Five months into the lockdown, companies are continuing to cut down their business cost by either slowing down their hiring process or laying off their employees. However, despite this uncertainty, experts believe that jobs anchored around analytics, data science and AI are still better positioned. Nevertheless landing onto one amid COVID pandemic demands knowledge of advanced skill sets, and to achieve that self-learning can be the only efficient way.
In fact, due to the challenging times, it gets even difficult for organisations to provide necessary upskilling resources to their analytics professionals. And therefore, self-learning can prove to be immensely beneficial for keeping their relevance in the post-pandemic world. According to data, revealed by Analytics India Magazine, this COVID pandemic has forced 76.9% of the analytics professionals to invest their time on training through self-learning.
Self-learning can be the last resort for professionals who are willing to translate into data science amid this pandemic crisis. And in this article, we will discuss a few effective self-learning ways for data scientists.
Grab Some Online Certifications
Certifications have always been imperative for data scientists to get a job, whether it be pre- or post-pandemic world. However, currently, the learning process becomes siloed, and thus requires more effort from the learners. Having a university degree can definitely provide knowledge and lay a foundation, but doing a certification program will actually act as a testimony on your resume for that particular skill and would provide a competitive advantage. Not only will it demonstrate the completion of a course but will also encourage learners to put that extra effort in learning to obtain certificates.
That being said, it is critical for these data science learners and professionals to choose the right certification program among the many in the market. Also, with data science being a vast field, it is necessary for these self-learners to create a plan to manage their time and get the best out of these certification programs. Relevant certification programs would not only help these self-learners to gain proficiency in necessary skill sets but would also boost their resume for recruiters.
Apply Your Skills In Building Projects
Another way one can enhance their self-learning process amid COVID is by building personal projects, which can later be highlighted in the resume to impress the recruiters. Projects have also been a vital part of a data scientist’s life. Not only it helps in enhancing technical and programming skills but also makes these learners experience how the real world of data science looks like. Majority of these projects are similar to real-world business problems, and thus working on these could help these newbies understand the workflow more comprehensively and urge them to use their skills for practical problems.
Furthermore, these learners and professionals can also contribute to open-source projects, where they would be required to provide code or solutions to real-world business problems. GitHub could be an excellent source for these learners to get their hands dirty with open-source projects. This would encourage them to understand how business works and how to communicate with other team members for obtaining the necessary information. Building projects and contributing codes will help these self-learners to work in the field and augment their learning process.
While learning via projects and certifications is fundamental for data scientists, it is also critical that these learners and professionals keep applying these skills in the real world. This can be done by taking up freelance gigs for short term projects which can help in enhancing the skills that were learnt while building projects and passing exams. Having relevant freelancing experience not only allows these learners to showcase their learnt skills but also provides them with an upper hand among others with just degrees and certifications.
Additionally, freelancing experiences in a particular domain would also create possibilities for self-learners to land on a job that is relevant to the experience. Self-learning can be challenging even for the experts of the field, and that’s where freelance jobs would help in enhancing those learning and giving more confidence to professionals to deal with the real world.
Participate In Competitions For Better Exposure
Another way of applying the gained knowledge and skills learned in the real world scenario is by participating in competitions. This will enhance the whole process of self-learning by allowing these professionals to compete with the best minds of the industry. Winning is not the purpose here, however participating in competitions and hackathons like these will provide immense exposure to these self-learners and competing under time pressure will give a whole new perspective towards the data science industry.
Hackathons not only provide an opportunity for self-learners to collaborate with others but also allow them to create real-world projects that can actually provide business value. Moreover, hackathons would offer a comprehensive knowledge of the overall workflow of building models and releasing it for organisations. In addition to that, hackathons also act as a critical platform for recruiters to hire data scientists and to participate in one amid COVID could be an ideal opportunity for data scientists to land on a job.
Check out MachineHack.
Learn From Meet Up Buddies
Self-learning can be a disjointed experience for many newbies and amateurs, and that’s where meetups and tech conferences come into the picture. These tech meetups and data science conferences can act as an excellent platform for self-learners to come out of their isolations and network with professionals with similar interest. Along with that, the talks and workshops from the experts of the industry separately provide hands-on experience on important subjects.
Also, with a huge number of resources available to learn data science, it gets overwhelming for professionals, thus with the help of networking buddies, one can clear their doubts, debate concepts and can also practice their skills with them. Such type of learning would be necessary to avoid the confinement that self-learning brings in. And for this reason, self-learning data scientists must join in meetups and visit data science conferences virtually to enhance their knowledge.
Check out Computer Vision Devcon 2020
Learns From Mentors
Data science is a complex field, and thus it is advisable for beginners and newly transitioned data scientists to take help from some experts of the industry. This is what is the job of a mentor, to add value to the self-learning process data scientists are doing amid this crisis. A good mentorship will not only provide comprehensive feedback to enhance the learning process but also guides amateurs towards necessary job prospects in the industry.
Sharing relevant interests, expectations and doubts with mentors can help self-learners to understand specific problems of the field. Also, different mentors specialise in different skills, and thus one can also avail mentorship for different aspects of data science to get the best out of the whole process. Mentors can also help these self-learners to network with potential employers who can help them to land on a job despite this uncertain time. Thus, mentorship can prove to be immensely beneficial for data scientists, despite their expertise and interest.
Join AIM Mentoring Circle