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My Data Science Boot Camp Experience

Greg Condit
Mar 7, 2023

I receive a lot of questions about my Data Science boot camp experience, so rather than trying to respond with full detail in an email or LinkedIn message, I probably sent you this link. While this does include a review specific to the one I attended (Thinkful/Bloc), it is intended to be a broader blueprint to anyone who is attending or considering a Data Science boot camp/accelerator. If I sent you this link, don't take it as a conversation ender - I'm totally open to discussing further!

Quick Overview:

These are the main topics, which I'll write about as responses to questions I frequently hear.

  • Format and Content: Self-owned, structured study and project learning, then meet with a mentor 2x a week
  • Mentorship: Done via video calls
  • Location: Remote
  • Duration: Pitched as 6 months, but I took 8 months to do some deeper dives into various projects
  • Job Guarantee: In certain markets, including mine, the program cost was refunded if you don't get a job offer 6 months after graduation
  • Cost: ~ $8,000
  • Job Search: How it went, what helped and what was tough

One disclaimer specific to Thinkful: The Bloc acquisition/merger happened during my program, so any changes due to that event may not be captured in my experience.

Format and Content

What was the format of your boot camp?

Thinkful provided online content through a web portal. Assignments and projects were to be hosted on GitHub, and the links were submitted through a portal. I was assigned a mentor, and we were to meet via video call twice a week, 45 minutes each. There was also a slack community for smaller questions.

What did your boot camp cover?

Thinkful started with basics of Python and Git, moved into basics of data pulling and manipulation (SQL, dataframes, etc), cleaning and pre-processing, and then machine learning and other predictive techniques. The last month of the boot camp branched into an elective capstone, with topics like Time Series forecasting, Deep Learning, or Big Data to choose from.

How did Thinkful manage the content?

The Thinkful web content linked out to other websites pretty frequently, so it can perhaps be thought of as an outline with basic content/explanations that collated useful links for deeper study. Each section ended in a hands on project - no easy/clean data provided, you had to find your own, real-world data, and apply what you learned to that dataset. For example, an assignment might be, 'Find a dataset with at least 5 continuous variables, and practice using PCA as a dimensionality reduction technique to reduce those to 2 feature components. Visualize the output." All assignments like this had to be reviewed with your mentor for validation.

It sounds like some boot camps sort of just organize content that's already out there. Couldn't I just replicate this learning experience on my own without paying so much money?

Hmm. Well, yes in a sense, but no. You technically could access content that is just as good as what Thinkful provides and links. (By the way, I don't look down on them for linking to other resources. There's no need to reinvent the wheel). And if you're really, really disciplined, you could guide yourself through projects and find ways to get feedback on them.

I don't think the value of my boot camp was providing/generating the content. Instead, what I paid for was:

  1. Organization: Sure, you can find the individual resources for free, but how do you know how to organize them into a cohesive study plan? This actually matters a lot - learning things in a logical order allows the concepts to build on each other, and jumping around - the way an overwhelmed beginner might without direction - can be very inefficient.
  2. Community and Support: Even with the best resources out there, I got stuck pretty often. For small things, I could post in Slack and get some good debate that would clarify my understanding. For bigger things, open Q&A sessions and my mentor meetings provided breakthroughs I couldn't achieve on my own.
  3. Deadlines: If you have absolutely gold-tier discipline you can skip this bullet point, but for the rest of us, having concrete deadlines helps productivity. If I'd been on my own, I'd get too excited by some project and go down a many-month rabbit hole.

What was the most useful part / what made the format work for you?

HAVING A GREAT MENTOR. My mentor, Mike Ricos, really made the program. Mike values curiosity and passion projects, and we ended up spending many hours collaborating on my projects together - hours for which he was NOT paid. You can't count on finding someone that giving just anywhere, but you should expect to have a mentor who is responsive, educational, and willing to dive deep into discussions with you.

By the way, he was my 3rd mentor, which leads me to...


What if I don't get a great mentor?

Raise this issue early and loudly! You are paying for this experience, don't settle! My first mentor assigned by Thinkful was very good, but she had to resign unexpectedly. My second mentor was smart, but not very educational. Our '45 minute' calls often ended early, because they would answer my questions by sending my links instead of discussing with me. I gave it a rigorous effort, but it just wasn't working, so I demanded a new mentor. I would've had a completely different experience if I'd just seen it through. Do not hesitate to demand the best for yourself.


What's your opinion on remote boot camps vs. in-person?

If you can cut it, I think remote is great - for 2 main reasons:

  1. Flexibility: A few different times, I got excited about a project and went down a 2-3 week rabbit hole. These projects were super valuable for my eventual job search / interviewing. A more rigid, in-person curriculum may not allow this type of diversion.
  2. Saved Time: Even if your commute is short, any time spent on the road is time you could be learning and studying. I value my time very highly, as should you.

What considerations should I think about to see if I can do a remote boot camp?

Home environment, and the support network of the specific boot camp.

  • Home: a boot camp is challenging, especially if you have a family or a full time job. I had both, and my wife is a saint for making it though those months. I would go into my office at 7 am for my day job, and basically not emerge until 11 pm when I'd collapse into sleep. Had she been less supportive, it would've been an extremely challenging time. It goes without saying as well that you need a quiet, dedicated study space. Don't try to complete a boot camp on the couch with the TV on.
  • Their Support Network: Before I committed any money, Thinkful let me join their slack channel and any mentor Q&A sessions. I was able to see that their community was pretty robust, and that it would do a decent job of matching the support you'd get in-person. It's probably not equally good, but it was close enough to be effective. Don't pay for a remote boot camp without validating this.


How long was your boot camp?

By the book? 6 months. In reality it took me 8 months; partly because it's a tremendous amount of deep work, and partly because I would occasionally get excited about projects and spend 2-3 weeks working on those instead of the content. The latter I don't regret at all.

Job Guarantee

What is a job guarantee?

Some boot camps - including the one I attended - offer a conditional job guarantee. If you complete the program well, and perform an agreed-upon amount of job searching afterwards, they guarantee that you'll get a job in data science, data analysis, or data engineering. If you don't,they'll refund your tuition.

Was it useful to have a job guarantee?

Yes, but I declined it pretty shortly after graduation. It's useful, but maybe not for the reasons you think:

Bad Reasons to want a job guarantee:

  • Because it will help me get a job after I graduate. In my experience, the job guarantee requirements for job searching were counterproductive. In order to keep the guarantee valid, I was supposed to apply to 10 jobs per week, and attend 5 networking events per month. I get why they have these requirements, but even my career adviser seemed to have mixed feelings about the arrangement. As I've stated before, I value my time highly, and this was effectively endorsing a quantity-over-quality strategy. Anyone can go onto a LinkedIn job board, search 'Data Scientist', and click 'Quick Apply' 10 times. Those folks will also be ignored almost every time. I would much rather submit 2 highly customized, quality applications than 10 rapid-fire, generic applications. More on this in the Job Search section below.
  • Because if I don't get a job I want my money back.  This is a defeatist mentality! Of course you'll get a job. I understand wanting a safety net, but build some self-reliance and don't plan for a bail out. Burn your ships!

For these reasons, I declined my job guarantee. However, I am glad I had it:

Good Reasons to want a job guarantee:

  • Because I want LEVERAGE to ensure I have a good educational experience before I graduate. As I mentioned above, I went through 3 mentors before finding a truly great one. I have no doubt that when I sent in complaints or requests, boot camp admin was checking my file and seeing that if they don't take care of me, they could lose some big cash. This kind of attention makes a difference.
  • Because I want the boot camp to have an incentive to help me with networking. Suppose your boot camp admin gets an audience with a company and plans to present some candidates. All else equal, they will prefer to promote candidates whose success dictates their own income.

In my opinion, this is the winning mentality - use a job guarantee as a tool to further guarantee eventual success, not as a safety net for eventual failure.


Thinkful costed about $8,000, or a bit more if you chose to pay in installments.

Does it matter how I pay (Lump sum up front vs monthly)?

Yes. I'm not here to be a financial advisor, but if you have the choice, here are some considerations specific to the education itself:

Monthly Payments: The upside to paying monthly is that if you somehow get a job before your program even ends, you can just cut the boot camp short and save some money. This may sound unlikely, but I know at least 2 colleagues who achieved this scenario. Once you have a job, why continue paying to learn? You are now getting paid to learn! The downside is that you won't dive deep on some passion project if it means you may have to pay for additional months. These can be valuable learning opportunities.

Lump Sum: Conversely, the upside to paying upfront (besides typically paying less overall) is that you typically get some (not unlimited) flexibility to take longer, learn more, and build more impressive portfolio projects. I found this very valuable and I believe it helped my job search succeed. The downside is that if you are one of the lucky folks who get a job early, you aren't getting a refund for unused time.

As I implied, I paid a lump sum upfront.

Job Search

What advice do you have for boot camp grads who are job seeking?

  1. Put time, effort, and (if necessary) money into displaying a portfolio of your work. Hence... this website. Look around here and steal some ideas! Notice how I have my work organized in repositories on GitHub, and I have my thought process and strategy laid out here in articles. GitHub demonstrates competence, but a site like this demonstrates communication and clarity of thought.
    Hiring managers love content like this, because it's pressure-free; they can peruse without feeling any obligation, which means they'll be more comfortable and willing to spend time reviewing. Because of this website, GitHub, Medium, and LinkedIn, I would say about half of my interviews came from recruiters reaching out to me, instead of my own applications.
  2. For applications, choose quality over quantity. I alluded to this above in the 'job guarantee section'. I only applied to jobs I would actually consider. In general, I would first apply, then 2 days later, I'd find someone on LinkedIn on the company's data science team and message them. You don't need premium for this - send them a connection request, and you can include the message in the connection request for free. (It is limited by length, but that's okay, you shouldn't be writing them a book anyway.) Don't mention the job at all, just mention that you are interested in hearing what they are working on and would love to do an informational over the phone sometime. For most people that's a pretty small commitment. If possible, include some snippet in your message that shows you've researched their group/company. If that doesn't get a response within a week, find anther contact there and repeat the connection request.
    When you speak with them, keep the conversation focused on them and their achievements. Eventually, they will probably realize they've been talking a lot and ask about your background, at which point you can casually mention that you are on the market and that 'calls like this one have proven helpful for me to understand the landscape of data science in [industry x]'. End your elevator pitch by asking for advice and/or any other data who might be willing to share their work with you (don't ask for a job referral). If you don't even get a chance to ask for advice, you can do it as a follow-up email or message.
    Often by this point people will offer a job referral, if you've proven you aren't a crazy person. If not, you at least have a new connection and hopefully leads for more connections.
    This is a lot of googling, reading, and researching, but it's time better spent than spam-applying 7 jobs and forgetting about them.
  3. Let them disqualify you, don't disqualify yourself. If you saw the job description for the role I accepted, you might laugh. I fulfilled very little of the job requirements, which included 7+ years experience as a Data Scientist and experience with a few database platforms I had never heard of. You should still apply, even if the requirements seem too intense. Let them make that decision, don't make it for them! Companies out there don't always know what they need. What they are actually searching for is a smart person who can tell them what they need. Checking software boxes is not actually that important.
    To be clear, I didn't pretend I had 7 years of experience, and I was very upfront that I had only done a 1 hour tutorial on the database platform they use. If you are honest but still seem confident you can learn quick and do the job, they are less likely to worry about specific software requirement

Still have questions? Feel free to reach out using the form on this website, or email/LinkedIn.

Greg Condit

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