Are you looking to learn data science fast so you can rein in some incredible new career opportunities? In this article, I am going to lay out the very best data science learning paths for you to choose depending on your own unique circumstances.

I’m also going to share the very best, low-cost data science boot camps on the market. These recommendations are based on current market research in 2021 as well as my opinion based on my own experience working in data science for the last 9 years.

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Why am I qualified to say anything about learning data science anyway? Well, I learned data science back in 2012 and since then I started my own data business. Within that data business, I was able to train over 1 million data professionals on how to do machine learning and AI.

My name is Lillian Pierson and I support data professionals to become world-class data leaders and entrepreneurs.

In this article, I’m going to share with you what I would do if I had to learn data science again, but that may not apply to you…which is why I carved out a few different learning paths that you can  adopt based on your current circumstances. 

Approach #1: The Self-Taught Data Scientist 

The self-taught data scientist approach is the approach I took when I learned data science back in 2012. I actually produced an ebook on this topic a few years ago and not a lot has changed since then. This approach is pretty simple and very affordable.

The self-taught approach is for people who already have a stem degree. If you have a stem degree then you just need to kick it into overdrive by taking some extra courses on the following: 

  • Statistics
  • Machine learning
  • Data visualization
  • Data storytelling 
  • Python for data science 
  • R programming
  • SQL

Honestly, you can just go over to Udemy and look for some top rated courses there and once you’ve got those courses under your belt, then you should be good to go. You may want to look into specializing in natural language processing and deep learning or you may prefer to go into the more business-end of data science and become something like a data science product manager, product manager or even start your own business, which is what I did.

Remember this: Data Scientists are NOT Statisticians!

The key distinguishing point between them is that data scientists have subject matter expertise. So while you’re learning data science, be sure to lean in heavily on the area of your subject matter expertise – that would probably be similar or related to your university degree. Or if you already have substantial work experience, then the industry you’ve worked in the past would be a good candidate for subject matter expertise.

I have courses on LinkedIn Learning about Python for Data Science and How to Build Recommendation Engines that you can check out here

Let’s move on to the next approach in the data science learning path…

Approach #2: The Data Science Degree

This is for people who do not have a stem degree yet. If you don’t have a stem degree, don’t worry, you can still learn to do data science. But I recommend that you go through a university program because they will make sure that you have all of your essential pre-requisites before admitting you to the program. They will also put you through the rigorous approach that it takes for you to get a degree in the stem field. You really want to have that experience under your belt just to prepare you for the challenges of what it’s like working in data science. 

Unfortunately, I know that going back to a university can be expensive, but I recommend shopping around and looking for the most affordable ones or even looking at community colleges that can get you up to speed in the basics that you need in order to learn data science. 

If you like this post about the data science learning path, then I’m sure you’re going to love the video I did on Data science career path as well. Check it out here.

Approach # 3: The Data Science Bootcamp

Now, if I needed to learn data science over again, I would take a data science boot camp approach. The thing I really like about data science boot camps is that they quickly adapt and evolve with industry needs. They adapt faster than University programs, so they will get you up to speed on the latest developments.

Also, one of the nice things about a boot camp is that you don’t have to worry about designing your own curriculum or trying to hold yourself accountable. They have a program in place to support you and hold you accountable and walk you through each and every step of the process.

You can generally get an entire set of data science skills in 16 weeks or so through one of the online data science boot camps, but again, I only recommend these for people who already have a stem degree. 

And lastly I’ve promised you that I would tell you the very best and low-cost data science boot camps in the market and these are the programs I would look at enrolling in if I had to learn data science all over again…

What I Would Do

Personally, what’s changed in my life since I first learned data science is that I started my own data business and that business brings in enough revenue that I don’t have to skimp and save all the time just to get by. Because I have that money, I would take the easier and faster approach which is to go to a data science boot camp. 

But not just any boot camp. Let me tell you, these data science boot camps are making a lot of money and most of these companies are funded out of Silicon Valley by investors who are looking to get a good return on investment. So, they’re coming out with programs that cost $16K-$18K for 4 months and then you’ll get a set of skills that you could literally learn on Udemy for less than $100, if you had the initiative. 

Please do not sign up for something like that, unless you are especially compelled to do so.

I, myself, would never spend $16k on a data science or any sort of skill-building workshop.

The boot camps I did see out there that look especially promising though are:

  • UCLA Extension – 10-Week Data Science Intensive ($4.5k)
  • Guru Path of the Data Science Bootcamp at Data Science Dojo ($3k)

I chose these two boot camps over all the rest because they allow remote learning and the programs are robust. When I looked at their curriculum, I was looking for a more sophisticated expertise and experience that you would develop –  things like network analysis, natural language processing or time series analysis – things that aren’t straight out of the box pretty simple and these two programs offer that at a very affordable price point. They also have really cool, real-world data science projects as part of their programs.

In terms of getting hired as a data scientist, you’ll need to have some experience. There are really two ways to get experience once you know how to do data science and that is either:

  • to get paid for your work and learn by doing it on the job
  • by freelancing for a reduced rate since you’re new

What I don’t recommend however, is spending lots of time doing tons of practice and building out these huge coding portfolios and applying for jobs when you can actually get paid to improve and become a data scientist on the job.

I cover both of these approaches in this ebook “A Badass’s Guide to Breaking Into Data.” Make sure to get your free copy here.

badass's guide to breaking into data

 

If you’re looking to invest both your time and money into learning data science, then now is the time for you to actually start setting a vision for what you’ll actually do with those data science skills. I have put together a really fun, 45-second quiz that’s all about you and how your personality type aligns with the top 50 data roles that companies are actively hiring for. It’s called the Data Superhero Quiz

Take the Data Superhero Quiz Today!

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Lillian Pierson, P.E.

Lillian Pierson is a CEO & data leader that supports data professionals to evolve into world-class leaders & entrepreneurs. To date, she’s helped educate over 1.3 million data professionals on AI and data science. Lillian has authored 6 data books with Wiley & Sons Publishers as well as 8 data courses with LinkedIn Learning. She’s supported a wide variety of organizations across the globe, from the United Nations and National Geographic, to Ericsson and Saudi Aramco, and everything in between. She is a licensed Professional Engineer, in good standing. She’s been a technical consultant since 2007 and a data business mentor since 2018. She occasionally volunteers her expertise in global summits and forums on data privacy and ethics.

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