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Who doesn’t love a good mystery, especially one that stumps researchers?

Popular Science‘s editor-in-chief, Cliff Ransom, moderated a panel about such seemingly inexplicable phenomena this weekend at Comic-Con in San Diego. The occasion: the debut of the Science Channel’s second season of “The Unexplained Files,” which premieres tonight (July 29) at 10 p.m. ET/PT.

We thought it was fine occasion to ask, “What are some phenomena that science can’t yet explain?” Below are five of our favorite enduring mysteries.


1. Why People Yawn

You yawn, I yawn, we all yawn. Reading or thinking about it makes you more likely to yawn. (Did you just yawn?) You can even “catch” yawns from other people, and from other animals like dogs. Thanks, biology—but what purpose does yawning serve?

Ideas abound, but none seem to hold up to scientific scrutiny. One is that yawning helps to cool the brain by increasing blood flow to the jaws, neck, and sinuses, and then removing heat from this blood when inhaling a big breath. Counterintuitively, yawning occurs less frequently in hot weather, when air has less ability to cool the body. In short, yawning “fails precisely when we need it,” Dr. Adrian Guggisberg told WebMD. One hypothesis that has not (yet) been discarded: yawns “serve as a signal for our bodies to perk up, a way of making sure we stay alert,” Maria Konnikova wrote in The New Yorker. “A yawn is usually followed by increased movement and physiological activity, which suggests that some sort of ‘waking up’ has taken place.”

And why are yawns contagious? A recent study in PLoS ONE suggests they’re way of showing empathy. But another newer study concluded the opposite. So it goes.

Patrick Swayze as a ghoul in the movie “Ghost.”

2. Ghosts

“Alright,” you might say, “I understand that yawning thing, but ghosts don’t exist.” Well, a plurality of Americans—48 percent, in fact—believe they do, according to a CBS News poll in 2005. Most women—about 56 percent—believe in ghosts. And more than one-fifth of people CBS polled say they’ve seen or felt the presence of a ghost.

Modern scientists haven’t delved into this topic all that much, but a few compelling explanations exist. One has to do with infrasound, or low-frequency sounds inaudible to humans but that storms and even household appliances can generate. Such rumbles can vibrate human organs and make people feel a sense of unease. Infrasound vibrations can also mess with vision and make people think they are seeing things. Another idea is that drafts may create “cold spots” thought to be signs of spirits. A final theory is that some observations of ghosts may have been due to hallucinations caused by carbon monoxide poisoning.

One stage productions’ (creepy) interpretation of what déjà vu looks/feels like. Yohanntd via Wikimedia Commons CC3.0

3. Déjà Vu

You’ve probably had this feeling before: As something happens, you feel you’re reliving a past moment. What causes this eerie feeling of déjà vu? In short: No one is certain, but some ideas exist.

One study, which placed people in a virtual computer world, hints that the feeling triggers most frequently when a person encounters a place that’s similar in layout to another place he or she has visited, but doesn’t consciously recognize. “One reason for the jarring sense that accompanies déjà vu may be the contrast between the sense of newness and the simultaneous sense of oldness—something unfamiliar should not also feel familiar,” cognitive psychologist Anne Cleary at Colorado State University told Scientific American. Another study found that one healthy male subject experienced a strong recurrent sense of déjà vu when he took two drugs to ward off the flu. Déjà vu might also come about when the brain improperly encodes a new memory, or when it misfires when establishing a sense of familiarity.

A grainy image of Sasquatch from the Patterson-Gimlin film, which purports to show Bigfoot. Wikimedia Commons

4. Bigfoot

Bigfoot is a creature of many names — Sasquatch in the Pacific Northwest, Yeti in the Himalayas, “wild man” in Central Asia, and (my favorite) “Yowie” in Australia — but science knows it as a cryptid: a type of animal whose existence hasn’t been proven. Definitive proof of Bigfoot has never been established, but as scientists have been known to say, “absence of proof isn’t proof of absence.” Many speculate that Bigfoot sightings often involve large animals that could be mistaken for humans, such as bears. One recent study looked at DNA from hairs, which allegedly came from a large human-like beast. The study found that the hairs came from “raccoons, sheep, bears, dogs, humans and more,” the New York Times reported. (Bigfoot was not listed.)

Spinal Placebo

Pain relief through the placebo effect may take place in spinal cord cells

5. The Placebo Effect

You surely know about the placebo effect: If you truly think something will have a particular somatic effect (like reduce pain), it probably will—even if it is just a sugar pill and has no pharmacological activity. For this reason, placebo pills are used in all legitimate medical studies, to prove whether or not a drug actually has an effect that isn’t psychological. The placebo effect is actually more puzzling than you might expect, though—recent work has shown, for example, that it even works when participants are told they are taking a sugar pill. It also works for sleep. If you believe you got a better night of sleep compared to others who slept the same amount, you are more likely to perform better at a variety of tasks.

There are some clues here and there as to how it might work. For example, one study found that in people given fake pain-relieving cream experienced less activity in pain-sensing regions of the brain. Another found a similar fake cream activated cells in the spinal cord (see the above image). But how the exact process maps across a whole host of experiences—from fighting infection, to performing better on tests, to sleeping better—nobody really knows.

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Inpixio Photo Clip 7: A Fully Featured Yet Simple Photo Editing App

With smartphone cameras becoming better and better, and standalone cameras becoming more affordable, there’s no denying the fact that we take a lot of photos and while there are a ton of photo editing apps for phones out there, I like editing my photos on my Windows 10 PC. While you can always use editing software like GIMP or Photoshop, they might seem a bit too complex. Thankfully, there are other decent photo editing solutions out there. Today, I’d like to recommend a photo editing tool for Windows that I think is great. I’m talking about the InPixio Photo Clip 7, which brings a number of cool features that you will definitely like. So, let’s get into the details of the software, shall we?

Key Features

As I mentioned, InPixio Photo Clip 7 brings a number of cool features to the fore. So, let’s take a look at some of the key features:

Photo Eraser

There are always times when a perfect photo is ruined by an unwanted object in the background. Well, this is where the “Photo Eraser” tool from InPixio Photo Clip 7 comes into play. The tool lets you remove any unwanted things in the background and that too very very easily, unlike most other tools out there. While it removes distracting objects from the background automatically, you can also choose to manually paint a part of the image to another part in the image.

Photo Cutter

Various Photo Effects and Textures

As you’d expect, InPixio Photo Clip 7 also includes a very capable photo editor. The “Photo Editor” brings a ton of effects to choose from. There are effects in different categories, like Lomo, Black & White, Vintage, Portrait, Photography and more. Plus, you can make various adjustments to the temperature, hue, brightness, saturation, clarity, highlights etc. That’s not all, you can also play with the color balance, tone curve, creative blur, and vignette.

Other than that, you get various frames, ability to add text and a ton of cool textures to add to your photo.

User Interface

Ease of Use

I have been using the InPixio Photo Clip 7 for quite some time now and let me just get it out there. I like it. As I mentioned, the UI is pretty great but along with that, the tools also work very very well. I tried all the three tools and I really like how they work. I especially like the fact that all the tools have tutorials, which explain the working of the tools to you. These tutorials should surely come in handy for people who aren’t very well versed with photo editing software.

Overall, the tools that InPixio Photo Clip 7 brings work very well, and in my usage, I found the working to be pretty sleek and I never came across any lags inside the tools. However, the main welcome window of Photo Clip does tend to hang, which is weird. I hope the developers fix this, because other than that, the software is pretty flawless.

Price and Availability Pros:

Very useful tools

Plethora of photo editing features

Easy to use UI and features

Handy tutorials

No lag in the tools at all


The welcome page tends to get stuck

Edit Your Photos Better with InPixio Photo Clip 7

5 Weird And Hilarious Uses Of Data Science


“Ripley’s Believe or Not” features some of the weirdest and most bizarre facts from around the world. How about creating our own Ripley’s Hall of Fame for Data Science applications?

Think about it – what’s the first thought that comes to your mind when you think about Data Science? It’s usually all about techniques, algorithms, programming, among other things. Here’s what I’m proposing – how about we explore the road less traveled?

Yes – I’m talking about embracing the weird and fun part of data science!

In this weird and wacky world, our data science work reflects surprising connections, such as – if you are buying diapers then you are most likely to buy beer. Or, people who go to bars are a higher credit risk! Oh, I cannot miss out on this one – Smart people prefer curly fries. Liking “Curly Fries” on Facebook is a decent predictor of high intelligence!

So in this article, let’s take this roller coaster ride into the fun-world of data science and its weird and hilarious applications. And before we begin, here is a word of caution – this article might tickle your funny bone!

A new Harry Potter piece is hitting the book stores soon:

No, that’s not another J.K. Rowling book. It’s a Natural Language Processing (NLP)-generated Harry Potter chapter! Check out this weird line generated entirely by the model:

“Harry tore his eyes from his head and threw them into the forest. Voldemort raised his eyebrows at Harry, who could not see anything at the moment.”

This was generated by Botnik Studio, an open community of writers, artists, and producers who generate strange content using Data Science.

They collaboratively fed the text from all the seven volumes of this mesmerizing wizarding saga into a predictive algorithm. In just a fraction of minutes, the algorithm detected the pattern of words paired throughout the series. Interfaced in the form of predictive keyboards, the algorithm started making suggestions based on the pattern.

Two different predictive keyboards were used for this task — one for narration and the other for dialogues. And the sentences framed turned out to be pretty hilarious and outright crazy! Here is a relief for all those who lamented the death of Albus Dumbledore in Harry Potter And The Half-Blood Prince- the NLP model has resurrected him. 🙂

In August last year, a fan of the Game Of Thrones series had “written” five AI-generated chapters using recurring neural network (RNN). While the fan had managed to capture George RR Martin’s style of writing, the results were again in the realm of absurd.

What about getting one of your own stories written by a data science model?

So here it is – just try and build your own story by feeding articles about your favorite topic/series into an algorithmic text emulator, give it some input about your choice of words, and voila: you will have the lead paragraph for your story.

See, data science is entertaining us in the most bizarre way. Hopefully, it doesn’t make Harry the villain of this series going forward!

I love the creativity involved in this application.

This website is created by silicon valley software engineer Philip Wang. Each time you visit the site, it generates a unique face – a photo of a human dreamed up by the computer code.

It’s a simple website with no explanation, no code, no FAQ, and no branding. It just reflects a face that has never existed before (at that moment). Keep refreshing and it will keep generating fresh faces to infinity “from a 512-dimensional vector”!

What’s the computer vision concept powering this model, you ask? It’s Generative Adversarial Networks (GANs)!

But you must be wondering how GANs actually work. Here’s a brief explanation:

Broadly, the GANs training phase has two main subparts that work sequentially:

Phase 1: Train discriminator and freeze generator (freezing means setting training as false. The network does only forward pass and no backpropagation is applied):

Phase 2: Train generator and freeze discriminator:

If you want to dig deep into it then here are the steps to train your own GAN model. Pull up your socks and get ready to generate something as cool as this:

Phew! GANs are quite exhaustive and fun!

GAN was introduced in 2014 by Ian Goodfellow but it wasn’t until 2023 that researchers were able to create high-quality, 1024 x 1024 images detailed in the now-famous ProGAN paper.

I have been refreshing the site constantly – it’s super fun to see all sorts of new people!

3. Look who’s making us Dazzle with Ultra Stylish Clothes – AI Of course!

I never thought I would witness something like this – a machine learning model designing clothes much, much better than designers! The reaction of people, when asked to compare an AI designed dress against a human-designed dress was epic! Check it out:

Bizzare and amazing, this touches both cords for me as a fashion enthusiast. Imagine its applications – it will solve all the worries of deciding what to wear in the morning! A data science model will read my mind as I wake up and get my clothes ready according to my mood.

Talking about the fashion show, this data science use case has been created by Intelistyle – an AI styling service company. Typically, computer vision techniques that focus on Pattern recognition are used to find visually similar clothes but their approach was a little different.

Their main focus was on building a system that can recognize ‘style’. It is a lot more nuanced than finding visually similar clothes. So, they used deep learning to ‘extract the essence of style’. Of course, this step was executed after they successfully crawled the web for fashion photography examining thousands of outfits put together by influencers and stylists, designers and retailers.

Intelistyle even tested it against real stylists and fashion influencers at London Fashion Week. As Forbes reported, 70% of respondents unwittingly chose the looks created by their model.

Image Credits – Intelistyle

Here’s another fun data science application in fashion I spotted on Twitter. The AI, created by artist Robbie Barrat, has generated an entire collection based on Balenciaga’s previous styles. The fashion week came early on Twitter, courtesy of a clever neural network.

• Neat asymmetrical multi-component coat (one arm hidden… probably unintentionally though)

• Patterned sweater (shirt ?) with what looks like a two-tone turtleneck underneath (?) chúng tôi — Robbie Barrat (@DrBeef_)

You can also check out this paper, Generating High-Resolution Fashion Model Images Wearing Custom Outfits, for more information on creating AI-generated Fashion Trends.

4. Who’s killing the Academy Awards Game? Let’s have Data Science predicted Nominations Please!

Who is your pick for the best actor and best actress at this year Oscar’s?

Quite often we can guess the eventual winner by combining our intuition with the power of the media rumor mill. But there’s a major issue there – our picks can be heavily biased based on our own preferences and watching history.

Where there is a guessing game – there is data science!. You might think it’s weird but yes, AI had an impressive 94 percent score in predicting last year’s Oscars, for the third year in a row, you will be thrilled to know that AI outperformed industry experts.

The Hollywood Reporter and Microsoft teamed up to predict who would take home an Oscar at the 2023 Academy Awards through an online prediction poll called Awards Predictor (powered by Microsoft AI).

Unanimous A.I., a company that uses “Swarm A.I.” technology to create artificial intelligence products, comprises of a hive-mind of dozens of movie enthusiasts.

This TED Talk by Unanimous A.I. founder Louis Rosenberg, Ph.D., goes into further detail about this fascinating application of technology and the human brain.

These are the Swarm AI predictions for the 2023 Oscars:

Swarm AI combines real-time human input with artificial intelligence algorithms, optimizing a group’s combined wisdom and intuition into a unified output. In other words, Unanimous builds artificial “hive minds” that amplify the intelligence of human populations to create an artificial super-expert that can outperform traditional experts.

How can you build this exciting predictive machine learning model?

Well, it’s simple – combine OptiML, the optimization process on BigML that automatically finds the best-supervised model (and runs some top-performing models including deepnets, ensembles, logistic regression, and decision trees) with Fusions, that combines multiple supervised models for improved performance and make a batch prediction – and boom – your model will be ready!

5. Let’s Have a Good Laugh with AI-Powered ‘LOL BOT’

Now we have a robot who can make us laugh – literally! By far I found this to be the most unusual application of data science because I would never expect a bot to make me laugh, that too on the topic of my choice.

Meet – LOL BOT. The rib-tickling bot made its debut at the Melbourne International Comedy Festival and has been savoring fandom ever since then. It’s the world’s first bot that is capable of generating its own jokes, detecting real-time human reactions, and reacting accordingly.

Creative technologist Steven Nicholson said his team had developed LOL-Bot to use stochastic modelling to pull data and learn from thousands of hours of live comedy shows.

Stochastic modeling enables LOL BOT to pull data from the enormous library of jokes from all the comedians around the world. It uses deep learning algorithms to tease out the meaning from those shows and generate its own jokes. Here is a glimpse:

But, here is the catch – this BOT is not in existence now. Because at the comedy festival it was powered not by AI but by 7 top comedians of Australia! But nevertheless – building something like this is quite possible in today’s scenario. Why don’t you give it a

But, here is the catch – this BOT is not in existence now. Because at the comedy festival it was powered not by AI but by 7 top comedians of Australia! But nevertheless – building something like this is quite possible in today’s scenario. Why don’t you give it a try on this dataset and share your results?

End Notes

The idea of using data science to have some fun is really fascinating. My aim in this article was to open up a new portal for all of you who think of data science as a technical and all-too-serious field. Let’s have a little fun on the way!

How lucky we are, without any heavy investments, that we get to freely experiment. And I firmly believe that by using this power, our champion data science community will take the world by storm.


Top 10 Data Science Platforms That Cash The Analytics Code

Data science platforms are the must-have tools for any business enterprises that aspire to scale up its frontiers. Data science platform is essentially a software hub around which all the data science functionalities like data exploration and integration from various sources, coding, model building are performed. Data science platforms are programmed to train and test models and deploy the results to solve real-life business problems. Data science platforms are a massive hit driving business revenues to new heights, this can be ascertained by the fact that the global data science platform market is expected to grow at a CAGR of around 39.2% in the next decade to reach to approx. $385.2 billion by 2025. Using the massively varied data science platforms, one question is often asked and debated, which ones are the top data science platforms that let you use the best tools for the job at hand? According to a leading Data Science and Analytics recruitment agency, Burtch Works, 62% of analytics professionals prefer to code in R or Python over legacy solution SAS. While choosing a data science platform, among available open source solutions like Jupyter and RStudio or the closed platforms that rely on proprietary solutions can be a daunting task, business enterprises should rely on data science platforms that best serve their needs and allow them to use packages and languages as per their requirements. Here are the top data science platforms that are most used and liked in the business world, in short, these are the data science platforms that feature most of the Analytics code written!  

Alteryx is a computer software company headquartered at Irvine, California. Alteryx Analytics offers business intelligence and predictive analytics products that are used for data science and analytics. Alteryx Analytics is a closed platform and pricing vary from $3,995 per user, per year (for a 3-year subscription of Alteryx Designer) to $5,194 per user, per year (for a 1-Year Subscription of Alteryx Designer). Another offering is the cloud-based Alteryx analytics gallery which costs $1,950 per year, per user under a one year contract and $1,500 per year, per user under a three-year contract. Alteryx Analytics technology partners include Tableau, Microsoft, Amazon Web Services and Qlik (provider of QlikView & Qliksense). Alteryx Analytics is deployed by popular names including Johnson & Johnson, Hyatt, Unilever, and Audi among others.  

TIBCO Statistica is increasingly being relied upon by business enterprises to solve complex problems. The platform offers users to create innovative models with the latest deep learning, predictive, prescriptive, AI, and analytical techniques. The platform’s capabilities include comprehensive analytics algorithms including regression, clustering, decision trees, neural networks, machine learning that can be accessed through the built-in nodes. TIBCO Statistica offers data access through Apache Hadoop databases and data preparation by an automated data health check node. Users can use the reusable analytic workflow templates and integrate open source R, Python, C# and Scala, scripts to upgrade analytic workflows. While the TIBCO Statistica for Windows comes with a free trial of 30 days, the Analyst, Modeler, Data Scientist server comes with a price tag.  

With over six million users worldwide, Anaconda is a free and open source distribution of Python and R programming languages.  Anaconda products include Anaconda Distribution and Anaconda Enterprise. While Anaconda Distribution helps users install and manage packages, dependencies, and environment for 1,400+ data science packages for Python/R language, Anaconda Enterprise helps business enterprises harness data science, machine learning and artificial intelligence capabilities through model development, model training and model deployment. Anaconda is used by National Grid (a British MNC electricity and gas utility company) extensively to reduce maintenance costs and improve safety and reliability of their electric transmission assets.  

Databricks Unified Analytics Platform is developed from the creators of Apache Spark. Databricks workspace provides its users with a platform to manage all analytic process from ETL to model training and deployment through shared notebooks, simplified production jobs and ecosystem integration. The Databricks Unified Analytics platform prepares clean data on a real-time basis ready to train ML models for AI applications. Databricks is available for a 14-day free trial. For Databricks basic, Databricks Data Engineering, and Databricks Data Analytics, users have to pay as per Databricks Unit (DBU) on the workload the business enterprises run.  

6 Open Source Data Science Projects That Provide An Edge To Your Portfolio


“I understand the concepts well. Why should I focus on data science projects in my data science journey?”

I have been in the data science industry for more than a year now and this question is one of the most asked ones in the data science journey. This is especially true if are at the beginning stage of your journey. Personally speaking, the existence of this question is plainly immoral.

In the 21st century, there is not a single domain in the world that does not expect the candidate to have some form of self-practice that portrays his/her interest, understanding, and skill. The same is true for data science.

Data Science projects are the best way to showcase to the world your understanding of the topic. The projects you do are a manifestation of your programming skills, knowledge acquired and structured thinking. And let me tell you a little secret- “The data science projects you do serve as the key to unlock the tricky door, called the interview.”

With the importance of data science piquing more than ever, we bring to you 6 open source data science projects published last month that can give your portfolio an edge over the others.

The best way to make the most of your data science journey is to choose the right course, having the right kind of mentorship, and industry-relevant projects to make you industry-ready. Check-out our well-curated Certified AI & ML BlackBelt Plus Program.

Open Source Data Science Projects to Enhance your Portfolio

Let us divide the projects into categories.

Open Source Computer Vision Projects

FaceX-Zoo has to be one of the most impressive projects of the month. With face recognition becoming more and more relevant in the realm of computer vision FaceX-Zoo is an open-source data science project you do not want to miss.

Also, a simple yet fully functional face SDK is provided for the validation and primary application of the trained models. Also, FaceX-Zoo easily upgrades and extends along with the development of face-related domains.

Another mind-blowing project in computer vision, Bottleneck Transformer looks like a very good project to add to your data science portfolio.

The paper says-

“It is simple yet powerful backbone architecture that incorporates self-attention for multiple computer vision tasks including image classification, object detection, and instance segmentation”

Baseline models see significant improvement by simply replacing the last 3 bottleneck blocks of a ResNet and no other changes. Sounds promising, doesn’t it?

The Bottleneck transformer has all the potential to serve as a strong baseline for future research in self-attention models for vision.

The project come with a lot of promises including-

Full support for all primary training configurations.

Extensive verification of image quality, training curves, and quality metrics against the TensorFlow version.

Results are expected to match in all cases, excluding the effects of pseudo-random numbers and floating-point arithmetic.

With increased speed and efficiency as compared to other projects, StyleGAN2-ADA is a nice open-sourced project to add to your portfolio.

Open Source Natural Language Processing Projects

The fascinating world of NLP is not far behind when it comes to impressive open-sourced data science projects. Trankit is another popular project released last month.

Trankit is a light-weight transformer-based python toolkit for multilingual Natural Language Processing. Its 2 main constituents include-

A trainable pipeline for fundamental NLP tasks over 100 languages

90 downloadable pretrained pipelines for 56 languages

Another impressive thing about Trankit is that it beats the current state-of-the-art multilingual toolkit Stanza (StanfordNLP) in many tasks over 90 Universal Dependencies v2.5 treebanks of 56 different languages without losing efficiency in memory usage and speed, making it usable amongst a larger audience.

With Easy installation, usage, and Automatic download of pre-trained machine translation models, EasyMNT will easily make your NLP portfolio stand out.

It has translation between 150+ languages and automatic language detection for 170+ languages along with sentence and document translation.

At present, the project provides the following models-

Open Source Machine Learning Project

SeaLion is a brilliant Machine Learning Project created to teach the concepts in a more easy manner using concise algorithms capable of doing the tasks efficiently.

SeaLion is designed to teach today’s aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application.

It is beginner-friendly when it comes to solving the standard libraries like iris, breast cancer, swiss roll, the moons dataset, MNIST, etc. The algorithms in SeaLion include-

Deep Neural Networks


Dimensionality Reduction

Unsupervised Clustering

Naive Bayes


Ensemble Learning

Nearest Neighbors


End Notes

Wow– that’s a lot of projects. My aim, as always, was to keep the projects as diverse as possible so you can pick the ones that fit into your data science journey. If you’re just beginning, I would suggest starting with the SeaLion project. A great chance to get a head start.

I would love to hear your thoughts on which open source project you found the most useful. Or let me know if you want me to feature any other data science projects here or in next month’s edition.


5 Digital Jobs That Allow You To Work From Home

Over the past few years, working from home has become increasingly popular, and it’s easy to understand why. Many individuals are looking for ways to create a better work-life balance.

With a home job, you can benefit from flexible hours and spend more time with your family. That being said, it can be challenging to know where to get started.

Below we are going to take a look at five digital jobs that allow you to work from home.

Want to learn more? Then keep on reading.

Graphic Designer

If you have a passion for art and design, becoming a graphic designer is a great job that allows you to work remotely. It’s a popular career, and once you build up a reputation, the workflow can be consistent.

Virtual Assistant

A business might consider hiring an assistant for several reasons. As well as increasing efficiency, it can free up their time to focus on other critical tasks.

As a virtual assistant, you work self-employed as a freelancer. Your role can involve scheduling appointments, making phone calls, making travel arrangements, and responding to emails.


There are many different types of writers, and as you probably guessed, their work can be done from the comfort of their homes. Alongside copywriting for others, you may also decide to create your own online novels and webcomics.

Web Designer

Another excellent job for creative individuals is to become a web designer. Again, you get to work in a wide range of industries, and of course, you don’t need to go into the office.

While a degree isn’t required to get started, it is beneficial to undergo some training. This way, you can increase your skills in both design and web development.

Social Media Manager

Finally, if you think you have a knack for social media, a career that you might consider is becoming a social media manager. You’ll be in charge of managing your client’s accounts to help them grow their following.

Final Words

As you can see from the above, there are many different jobs that allow you to work from home, and we are just touching the surface. There are plenty of other career options that offer remote work too!

Before you make any significant decisions, it’s best to consider all of your options carefully. This way you can pick the perfect one for you.

John Moran

John Moran is an American who enjoys the fine art of living well. His interests include anything wine, food or nature related especially when enjoyed with friends and family.

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