You’ve probably seen the headlines that state the role of data scientist to be the 21st century’s sexiest job and are somewhat aware of the excellent pay packet coupled with other perks and excellent future prospect that a data scientist can enjoy.
In today’s data-driven economy, businesses across the globe are constantly searching for good data scientists who can turn the huge amount of data into valuable insights.
So, no wonder why people from a diverse range of fields are gearing toward a career in the field of data science. Unfortunately, a majority of the universities don’t offer major programs or degrees that are designed explicitly for data scientist training.
So, how do you prepare to step into the data science field? Though there isn’t any standard roadmap to follow to become a data scientist, there’re some options used by aspiring candidates like going through the traditional route, becoming a self-taught professional, or attending a data science bootcamp.
Among all these options, the last one i.e. attending a data science bootcamp has become the most preferred option among aspiring candidates. This is because these programs offer a multitude of benefits that are impossible to find if you follow any other option.
However, participating in a data science bootcamp and completing it successfully isn’t as simple as many may think and/or express it through their reviews on the web. In reality, there’re participants who fail to complete the program successfully or fail to make the most out of it.
In this post, we’ve put together five key tips that would help you survive a data science bootcamp and embark on your journey to become a data scientist.
What exactly motivates you to join a data science bootcamp? To switch into the data science field, expand your present skills, or just your personal interest? Write it down and review it frequently. Because there’re high probabilities that things will get tough and you’ll hit inevitable roadblocks, and it’ll be your goals that’ll help you get through.
You should also understand that participating in a data science bootcamp may sometimes feel like a difficult task. This is because participants of the program come from different backgrounds and with different levels of strengths and weaknesses. Given the wide spectrum of addressed topics, it’s quite normal if you find yourself a bit overwhelmed. Again, it’ll be your goals that’ll help you maintain focus and encourage you to invest your time and effort on what you want and need to learn exclusively.
A data science bootcamp is an intensive, fast-paced course where you get to learn both technical and non-technical skills that are relevant to the present-day data science industry. However, the reason we’re trying to emphasize on preparation is because graduating from a data science bootcamp successfully is difficult. While these programs greatly help aspiring data science professionals to step into the field by eliminating the need of following a complicated degree path, having a little bit of preparation can go a long way in sailing through the program.
Ideally, you should have a good understanding of statistics, probability, linear algebra, and Python, among others, before attending a data science bootcamp.
Though there’re some good amount of resources available that would help you to gain this understanding, taking online courses is probably the best one among them. If you can pursue a data science preparatory course from the same institute where you’re planning to do the data science bootcamp from, it’d be even better.
Put simply, a data science bootcamp offers a great deal of information crammed into a comparatively short amount of time. So, it’s quite normal that no participant is able to maintain the pace always. There’ll be lots of assignments, lectures, sessions, discussions etc which can easily make you feel overwhelmed. Here’re the things you should follow at the very beginning of the data science bootcamp.
- Start your assignments from the day they’re given to you. You don’t need to finish them immediately but something like going through them thoroughly will make them much easier and will also help you get an overview of them.
- When you’re participating in a data science bootcamp, falling behind isn’t an uncommon thing. However, when you actually do, it’s important to manage your current assignments. Participants usually fall behind on something they find more difficult. While it’s quite tempting to try to complete the earlier things before working on your present assignments, you shouldn’t do that. Instead, you should focus on the current ones so you don’t fall behind further.
Apart from assignments, you should also try not to be too selective about the things you need to work on. Remember that since you get only a fixed amount of time in a data science bootcamp, being too selective will probably hinder your progress.
Ideally, you should always keep your mind open to more common topics. Even if those subjects aren’t among your preferences, you should focus on mastering them.
The program offered at a data science bootcamp is usually well thought out, structured, and aimed to meet the industry requirements.
So, you should try to learn everything the program offers to make the most out of it.
We’ve already discussed the importance of defining your goals. However, setting unrealistic goals won’t help you reach anywhere, apart from wasting your time, money, and effort that you invest in the data science bootcamp. If you want to stay within your comfort zone, learning can become difficult.
So, you should expect to get hurt by the program every now and then. If it doesn’t happen, you’re most probably not making much progress and/or aren’t paying complete attention. Ideally, you should try to build a strong foundation with your newly acquired skills in the data science bootcamp when doing assignments during the program. In addition, to make steady progress, you can deal with the highest-risk problems first and then move on to the easier ones.
Full-immersion data science bootcamps are intense and it’s quite easy to try to self-protect, and to get defensive. However, the truth is you’re not attending a data science bootcamp to impress someone. So, you must be open to learning and fully admit if you don’t know something.
As we’ve already discussed earlier, participants in a data science bootcamp can come from a diverse range of backgrounds. So, some may learn faster or already have more experience with the fundamentals than you do. It’s important not to compare yourself to others because you’re not there to win a race against your fellow participants. Also, you shouldn’t feel embarrassed to ask questions. Sometimes, the unasked questions are the key to mastering a concept.
Apart from these tips, you should take some time out to review your progress. So, go back and review earlier lessons from the program once a week at the least. This proactive methodology helps to strengthen your concepts and accelerates your learning. Eventually, your response to certain challenges will become automatic.
The internet is certainly a treasure trove of information. So, it’s obvious that every aspiring data science professional searches it first when s/he plans to attend a data science bootcamp. With the skyrocketing demand of data scientists, there’s a lot of schools that have started organizing data science bootcamps though some of which may not be able to rise up to the expectations of the participants. So, we strongly suggest you to focus on some critical factors before investing your money, time, and effort in a data science bootcamp. Let’s have a quick look at them.
While data science bootcamps are significantly more affordable compared to other traditional programs, the cost has to be within your budget.
Also, there’re programs where additional days bring additional costs in different ways that you may not have calculated before joining the program. So, it pays to make all these things clear before getting enrolled.
6.2- Success rate
Put simply, data science bootcamps aren’t for everyone and not every participant gets a job after finishing such a program. This happen mainly because the success rate depends on the efforts given by the participants to a great extent.
Also, sometimes data science bootcamps don’t count students who don’t remain in touch with them when calculating the success rate. So, don’t blindly trust the numbers you’re being given. Instead, ask questions like if the figures includes every participant who enrolls for and completes the bootcamp, or if it takes into account just the people who got a job after doing it.
While a data science bootcamp is intensive and needs a participant’s complete attention to help him/her proceed toward success, they’re really powerful at the same time. So, remember the above tips, try to adopt a growth mindset, work truly hard, and take your time to rejuvenate in-between the information-packed study sessions. This way, your data science bootcamp experience will surely be excellent.