People tend to increasingly share their data science certifications on social media with each other these days, mostly in the study groups on Facebook and LinkedIn.
So, in this piece, we will examine if it is worth getting certified, what employers are looking for and how to build a strong resume for data science.
First off, Making a data-career transition or getting a data science Job as a fresher or even an Internship in the market today is exceedingly challenging as this Pandemic has changed everything.
However, the emerging growth of tech is faster each day than ever before.
Covid-19 has upgraded the landscape for its growth and disrupted everything down to lives of individuals, who now work remotely and meet online.
My aim in this article is to highlight reasons why your data comprehension will surpass the need for validation to get a good data science Job,
And how connecting to the right channels will decrease distraction from the increasing sentiment for sharing achievements, aggressively crowding the timelines of many people.
So, let’s dive in to understand more how data science certifications may and may not be helpful.
How building a strong resume for data science surpasses the need for certifications ?
People who work to hire, spend their time carefully evaluating, they make data-driven decisions to hire people who can work on data science projects.
But when people struggle to reach and communicate clearly with the employers through the right channels, they resort to spreading and circulating certificates and resumes.
And, with so many hacks on going viral and getting attention, learners drift from the quality work and start aiming for the low hanging fruits, eventually becoming complacent.
It’s like sojourning through the virtual ocean of mediocrity and exploring through it.
Public display of the Data Science Certifications never attract quality people to connect but it furthermore distracts learners from connecting to the right channels b’coz when the time spent on making social media is prioritised over researching on some datasets, then the results are likely to be fruitless too.
So, No, Data Science Certifications will never be enough.
But Yes, It is not a bad idea to highlight on your resume that how any particular course helped you to build the sound machine learning skills and working on the data science projects helped you to grow intellectually and if any book changed your mindset to write better Python code.
In the end, It essentially boils down to how well you manage your time, and evaluating your circumstances to grow intellectually.
And, If you do the things that support your data-career growth, then you’ll work to make your resume strong.
—How can you build your resume for data science ?
If you manage your time with labor in practice, you’ll inculcate data intuition with heightened sense of understanding about how to make use of your skills and learn how to solidify those skills.
For e.g; If you know statistics, then you’d know why you cannot underestimate the significance of maths in data science otherwise you’ll get awfully stuck when working through the libraries that require sound math skills.
So, the more time you spend practicing how to write effective programs to become highly prepared to work on the models, you’ll also have the skills to communicate yourself clearly.
And, If you can express yourself clearly, you’ll write a stronger resume and its also b’coz hard-work seriously pays off.
It’ll provide you the edge you need to have at interviews.
Plus, speaking about the quality resources in your interviews could bootstrap your chances on getting opportunities, and highlighting your certifications and micro-degrees can be helpful in a gentle way by not making a big deal out of it, as that could be misleading.
HR professionals have already developed a data-driven approach for selections and they are well aware about the increasing number of people especially software engineers being very complacent about Information and Security.
Take a look at following Data Visualizations for the insights on how the U.S government is investing billions to prevent and minimize digital attacks.
Cyberwar is a very a serious problem and no leader in the right mind can be complacent about the rising risks.
So, companies don’t underestimate the importance of Cyber Security because the governments across the world are very serious about it,
And they allocate the necessary budgets based on the threats and Incident reports prepared by any data practitioner.
So, If you learn to see that risk by doing a lot of research, you’ll see why you need sound skills to write secure code and become highly prepared to collaborate with the Security Researchers.
And, with an Insatiable curiosity to learn, you’ll understand the landscape more and more each day, and learn to work with all your natural abilities which builds you a stronger resume.
—Building a strong data science resume with efforts
Nice resumes never highlight how you’ve learned to write better code or how critique helped and is helpful to you.
Employers don’t want certifications, they need people who know how to work on the data science projects and communicate, exert less in thinking to use data insights to make the sound decisions for building very secure products.
At the end of the day, someone will have to take a look at the knowledge you possess by looking at your resume.
So writing a simpler resume will make it easier for your potential employer to see how much you’ve dedicated yourself to a career in data science and they’ll only spend seconds looking at your resume, not minutes.
You can do simple things :) b’coz you can experience freedom in discipline to build data science skills by investing your efforts to stay on the data science projects while staying close to the conductive environment that supports your mental hygiene for the cognitive growth you need.
So this is why you should maintain a good Github profile, engage in data science communities, write for data science publications, use datasets to create compelling data visualizations and most importantly remain updated about the latest business trends.
And, you should highlight to express how any particular course helped you to change the way you think, what you learned about the programming, or even how it helped you to overcome some learning obstacles.
So, when you publish your articles and research, you’ll get noticed and the thing that you need the most is not appreciation but critique to seek a data science Job.
—How do you seek Data Science Jobs ?
If you want to be ready for the data science interviews, You’ll have to spend your time learning how to learn and correctly apply through the right channels.
It’s good to seek a critique from your mentor and not your interviewer, b’coz that inconsiderately leads the conversation according to your direction.
Being considerate pays off.
Your interviewer who is spending time to understand if you can be integrated in their teams will need you to make sense of your resume through the words you speak b’coz they’ll need you for the research.
This is why you’ll have to learn to determine what employers are seeking when, what they say that they are seeking in their Job openings.
So, dedicating time to complete a course and getting certified is not sufficient to get you through any interview, as they are useful only for examining your skills sometimes.
You’ll still have to demonstrate a certain level of understanding that you’ve acquired throughout your data science learning.
Since the pandemic has evidently drifted people to tech, there is good reason to stay away from the cringe-fest on social media.
Instead, you could think how to build the true confidence to speak how critique helps you b’coz employers are well aware that even a perfect data science course is not sufficient to make you aware about the landscape, but critique does inspire you to begin enquiring.
You’ll be able to understand the landscape yourself but the thing that you need the most for your honest desire to grow is curiosity.
Curiosity leads you onto to explore, learn and grow,
And one way to become more curious is to continue writing and share your work publicly to become better by receiving critique.
This way you’ll examine your skills and learn how much you know and how much you could do to improve your data science skills.
If you are becoming better each day at programming, then you are improving your chances, significantly.
Writing will also help you with the stillness and make you aware about what you are doing and positively help you to keep track of your own progress.
Indeed, Excessive sharing of Certifications have become a social norm, but they don’t actually express your qualifications.
You can have certification and still possess mediocre skills but on the other hand have no certification and be pristine.
Thanks for making it to the end 🙂
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