Aquisition of a different language in the globalized era is indeed beneficial. The world is in a phase where geographical mobility is quite simple and knowing a foreign language will help one to expand his/her horizons in the long run.
THE VARIOUS BENEFITS OF A LEARNING A FOREIGN LANGUAGE ARE AS FOLLOWS :
Enables easy travel – One will find it hassle free to travel across the globe by acquiring a new language. It will make traveling enthralling as one can easily interact with the locals of a particular place and learn about their culture, traditions, norms, etc.
Career Prospects – Companies that are willing to expand their business to other regions are constantly looking out for professionals having foreign language skills. Being multilingual can add up grace to one’s resume and open opportunities for pay hike and added incentives.
Boosts comprehension and listening skills – People having a vocabulary of more than 2 languages often end up working hard to distinguish sounds and pronounciations in different languages. The brain thus develops in such a way that it helps boost comprehension and listening skills in a person.
Deepens cultural knowledge – Language is a core cultural heritage of several nations. Thus, the best way to connect to the culture of others is by learning their language. By conversing in a nations’s mother tongue, we tend to comprehend their motives and cultural aspects in a much better manner. Studies have proven that this tends to nurture a sense of empathy amongst people. According to Karl Albrecht, “Learning another language is not only learning different words for the same things, but learning another way to think about thinks.”
Prevents Alzheimers/Dementia – Bilingual folks have a lesser chance of developing alzheimers/dementia. Knowing different languages strengthens the Cognitive Reserve of the brain. This in turn leads to a greater blood flow and increased activation of the neurons. Thus, it helps prevent brain related disorders.
Helps increase span of attention – Trying to learn a varied language helps exercise the brain functions in a precise manner. It challenges one to concentrate and improve problem solving skills. In this way, it enhances the memory and builds the ability of a person to learn vocabulary, problem solving and math in an easier way.
Recreational purpose – Linguaphiles (those who love words and languages) may try learning numerous languages as a part of their hobby. One can effortlessly read literature, watch shows without having to go through subtitles, write articles/blogs in the language that they have learnt. Thus, such language lovers can constructively utilise their time by indulging in such language related activities.
May help bind the world – An Arab proverb says, “learn a language and you’ll avoid a war.” Learning a new language helps understand other peoples culture. Hence, it will aid people to think rationally, logically and through a global perspective without prejudices or biases. This may in turn help prevent communal or ideological conflicts within the globe.
Marcel Proust has rightly quoted, “A language which we do not know is a fortress sealed.”
It is true that aquiring a new language opens doorways to golden opportunities in life. Multilingual people have a positive influence on their social, psychological and emotional development. Therefore, we can conclude that, learning a foreign language is truly beneficial in all terms.
As professional or aspiring data scientists today, we face so many challenges: Learning new skills, improving existing skills, building a strong professional network, job hunting, and landing a role. Data science is one of the glamorous tech fields at the moment, from being an analyst to deep learning professional. The resources to learn are many, the interested candidates are there, but the job availability is not always a match.
To move on in your career, especially in data science, you need to build more projects, hone your skillset, and prove your value as a data scientist. But, how are you going to do that if you can’t find a job or if you weren’t given a chance to put your knowledge to use and prove you can use it correctly?
One of the great options to improve your skills, gain experience, strengthen your portfolio, and have an income is freelancing. Personally, I am a big fan of freelancing; although I am fully aware that succeeding as a freelancer is not easy, it’s very doable. As a freelance data scientist, you can choose the projects that you find interesting and really want to work on. You can also set your hourly pay, and most importantly, you get to be your own boss.
Perhaps my favorite thing about being a freelancer is the freedom of time. You get to choose when to work and when to take some time off, which is not always an option in regular 9-to-5 jobs. So now, you probably have a few questions, like, how do I get started with freelancing? Where do I find a freelance role (a gig)? What kinds of gigs exist out there?
I answered the latter question in another article, and I will write one answering the first question later this month. But today, let’s focus on the middle question, “where can I find and browse available data science freelance gigs?” So I will focus today on the top 6 websites you can use to find freelance data science roles.
№1: LinkedIn Job Finder
I will start with a great website that is often ignored, especially when looking for LinkedIn freelance gigs. Of course, we all know the professional networking website, and some of us have found our full-time job on LinkedIn. But, LinkedIn won’t probably come to mind if you’re looking for a freelance project.
LinkedIn can be used to look for freelance jobs; the trick is to filter the role type to “contract” or “temporary” only to see the freelance roles. Another good thing about using LinkedIn to find freelance roles is that you can set your experience level only to see jobs that match your skillset.
№2: AngelList
Next up on the list is a website very popular with startups, AngelList. AngelList is one of the top websites to find freelance tech roles in general and data science ones in particular. So, all you need to do is build a potent profile and start browsing available roles.
My next website is not your typical freelance website; it’s a community of developers and startups, Lemon.io. We all understand the importance of community, of belonging especially in the freelance world. However, being a freelancer may feel lonely; Lemon tries to overcome that by building an exclusive community.
In Lemon, you can find different freelance roles for all tech specialties, from pure Python to web dev to data science, with hourly pay anywhere from $35~ to $55. To ensure quality, you will need to pass a simple English test and technical interview with one of Lemon’s developers to join Lemon.
№4: Toptal
When you ask an experienced freelance data scientist to recommend you a website to find roles, one of the websites that you will hear often is Toptal. Toptal is a remote talent company that aims to match skilled people with projects that match their skillset.
Toptal is more than a hiring website; it offers many resources and events to improve your skills and learn more about the future of work. Once you pass the initial screening and based on your experience and skill level, you can have an hourly rate ranging from $20 to $100+.6 Lesser-Known Data Science Blogs That Are Worth Followingtowardsdatascience.com
№5: Upwork
Next on today’s list is a website famous for being the freelance holy grail, not just tech freelance, but any freelance out there, Upwork. Create a profile, pass the screening, start browsing available roles, or just wait for clients to contact you.
In Upwork, you can mainly find two types of jobs based on payment: fixed payment and flexible roles. The fixed price has a fixed price to a specific amount of hours, while the flexible ones have average hourly pay starting from $20 and up.
№6: Kolabtree
Last but not least is a freelance platform with over 20,000 scientists and experts on board, Kolabtree. Kolabtree connects freelancers of all levels of experiance to businesses of all sizes from all over the world, with hundreds of projects are posted every month, and you can filter it by the exact topic you want to work on, like data science or a more specific subject areas.
Kolabtree is free to signup for and starts applying for projects with an hourly rate starting from $30 on data analysis, machine learning, and statistical analysis projects.
Final thoughts
As a data scientist myself and a computer science instructor, I fully understand the frustration of applying to tens of jobs and sometimes not hearing back from any. I know what it is like to feel unworthy and not enough, skilled enough, smart enough, and good enough. Unfortunately, the current way job hunting work tends to strengthen this feeling of unworthiness and leave the applicant mentally tired.
But, one of the ways I was able to overcome that feeling of being unemployable is freelancing. So, I decided to get out of the job-hunting world and make my own path to prove myself, to myself first, and to employers out there. I made a profile and started doing freelance projects. I started small, and the size of my projects and my skills grew with time.5 Python Books to Transfer Your Code to The Next Leveltowardsdatascience.com
So, if you reached a good point in your learning journey or got tired of your company and looking for something new, something challenging and rewarding, I suggest you give freelancing a try. Check the websites I proposed in this article out, and maybe you will find a gig that matches your skills and that you will feel excited about.
We’ve got decades of experience in programming and language adoption under our belt at this point, and there are a few things we can say definitively that developers in general (and DevOps engineers specifically) should be aware of.
First, it doesn’t matter as much as you think. It really doesn’t. Most developers don’t choose programming languages based on important things like optimization or general applicability. They choose a language based on ease of use, availability of third-party libraries and simplification of things like UI. Open source version availability helps, but only insofar as it spawns more third-party libraries. So, use the language that works best for the project, and don’t get too hung up on whether or not it’s the newest shiny one.
Second, the changes in use and adoption that matter–the top five to 10 languages that make up the vast majority of all professional programming activity–don’t happen overnight. Both JavaScript and Python are considered “rapid ascent” in terms of uptake when they took off … but both were around for years before that spike in adoption occurred. So, learning any of the top few languages is a far better long-term investment than learning the hottest new language.
Third, those top languages actually don’t change much. They were written to fulfill a need, and that doesn’t change much over time. Indeed, the only language I can think of that has fundamentally changed in its lifetime is C++, which seems to want to keep up with the times rather than keep serving its original niche. Python? Java? Still pretty much the same as when they became popular back in the day. And that’s a good thing. But that means if you want to try something new and engaging, you need to look to up-and-coming languages. At the time of this writing, specialist languages like R and Kafka are having their day, and that’s a good thing. After all, we know that different applications have different needs and different platforms have different needs–and have been trying to address that second one forever, currently with languages like Flutter. All of these will offer new ways of doing things, which is good exposure.
Fourth, (though we briefly toyed with eliminating this one) organizations do determine the pool of available languages. Frankly, allowing each team to build a separate architecture was never a good idea from a long-term maintenance point of view … but a fairly large number of organizations played with the idea and learned the lessons about technical debt all over again. Now we’re back to “We use these languages, pick one,” which is better than “We’re an X shop,” and offers maintainability over time without burning a ton of man-hours.
And finally, you can do anything with those languages your organization makes available. I’ve seen object-oriented assembler, I’ve seen entire websites served in C; the list goes on. The language you choose makes certain things easier or harder, but if you need to get it done, you’ll either get an exception to the language list, or you’ll figure out how to get it done with what’s available. But you can … But as my father used to love to say, “Just because you can, doesn’t mean you should.” He had nothing to do with programming and as little as possible to do with computers, but his logic still applies perfectly.
So, grab an approved language, and crank out solutions. Just keep driving it home; you’re rocking it. Don’t stop, and don’t worry too much about which language you’re using, just focus on the language and do what needs doing–like you’ve done all along. And spin us up even more cool apps.
‘I’m learning a new language’ feels good to say right. When you tell other people that you are learning a language and they go ‘Awe that is awesome! But isn’t it difficult’ and then you reply ‘Nahh, it’s so easy and interesting (yes, I’m a born genius (ツ))’. But who are you kidding, learning a new language is hell of a difficult job to do!!
When I started learning Japanese it was very fun, easy but as I progressed further it started becoming tough; tough, yes BUT interesting. You have no idea how good it feels to be able to watch anime without subtitles. Okay, okay sometimes I do need subtitles because I am still learning but you have to agree starting to understand a different language other than your own does feel like a great accomplishment, doesn’t it.
Now as to why I started to learn Japanese, because I AM IN LOVE WITH JAPAN, always have been ever since I was 10. I was always fascinated by it. I wanted to learn more about the country and still learning. I was a student of economics, yes I studied economics first, graduated and then currently doing my second graduation in Japanese. All of the people around me asked me ‘what the hell are you doing?’ ‘Shouldn’t you be doing your post-graduation?’ ‘Why are you wasting your time?’ and I had only one answer ‘BECAUSE I WANT TO¯\_(ツ)_/¯’.
But the truth is I realized it a little late what I actually wanted to do. I took economics because it was a very trending course and everyone around me was doing it (luckily, got the percentage for it) but after 3 years of studying I realized this wasn’t what I should be doing because I was not able to see myself anywhere. The initial idea was to learn Japanese as something extra outside of my normal academic life but it turned out to be something that I should have been doing all along. So I did. After graduating I told my parents I want to do another graduation and they happily agreed. Then for the first time in my life I had the answer to the question-‘Where do you see yourself in the next 5-10 years’. The picture has finally become clear to me. So do what you want to do, then only you will be able to look in the future and see yourself standing where you actually want to be. No regrets.
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