll have someone engaged with your progress and who wants to see you succeed. This human element is given less and less weight in the era of emerging AI, but there’s little that can replace learning from a sentient being of your own species. AI may have its uses when it comes to making head or tail out of unstructured data, but even machine learning has to learn from a human. There is, bottom line, little that can replace learning in real-time from a real person. Yes, it’s going to involve an investment, but it’s an investment in your future.

What to Do After Utilizing Free Data Science Resources

Although free online resources have their usefulness, ultimately, you’re going to need to turn to a live class if your goal is to break into data science professionally. The shortcomings of learning from free online resources and on-demand courses disappear when you switch the teaching modality to live online (or live in-person, although those courses are becoming rarer than white peacocks.) Although you may not have experienced a live online class, rest assured that they offer all the advantages of a live in-person class, only you get to study from a comfortable spot you get to choose and don’t have to brave rush-hour crowds to get to school.

Noble Desktop, a provider of live online data science courses, offers both substantial certificate programs geared toward beginners and shorter courses that are better suited to those with something of a background in the field. Noble’s twin flagship data science certificate programs are the Data Science Certificate and a slightly longer alternative, the Data Analytics Certificate. Both cover Python and its data science libraries (NumPy, pandas, Matplotlib), SQL, and will initiate you into the mysteries of machine learning, and both will prepare you for an entry-level position in data science or data analytics. Among the shorter offerings, you’ll encounter a Python Machine Learning Bootcamp, which is designed for people who already know how to program in Python and are looking to catch the programming wave of the future.

All of these Noble Desktop classes include mentoring sessions that offer you the opportunity to work with experienced data scientists 1-to-1, and give you a resource for asking questions that goes beyond your classroom teacher. These mentoring sessions can also be used to perfect your portfolio, resume, and other job-search materials. Additionally, you’ll get a one-year retake option. The courses are fast-paced (especially if taken full-time), and you may find that you want to take several of the modules (or all of them, for that matter) a second time.