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action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home2/magnimin/public_html/magnimind_academy/wp-includes/functions.php on line 6114You\u2019ve probably seen the headlines that state the role of data scientist<\/strong><\/em><\/a> to be the 21st<\/sup> century\u2019s 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\u2019s 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.<\/span> 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\u2019t offer major programs or degrees that are designed explicitly for data scientist training.<\/p>\n So, how do you prepare to step into the data science field? Though there isn\u2019t any standard roadmap to follow to become a data scientist, there\u2019re some options used by aspiring candidates like going through the traditional route, becoming a self-taught professional, or attending a data science bootcamp<\/strong>.<\/em><\/a><\/p>\n Among all these options, the last one i.e. attending a data science bootcamp<\/strong> 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.<\/p>\n However, participating in a data science bootcamp<\/strong> and completing it successfully isn\u2019t as simple as many may think and\/or express it through their reviews on the web. In reality, there\u2019re participants who fail to complete the program successfully or fail to make the most out of it.<\/p>\n In this post, we\u2019ve put together five key tips that would help you survive a data science bootcamp<\/strong> and embark on your journey to become a data scientist.<\/p>\n What exactly motivates you to join a data science bootcamp<\/strong>? 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\u2019re high probabilities that things will get tough and you\u2019ll hit inevitable roadblocks, and it\u2019ll be your goals that\u2019ll help you get through.<\/p>\n You should also understand that participating in a data science bootcamp<\/strong> 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\u2019s quite normal if you find yourself a bit overwhelmed. Again, it\u2019ll be your goals that\u2019ll help you maintain focus and encourage you to invest your time and effort on what you want and need to learn exclusively.<\/p>\n A data science bootcamp<\/strong> 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\u2019re trying to emphasize on preparation is because graduating from a data science bootcamp<\/strong> 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.<\/p>\n Ideally, you should have a good understanding of statistics, probability, linear algebra, and Python<\/strong><\/em><\/a>, among others, before attending a data science bootcamp<\/strong>.<\/span> Though there\u2019re 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\u2019re planning to do the data science bootcamp<\/strong> from, it\u2019d be even better.<\/p>\n Put simply, a data science bootcamp<\/strong> offers a great deal of information crammed into a comparatively short amount of time. So, it\u2019s quite normal that no participant is able to maintain the pace always. There\u2019ll be lots of assignments, lectures, sessions, discussions etc which can easily make you feel overwhelmed. Here\u2019re the things you should follow at the very beginning of the data science bootcamp<\/strong>.<\/p>\n 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<\/strong>, being too selective will probably hinder your progress.<\/p>\n Ideally, you should always keep your mind open to more common topics. Even if those subjects aren\u2019t among your preferences, you should focus on mastering them. The program offered at a data science bootcamp<\/strong> is usually well thought out, structured, and aimed to meet the industry requirements.<\/span> So, you should try to learn everything the program offers to make the most out of it.<\/p>\n We\u2019ve already discussed the importance of defining your goals. However, setting unrealistic goals won\u2019t help you reach anywhere, apart from wasting your time, money, and effort that you invest in the data science bootcamp<\/strong>. If you want to stay within your comfort zone, learning can become difficult.<\/p>\n So, you should expect to get hurt by the program every now and then. If it doesn\u2019t happen, you\u2019re most probably not making much progress and\/or aren\u2019t paying complete attention. Ideally, you should try to build a strong foundation with your newly acquired skills in the data science bootcamp<\/strong> 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.<\/p>\n Full-immersion data science bootcamps<\/strong> are intense and it\u2019s quite easy to try to self-protect, and to get defensive. However, the truth is you\u2019re not attending a data science bootcamp<\/strong> to impress someone. So, you must be open to learning and fully admit if you don\u2019t know something.<\/p>\n As we\u2019ve already discussed earlier, participants in a data science bootcamp<\/strong> 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\u2019s important not to compare yourself to others because you\u2019re not there to win a race against your fellow participants. Also, you shouldn\u2019t feel embarrassed to ask questions. Sometimes, the unasked questions are the key to mastering a concept.<\/p>\n 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.<\/p>\n The internet is certainly a treasure trove of information. So, it\u2019s obvious that every aspiring data science professional searches it first when s\/he plans to attend a data science bootcamp<\/strong>. With the skyrocketing demand of data scientists, there\u2019s a lot of schools that have started organizing data science bootcamps<\/strong> 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<\/strong>. Let\u2019s have a quick look at them.<\/p>\n While data science bootcamps<\/strong> are significantly more affordable compared to other traditional programs, the cost has to be within your budget.<\/span> Also, there\u2019re 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.<\/p>\n Put simply, data science bootcamps<\/strong> aren\u2019t 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.<\/p>\n Also, sometimes data science bootcamps<\/strong> don\u2019t count students who don\u2019t remain in touch with them when calculating the success rate. So, don\u2019t blindly trust the numbers you\u2019re 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.<\/p>\n While a data science bootcamp<\/strong> is intensive and needs a participant\u2019s complete attention to help him\/her proceed toward success, they\u2019re 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<\/strong><\/em><\/a> experience will surely be excellent.<\/p>\n1- Define your learning goals<\/em><\/strong><\/h3>\n
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2- Understand the power of preparation<\/em><\/strong><\/h3>\n
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3- Work hard to keep up with the pace<\/em><\/strong><\/h3>\n
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4- Be ambitious but understand your limits<\/em><\/strong><\/h3>\n
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5- Leave your ego at your home<\/em><\/strong><\/h3>\n
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6- Key things to keep in mind when selecting a data science bootcamp<\/em><\/strong><\/h3>\n
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6.1- Cost<\/em><\/h4>\n
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6.2- Success rate<\/em><\/h4>\n
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Wrapping up<\/em><\/strong><\/h3>\n
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