Why Data Science bootcamps are worth it in 2024
Data scientists are still in demand: Virtually every company, from Fortune 500 companies to local small businesses, are trying to tap into their data to see if they can apply machine learning or artificial intelligence. Every technology leader is getting pressure from their executives or investors on what their AI strategy is, and there is no AI strategy without a lot of data wrangling and analysis. Someone needs to do that! Industries are drowning in data and are in dire need of professionals who can turn this data into actionable insights. It's a great field to launch into.
You'll be at the cutting edge right now: Data science isn't static; it's evolving alongside other breakthroughs like AI and machine learning. Data scientists right now are getting a lot of leeway to play around with new tools and are given the space to figure out a useful application. There's so much to learn: imagine mastering not just data analytics, but also how to apply machine learning models to predict market trends or improve user experiences. This synergy makes you a highly valuable asset in any tech-driven company.
Stability across diverse industries: Unlike other tech roles that might ebb and flow with market trends, data science roles are consistently in demand across a multitude of sectors. Be it in retail, banking, healthcare, or entertainment, data science skills are universally sought after. This cross-industry demand makes data science skills both versatile and secure.
The core skills you learn in a data science bootcamp – statistical analysis, data mining, predictive modeling – are not just relevant today; they're foundational for the tech industry's future. As we continue to innovate, these skills will remain crucial, ensuring your long-term career relevance and growth.
It's easy(ish) to stand out: Because all of the new AI tools are, well, so new, it's possible to get up to speed on new tooling and be up to par (or even more advanced) than more senior data scientists. It's often the case the full-time data scientists don't have the time to dig into new code libraries, breakthroughs, and news stories, so beginners who spend 100% of their time learning can catch up fast. Although uncommon and not representative of the average person's experience, we've even heard stories where a beginner dove deep into large language models (LLMs) for a few months and as a result became a leader in the field; they were later hired as the head of AI for a large company. Simply keeping up to speed with the fast pace of development can open doors to higher salaries and leadership roles.
It's easier than ever to learn—but it can be overwhelming without a guide: Post-pandemic, the educational landscape has transformed, making learning more accessible. Data science bootcamps have embraced this change, offering flexible online formats. Whether you’re a full-time professional or a student, these bootcamps provide opportunities to learn and advance at your own pace. Bootcamps also typically include real-world projects and case studies, enabling students to apply their learning in practical scenarios. This not only solidifies their understanding but also adds valuable experience to their portfolios, which is a significant advantage in the job market.
However, there aren't that many free online resources that are up-to-date, and what's out there may be overwhelming. Because data science is changing so rapidly, it can be very helpful to have a guide (i.e. a company full-time devoted to educating people in the field) to navigate what's out there. The curriculum of these bootcamps is often developed in collaboration with industry experts, ensuring that the content is relevant and up-to-date with the latest trends and technologies in the field.
Why Data Science bootcamps may not be worth it in 2024
Challenging job market for certain roles: Unfortunately big tech is cutting back on junior engineers, so you likely won't be seeing crazy big tech salaries as a junior data scientist early on. While the field is less congested than, say, junior developer roles, simply completing a bootcamp doesn't guarantee a job anymore. Some bright spots: if you are good at data science, you will very high in demand—you just need to demonstrate your skills in a side project, initial work experience, and/or in the interview. And, if you're not set on working at a big tech company, you will also be in demand as companies are scrambling to add AI to their company to make themselves more competitive.
Costs: Cost of data science bootcamps have unfortunately gone up as interest rates have gone up. It's harder to get approved for a loan and if you do get a loan, you'll have to pay a higher interest rate than you would've have to 2 years ago. The cost of data science bootcamps can be prohibitive for many. Still, there are affordable ones out there that could be a good fit.
Quality and curriculum variability: The quality and relevance of bootcamp curricula can vary significantly. Some might not be up-to-date with the latest industry trends or technologies. This variability means that not all bootcamps provide the same value, and some might not adequately prepare students for the real-world challenges of a data science career.
Finally, data science bootcamps, with their fast-paced and intensive nature, might not suit everyone's learning style. They often require a significant time commitment, which might not be feasible for individuals with other responsibilities.
How to make a decision
We've given you some reasons as to why a data science bootcamp is a good idea and why now might now be the right time. How do you make a decision? Here are some things to consider:
- Timeline: Assess how quickly you need to acquire data science skills. Now is a unique time to join the job market as a data scientist and it could be a narrow window. If you wait a few years, it might close as the job market becomes more saturated with junior data scientists. If you're aiming for a rapid career transition or an urgent skill upgrade, a bootcamp’s fast-paced learning might be ideal. But if you have more time, you could opt for a more comprehensive course at a university or online platform.
- Financial resources: Evaluate the cost against your financial situation. Can you afford the tuition upfront, or do you need to get a loan? With current economic conditions, you can get pre-qualified for free with the school that you choose to see what your loan terms could be. Securing a loan might be tough, and interest rates could be high. Yet, if the bootcamp significantly boosts your earning potential, it would be a worthwhile investment.
- Consider college programs too: At Dreambound we try to provide both bootcamp and college options so you can choose the one that best fits your needs. That way too you can trust we're trying to provide an unbiased recommendation! Bootcamp programs tend to focus on more practical applications, which are key in data science. The programs are also shorter and may do a lot more in the way of real-world projects or job placement. On the other hand, college degrees may be recognized more in the job market and may have financial aid options for those who qualify. However, note that even those who qualify for financial aid may still end up paying more than bootcamp grads.
- Consider other tech bootcamps: Check out, cybersecurity classes, and others. Or, just search all technology programs on Dreambound.
