Tag: language learning

BENEFITS OF LEARNING A FOREIGN LANGUAGE

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.

Top 6 Websites to Find Data Science Freelance Jobs

Freelancing is a great choice, especially today

Photo by Bram Naus on Unsplash

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.

On AngelList, you can find roles for every experience level. Whether you are a fresh graduate, a self-learner, or a professional, you find well-paying roles for your experience. The website has many roles, both remote and in specific locations, with the possibility of being remote.9 Free Quality Resources to Learn and Expand Your Python SkillsLearn Python regardless of your technical background.towardsdatascience.com

№3: Lemon.io

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.

After all, you build your own path to success.

Programming Languages: Choose Wisely?

languages cybersecurity

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.

8 Hardest Languages to Learn In The World For English Speakers

Which languages are the most difficult to learn? You can see where different languages broke off as you peel back the onion to the beginnings of language creation, often known as the ‘Old World Language Families.’ You may now see why Spanish has parallels to languages such as German, Italian, and French. And why Korean is comparable to Mandarin, Japanese, and other Asian languages. We’ll concentrate exclusively on the most difficult languages for English speakers to learn.

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1. Mandarin: Why it’s so difficult: English may be the most widely spoken language on the planet, but it comes with its own set of challenges for native speakers. Because Mandarin is a tonal language, adjusting your tone can give a word a whole different meaning. Thousands of letters, intricate systems, and a wealth of homophones make it one of the most difficult languages to learn in the world.

2. Icelandic: Why it’s difficult: The Icelandic language has remained unchanged since the ninth and eleventh centuries, but it continues to add new meaning to old terms. It also doesn’t help that there are only about 400,000 native speakers with whom you can practise.

3. Japanese: Why is it difficult: There are three distinct writing systems in Japanese: hiragana, katakana, and kanji. Japanese students must first study thousands of distinct characters in these writing systems before they can begin writing. It is, nevertheless, much less difficult to learn than Mandarin!

4. Hungarian: Why is it difficult: As previously stated, most languages are descended from the Indo-European language family. Hungarian, on the other hand, is a Finno-Ugric language in which words are produced separately. To put it another way, it’s not the way English speakers generally construct words or phrases. ‘With my [female] friend,’ for example, is shortened to to ‘barátnőmmel.’ Are you perplexed yet? We’re in the same boat.

5. Korean: Why is it difficult: Korean is an isolated language that is not related to any other language family. There’s more, though. There are seven main speech levels in Korean, which native speakers switch between, depending on the formality.

6. Arabic: Why is it difficult: Despite the fact that there are 221 million native speakers from whom you can learn, Arabic remains one of the most difficult languages to master. First, when writing, vowels are not included. To make matters even more complicated, most Arabic letters are written in four distinct ways depending on where the word is placed.

7. Finnish: Have you ever seen The Lord of the Rings? The Elvish language was founded on the Finnish language by author J.R.R. Tolkien. Finnish, like Hungarian, is a Finno-Ugric language with a lot of grammatical intricacy. And just when you think you’ve figured out how to translate Finnish to English, you’ll discover that current Finnish speakers have their own method of expressing emotions that differs from the standard translation!

8. Polish: Making pierogies is one thing, but speaking the language of the country that produces them is another. The Polish language’s complexity can be divided into two categories. First and foremost, the pronunciation. For novice learners, simply saying ‘hello’ (cześć) is a headache because the ‘c’ and’s’ are pronounced significantly differently than in English. The other is that the Poles have seven different gender-affected grammatical cases and seventeen different cases for numbers. Yes, there are seventeen distinct ways to say ‘ten.’

The main crux is that the most difficult languages to learn for English speakers are determined by a variety of criteria, not just one. The number of speakers, linguistic origins, resemblance to English, and other factors all contribute to how difficult it will be to learn. Every language will have its own set of difficulties, but it will also have its own set of rewards, joys, and fulfilment. Remember that whatever language you choose to study, your time will be well invested.