https://www.datacamp.com/community/news/how-to-manage-title-confusion-in-data-science-1czj5ebpd29

As anyone who has tried to discern the “true definition” of a data scientist knows, titles can vary. How can you manage role expectations while job searching and know what you're getting into?

How to Manage Title Confusion in Data Science

https://www.datacamp.com/community/news/2018-data-science-hiring-survey-results-4f6br4d8h3f

After examining Attrition and Tenure of data scientists last year, we surveyed hiring managers to ask about their  hiring intentions for the beginning of 2018. The results were interesting!


2018 Data Science Hiring Survey Results

https://www.datacamp.com/community/news/data-science-resources-9juumimyaps

Data Science Resources!

<p><center><a href="https://www.datacamp.com/jobs/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1614871377/Raushon_tnvnpe.png" /></a></p>
<h2 id="tell-us-about-your-path-to-joining-datacamp-">Tell us about your path to joining DataCamp.</h2>
<p>After graduating university, I started working in tech as a Project Manager, but it wasn&#39;t long before I became fascinated with product development and the idea of designing and building products people love. I transitioned into my first Product role over five years ago and that’s when I realized that I was made for this job. Since then, I’ve worked as a Product Manager in various industries, with my previous role being in Fintech. Having worked in Fintech for a few years, I was keen to work in a less regulated environment where I could be more creative and contribute towards something more meaningful, and DataCamp seemed like the right place for that.</p>
<h2 id="how-was-your-onboarding-experience-at-datacamp-">How was your onboarding experience at DataCamp?</h2>
<p>I would describe my onboarding experience at DataCamp as &quot;do what you think is best.&quot; What I mean by this is that I was given the freedom to figure out what would help me to settle in quickly and do just that. This definitely pushed me to be self-sufficient from day one, which in hindsight is a blessing in disguise as after just two months, I already feel like I’ve been here a long time.</p>
<h2 id="what-excites-you-about-datacamp-">What excites you about DataCamp?</h2>
<p>Collaborating with so many talented people.</p>
<h2 id="what-s-your-home-office-setup-">What&#39;s your home office setup?</h2>
<p>Surely you would think that after a year of working from home, I’d have invested in a proper office setup? But no, I currently sit at my vanity on the most uncomfortable chair for hours everyday! And only because I don&#39;t want to ruin the aesthetics of my home with an office chair.</p>
<h2 id="what-do-you-like-to-do-in-your-spare-time-">What do you like to do in your spare time?</h2>
<p>I am a huge gym lover. Pre-lockdown, when gyms were still open, I would go to the gym five times a week. Otherwise, I always have my head in a book (I carry a book with me wherever I go) or am exploring the outdoors, wandering around in nature or hiking. I also love playing the piano but that&#39;s when the people in my house aren&#39;t tired of the noise I apparently make.</p>
<h2 id="what-s-something-interesting-you-ve-learned-recently-">What’s something interesting you’ve learned recently?</h2>
<p>Making sushi from scratch.</p>
<h2 id="how-do-you-feel-about-datacamp-s-evolution-and-positioning-in-the-market-">How do you feel about DataCamp’s evolution and positioning in the market?</h2>
<p>DataCamp’s evolution is impressive to say the least. There aren’t many companies out there that position themselves as having a mission to fight data illiteracy. The platform is dedicated to providing people with hands-on learning opportunities at a cost that can be easily justified. DataCamp has also done a great job at differentiating itself from its competitors through its continuous focus on innovation, and <a href="https://www.datacamp.com/community/blog/datacamp-2-0">DataCamp 2.0</a> is the prime example of this differentiation.</p>
<h2 id="what-would-you-tell-others-who-are-considering-working-at-datacamp-">What would you tell others who are considering working at DataCamp?</h2>
<p>If you want to work for a company that will push you to new levels of success, DataCamp is definitely the right place. The company really wants its employees to thrive as it continuously focuses on creating an environment that is both empowering and positive. Ultimately, DataCamp employees are not all that dissimilar. We all want to come to work, do good work, and feel valued for it. We also want to know that we’re working toward something more, and at DataCamp this is exactly how you end up feeling, regardless of how long you’ve been with the company.</p>
<p><em>Would you like to join Raushon at DataCamp? We’re currently hiring in New York; London; Leuven, Belgium; and remote locations. Check out our <a href="https://www.datacamp.com/jobs/">open roles</a>.</em></p>


https://www.datacamp.com/community/blog/raushon

Q&A with Raushon Uddin, Senior Product Manager at DataCamp

New Hire Spotlight: Creating the Best Platform to Fight Data Illiteracy | DataCamp

New Hire Spotlight: Creating the Best Platform to Fight Data Illiteracy

<p>March 8th is International Women’s Day. Despite an increase in the number of women in science and engineering jobs from 1.3 million to 2 million in the last 20 years, women remain underrepresented in the workforce. The greatest disparities still occur in engineering, computer science, and the physical sciences. According to the <a href="https://ncses.nsf.gov/pubs/nsb20201/u-s-s-e-workforce">National Science Foundation</a>, women make up just 27% of computer and mathematical scientists and only 15% of the engineering workforce in the United States, and the global statistics paint a similarly unjust picture. Even once those women secure a job in these competitive arenas, they typically make $15,000 less per year than their white male counterparts. For many women of color in STEM jobs, that pay difference is <em>double</em> (<a href="https://www.pewresearch.org/social-trends/2018/01/09/women-and-men-in-stem-often-at-odds-over-workplace-equity/ps_2018-01-09_stem_a-09/">Pew Research Center, 2018</a>).</p>
<p>Several of our <a href="https://support.datacamp.com/hc/en-us/articles/360051596574">DataCamp Donates partners</a> are determined to change that. One way they’re doing it is by helping us give free access to DataCamp to women of all ages around the world for free. Read on to learn other ways these nonprofits are working to increase diversity in STEM industries.</p>
<p><br><a href="https://www.blackgirlscode.com/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1614963104/BGC-banner_pkstiv.png" /></a><br>
<a href="https://www.blackgirlscode.com/">Black Girls Code</a> is spearheading a global movement to establish equal representation in the tech sector. They work with a broad community all over the United States to convene and empower young girls of color by fortifying their self-confidence, exposing them to unseen possibilities in the digital age, and equipping them with the tools and habits of mind required to become tomorrow’s creators, innovators, and leaders.</p>
<p><br><a href="https://www.datasciencefem.com/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1614963086/banner-datasciencefem_jotxmm.png" /></a><br>
<a href="https://www.datasciencefem.com/">Data Science FEM</a> is a group of women in Colombia dedicated to studying data science, who are regular participants in the annual Women in Data Science (WiDS) Conference at Stanford University. They challenge their members to become Data Scientists in one year, sharing knowledge with a network of mentors, events, and sponsors.</p>
<p><br><a href="https://www.girlswillcode.com/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1614963086/banner-girlswillcode_mppury.png" /></a><br>
<a href="https://www.girlswillcode.com/">Girls Will Code</a> is a nonprofit organization founded by 17-year-old CS wunderkind Isabel Sieh that encourages girls to participate in activities related to coding, programming, robotics and engineering. Through this platform, girls can share ideas about their personal projects, promote interest in programming and robotics in a fun learning environment.</p>
<p><br><a href="https://www.simplestepscc.org/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1614963086/banner-simplesteps_wkqyf7.png" /></a><br>
<a href="https://www.simplestepscc.org/">Simple Steps Community Connection</a> is a 501c3 organization founded in 2017 to help female immigrant talent in achieving their professional goals. They build a community for female talent to support, provide self-development and skill-building training in need, and connect female immigrant talent with job opportunities. Started in the California Bay Area, they serve other cities and states around the U.S.</p>
<p><br><a href="https://www.sistersofcode.org/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1614963086/banner-sistersofcode_zm40ew.png" /></a><br>
<a href="https://www.sistersofcode.org/">Sisters of Code</a> is the first Cambodian female coding club. Their mission is to grow confidence among female students and share the joy of learning coding skills, empowering them for a successful digital future.</p>
<p><br><a href="https://wi-tech.org/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1614963086/banner-witech_divxoq.png" /></a><br>
<a href="https://wi-tech.org/">WiTech</a> (Youth for Women in Technology Inc.) is a youth-led nonprofit organization that aims to inspire, educate, and empower the youth to break gender barriers and make a difference using science and technology. Their goal is to achieve gender equality in the Filippino tech industry through increased networking opportunities and mentors for young women interested in entering the tech industry.</p>
<p><br><a href="https://womenshavenafrica.com/"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1615214570/banner-womenshaven_vlxyeu.png" /></a><br>
<a href="https://womenshavenafrica.com/">Women&#39;s Haven Africa</a> is an innovative entrepreneurial female hub creating a friendly and productive environment for the growth and development of women-led businesses, projects, and initiatives. They connect promising young women, startups, women-led organizations and women leaders with the business support, tools, and resources to thrive. Women&#39;s Haven Africa is focused on increasing the participation of women in Entrepreneurship, Leadership and Technology so they can provide viable and sustainable solutions for various challenges facing the world.</p>
<h2 id="partner-with-datacamp-donates">Partner with DataCamp Donates</h2>
<p>Do you know of any public high schools or nonprofit organizations that could benefit from partnering with DataCamp Donates? We have 5,000 more subscriptions to give away—apply at <a href="mailto:donate@datacamp.com">donate@datacamp.com</a>!</p>
<p><center><a href="mailto:donate@datacamp.com"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1614963242/DCD_feejli.png" /></a><br></p>
<p>Calling all students, unemployed, and underpaid aspiring data professionals around the world: our DataCamp Donates partners may be able to provide you with a free year of DataCamp if you meet their eligibility requirements, which vary between organizations. Visit the <a href="https://support.datacamp.com/hc/en-us/articles/360051596574">FAQ</a> to find the organizations closest to you and reach out to them directly for more information.</p>
<h2 id="join-the-datacamp-team">Join the DataCamp Team</h2>
<p>Lastly, if you&#39;re interested in democratizing data education, DataCamp is hiring talented humans from all walks of life. <a href="https://datacamp.com/jobs">Apply here</a>!</p>


https://www.datacamp.com/community/blog/datacamp-donates-women-partners

These trailblazing organizations are using DataCamp to bring more women into STEM education and careers.

We Salute Our Women-Focused DataCamp Donates Partners

<p>After learning on an online interactive training and education platform like Datacamp, one of the next steps is taking that skill gained in Python, R, Git, or Unix Shell and using it on your local computer. It is not always easy to know what you need to install for the various projects you have in mind. This tutorial will let you know what packages, what softwares you need to install to get started with the various technologies. This tutorial will include:</p>
<p><nav></p>
<ul>
<li><p><a href="#anaconda">The benefits of the Anaconda Python Distribution as well as how to install it on your operating system.</a></p>
</li>
<li><p><a href="#R">The benefits of using R and RStudio together as well as how to install them on your operating system.</a></p>
</li>
<li><p><a href="#Unix">The benefits of a Unix Shell as well as how to use it on your operating system.</a></p>
</li>
<li><p><a href="#Git">The benefits of using Git as well as how to install it on your operating system. </a>
</nav>
<div id="scoped-content">
<style type="text/css">:target:before { content:&quot;&quot;; display:block; height:150px; margin:-150px 0 0; } h3 {font-weight:normal; margin-top:.5em} h4 { font-weight:lighter }
</style>
With that, let&#39;s get started!</p>
</li>
</ul>
<h2 id="python">Python</h2>
<p>To be able to use Python on your local computer, you first need to install it. There are many different python distributions, but for data science, the Anaconda Python Distribution is the most popular.</p>
<p><a id="anaconda"></a></p>
<h3 id="benefits-of-anaconda">Benefits of Anaconda</h3>
<p>Anaconda is a package manager, an environment manager, and Python distribution that contains a collection of many open source packages. An installation of Anaconda comes with many packages such as numpy, scikit-learn, scipy, and pandas preinstalled and it is also the <a href="http://jupyter.org/install.html">recommended way to install Jupyter Notebooks</a>. The image below shows a Jupyter Notebook in action. Jupyter notebooks contain both code and rich text elements, such as figures, links, and equations. You can learn more about Jupyter Notebooks <a href="https://www.datacamp.com/community/tutorials/tutorial-jupyter-notebook">here</a>.</p>
<p><img src="http://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1528918831/jupyterNotebook_oawzyh.gif" /></p>
<p>Some other benefits of Anaconda include:</p>
<ul>
<li><p>If you need additional packages after installing Anaconda, you can use Anaconda&#39;s package manager conda or pip to install those packages.This is highly advantageous as you don&#39;t have to manage dependencies between multiple packages yourself. Conda even makes it easy to switch between Python 2 and 3 (you can learn more <a href="https://towardsdatascience.com/environment-management-with-conda-python-2-3-b9961a8a5097">here</a>).</p>
</li>
<li><p>Anaconda comes with Spyder, a Python Integrated Development Environment. An Integrated Development Environment is a coding tool which allows you to write, test and debug your code as they typically offer code completion, code insight by highlighting, resource management and debugging tools among many other features. It is also possible to integrate Anaconda with other  Python Integrated Development Environments including PyCharm and Atom. You can learn more about different Python Integrated Development Environments <a href="https://www.datacamp.com/community/tutorials/top-python-ides-for-2019">here</a>.</p>
</li>
</ul>
<h3 id="how-to-install-anaconda-python-">How to Install Anaconda (Python)</h3>
<p>Here are some links to guides below on how to install Anaconda on your operating system.</p>
<p><a href="https://www.datacamp.com/community/tutorials/installing-anaconda-mac-os-x">Install Anaconda on Mac</a></p>
<p><a href="https://medium.com/@GalarnykMichael/install-python-on-windows-anaconda-c63c7c3d1444">Install Anaconda on Windows</a></p>
<p><a id="R"></a></p>
<h2 id="r-programming-language">R Programming Language</h2>
<p>Most people generally install RStudio alongside the R programming language. The RStudio integrated development environment (IDE) is generally considered the easiest and best way to work with the R Programming language.</p>
<h3 id="benefits-of-rstudio">Benefits of RStudio</h3>
<p>An install of the R programming language gives you a set of functions and objects from the R language and an R interpreter that allows you to build and run commands. RStudio gives you an integrated development environment that works <b>alongside</b> the R interpreter.</p>
<p><img src="http://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1528918830/RStudio_abcd_pp8pks.png" /></p>
<p>When you open RStudio, an screen like the one above appears. A few features in contained in the four RStudio Panes are: (A) a Text Editor. (B) Dashboard to Work Environment. (C) R Interpreter. (D) Help Window and Package Management System. All these features make it so RStudio is all you really need after installing R.</p>
<h3 id="how-to-install-r-and-rstudio">How to Install R and RStudio</h3>
<p>Here are some links to guides below on how to install R and RStudio on your operating system.</p>
<p><a href="https://medium.com/@GalarnykMichael/install-r-and-rstudio-on-mac-e911606ce4f4">Install R and RStudio on Mac</a></p>
<p><a href="https://medium.com/@GalarnykMichael/install-r-and-rstudio-on-windows-5f503f708027">Install R and RStudio on Windows</a></p>
<p><a id="Unix"></a></p>
<h2 id="unix-shell">Unix Shell</h2>
<p>Navigating directories, copying files, using virtual machines, and more are a regular part of a data scientist&#39;s job. You will often find the Unix Shell utilized to accomplish these tasks.</p>
<h3 id="some-uses-of-a-unix-shell">Some Uses of a Unix Shell</h3>
<p>1 - Many Cloud Computing Platforms are Linux based (utilize a flavor of Unix Shell). For instance, if you want to <a href="https://www.datacamp.com/community/tutorials/google-cloud-data-science">Setup a Data Science Environment on Google Cloud</a>, or do <a href="https://www.datacamp.com/community/tutorials/deep-learning-jupyter-aws">Deep Learning With Jupyter Notebooks In The Cloud (AWS EC2)</a> it requires some Unix Shell knowledge. There are times when you may have a use for a <a href="https://www.datacamp.com/community/tutorials/aws-ec2-beginner-tutorial">Windows virtual machine</a>, but it is less common.</p>
<p>2 - Unix Shell provides a number of useful commands such as: <code>wc</code> command which counts the number of lines or words in a file, <code>cat</code> command which concatenates/merges files, <code>head</code> and <code>tail</code> commands which help you subset large files. You can learn more about this in <a href="https://www.datacamp.com/community/tutorials/shell-commands-data-scientist">8 Useful Shell Commands for Data Science</a>. Also, check out DataCamp&#39;s course <a href="https://www.datacamp.com/courses/data-processing-in-shell">Data Processing in Shell</a>.</p>
<p>3 - You will often find Unix Shell integrated with other technologies as you will see throughout the rest of the article.</p>
<h3 id="integration-with-other-technologies">Integration with Other Technologies</h3>
<p>You will often find Unix Shell commands integrated in other technologies. For example, it is common to find shell commands in Jupyter Notebooks alongside Python code. In Jupyter Notebook, you can access shell commands by escaping to the shell by using an <code>!</code>. In the code below, the result of the shell command <code>ls</code> (which lists all the files in the current directory) is assigned to the Python variable myfiles.</p>
<pre><code>myfiles = !ls
</code></pre><p>The image below shows some Python Code integrated in a workflow to combine multiple datasets. Notice a Unix Shell command (enclosed in the red rectangle) integrated in a Jupyter Notebook.
<img src="http://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1528918829/escapeJupyter_cyppxl.png" /></p>
<p>Keep in mind that the code in the image above isn&#39;t some unique way to do a task, but just a small example of how you may see Unix utilized. If you want to learn how to use Unix for Data Science, Datacamp has a free course <a href="https://www.datacamp.com/courses/introduction-to-shell-for-data-science">Introduction to Shell for Data Science</a> which I highly recommend. It is a skill that lots of aspiring data scientists forget about, but it is a very important skill in the workplace.</p>
<h3 id="unix-shell-on-mac">Unix Shell on Mac</h3>
<p>Mac comes with a Unix shell so you usually don&#39;t need to install anything! An important point is that there is a variety of Unix systems that have different commands. Sometimes you find that you don&#39;t have a Unix command (like <code>wget</code>) found on another Unix system. Similar to how you have package managers through RStudio and Anaconda, Mac can have a package manager called Homebrew if you install it. The link below goes over how to install and use Homebrew.</p>
<p><a href="https://www.datacamp.com/community/tutorials/homebrew-install-use">How to Install and Use Homebrew</a></p>
<h3 id="unix-shell-commands-on-windows">Unix Shell Commands on Windows</h3>
<p>Windows does not come with a Unix Shell. Keep in mind that what Unix Shell does for you is give you useful commands for Data Science. There are many different ways to get these useful commands on Windows. You can <a href="https://hackernoon.com/install-git-on-windows-9acf2a1944f0">Install Git on Windows</a> with the optional Unix tools so that you can have Unix commands on your Command Prompt. Alternatively, you could <a href="https://github.com/bmatzelle/gow">install Gnu on Windows (GOW)</a> (10mb), Cygwin (100mb minimum), among many other options.</p>
<p><a id="Git"></a></p>
<h2 id="git">Git</h2>
<p>Git is the most widely used version control system. A version control system is something that records changes to a file or set of files over time so that you can recall specific versions later. Git is an important technology as it really helps you work with others and it is something you will find in a lot of workplaces. Some of the benefits of learning Git include:</p>
<ul>
<li><p>Nothing version controlled using Git is ever lost, so you can always go back to see previous versions of your programs.</p>
</li>
<li><p>Git notifies you when your work conflicts with someone else&#39;s, so it&#39;s harder (but not impossible) to accidentally overwrite work.</p>
</li>
<li><p>Git can synchronize work done by different people on different machines, so it scales as your team does.</p>
</li>
<li><p>Knowing  Git makes it easier to contribute to open source development of packages in R and Python.</p>
</li>
</ul>
<h3 id="integration-with-other-technologies">Integration with Other Technologies</h3>
<p>One of the cool things about Git is you often find it integrated with other technologies. Earlier I mentioned that the RStudio integrated development environment (IDE) is generally considered the best way to work with the R Programming language. <a href="https://support.rstudio.com/hc/en-us/articles/200532077-Version-Control-with-Git-and-SVN">RStudio offers version control support</a> and most many Python Integrated Development Environments (IDE) (learn more <a href="https://www.datacamp.com/community/tutorials/data-science-python-ide">here</a>) offer version control support.</p>
<p>If you want to learn how to use Git for Data Science, DataCamp has a free course <a href="https://www.datacamp.com/courses/introduction-to-git-for-data-science">Introduction to Git for Data Science</a> which I highly recommend.</p>
<h3 id="how-to-install-git">How to Install Git</h3>
<p>Here are some links to guides below on how to install Git on your operating system.</p>
<p><a href="https://hackernoon.com/install-git-on-mac-a884f0c9d32c">Install Git on Mac</a></p>
<p><a href="https://hackernoon.com/install-git-on-windows-9acf2a1944f0">Install Git on Windows</a></p>
<h2 id="conclusion">Conclusion</h2>
<p>This tutorial provides a way to setup a local data science environment on your local computer. An important point to emphasize is that these technologies can and are often integrated together. If you any questions or thoughts on the tutorial, feel free to reach out in the comments below or through <a href="https://twitter.com/GalarnykMichael">Twitter</a>. Also, feel free to check out my other installation based tutorials located on my <a href="https://github.com/mGalarnyk/Installations_Mac_Ubuntu_Windows">Github</a> or my <a href="https://medium.com/@GalarnykMichael">Medium blog</a>.</p>

https://www.datacamp.com/community/tutorials/setup-data-science-environment

Learn about the various options you have to setup a data science environment with Python, R, Git, and Unix Shell on your local computer.

How to Setup a Data Science Environment

Setup a Data Science Environment on your Computer

<p>Data Science has its own language. So, if you want to have at least a slight chance of surviving in the enterprise world of tomorrow -with its obsessive focus on collecting and analyzing data- you better have started yesterday with learning this terminology.</p>

<p>
Luckily, and inspired by the <a href="http://techcrunch.com/2014/12/15/how-to-speak-startup/" target="_blank">&ldquo;How To Speak Startup&rdquo;</a> article on TechCrunch, the online data science school&nbsp;<a href="https://www.datacamp.com/?utm_source=How%20to%20speak%20data%20science&amp;utm_medium=blog&amp;utm_campaign=How%20to%20speak%20data%20science" target="_blank" title="Online R and Data Science Training">DataCamp</a> is here to help you with a great list of often-heard&nbsp;data science terminology and quotes:</p>

<p style="padding-left: 30px;"><em>(Note: This is an attempt to be funny. Whether this is a successful attempt is an opinion and open for debate. That it shouldn&rsquo;t be taken serious nor offensive is a fact.)</em></p>
<br>
<ul>
<li><b>Data scientist - </b>Average programmer looking for a job that pays as much as what a top programmer would get. Sometimes also goes by the name &quot;data analyst&quot;. <a href="http://ctt.ec/fd39T">Click To Tweet.</a></li>

<li><b>Statistician<b> - </b></b>Mathematician who can&rsquo;t program. <a href="http://ctt.ec/5GeK0">Click To Tweet</a></li>

<li><b>&quot;Our company is big data ready&quot;<b> - </b></b>My software vendor has done a great up-sell. <a href="http://ctt.ec/e60r2">Click To Tweet</a></li>

<li><b>&quot;We measure everything&quot;<b> - </b></b>We have absolutely no clue what to measure. <a href="http://ctt.ec/agQBd">Click To Tweet</a></li>

<li><b>Data savvy manager<b> - </b></b>Title used by managers active in marketing, sales or HR whom put pie charts in their powerpoint presentation.<a href="http://ctt.ec/yb5CO"> Click To Tweet</a></li>

<li><b>&quot;Correlation does not imply causation&quot;<b> - </b></b>We looked at the wrong data set and can&rsquo;t draw any conclusions from it. Often represented in a graph to create the illusion of adding value. <a href="http://ctt.ec/bYG2e">Click To Tweet</a></li>

<li><b>Machine Learning<b> - </b></b>Statistical technique used by the sales and marketing department of big data vendors to secure their yearly bonus. (also see &quot;Our company is big data ready&quot;) <a href="http://ctt.ec/V03xb">Click To Tweet</a></li>

<li><b>Chief Data Scientist</b> (CDS)<b> - </b>Former CTO (also see data scientist) <a href="http://ctt.ec/aIF5E">Click To Tweet</a></li>

<li><b>Hadoop<b> - </b></b>Open-source software used for distributed computing. Data Scientists seem to have a quota to drop the name every two sentences when talking big data, but most only know the logo is a yellow elephant.&nbsp;<a href="http://ctt.ec/SK6Z6">Click To Tweet</a></li>

<li><b>&ldquo;Being a data scientist is the sexiest job in the 21st century&quot;<b> - </b></b>Although a quote often used in the data science industry, statistical underpinned proof remains missing. <a href="http://ctt.ec/R5tvh">Click To Tweet</a></li>

<li><b>Data science bootcamp<b> - </b></b>Headhunting firm marketing itself as a school. <a href="http://ctt.ec/2p735">Click To Tweet</a></li>

<li><b>&ldquo;We booked these results with a small sample&quot;<b> - </b></b>Our financial budget wasn&rsquo;t large enough to perform a statistical significant data analysis.
<a href="http://ctt.ec/8Ura6">Click To Tweet</a></li>

<li><b>&ldquo;We implemented a data-driven decision making process&rdquo;<b> - </b></b>In the past we didn&rsquo;t have a clue what we were doing. <a href="http://ctt.ec/1cPGk">Click To Tweet</a></li>

<li><b>&quot;We use cutting edge predictive modeling techniques to forecast our results&rdquo;<b> - </b></b>We run a linear regression model and then ignore the result. <a href="http://ctt.ec/BacF3">Click To Tweet</a></li>

<li><b>&quot;There is a significant effect but ...&quot;<b> - </b></b>Sentence-start used by data scientists or statisticians when they&rsquo;ve put weeks of work into their analysis, the results look fishy and not as expected, and there is no time to redo the analysis. <a href="http://ctt.ec/UXfJd">Click To Tweet</a></li>
</ul>
<br>
<p>Hope this was helpful! Good Luck.</p>


https://www.datacamp.com/community/tutorials/how-to-speak-data-science

Data Science has its own language. This is a great list of often-heard data science terminology and quotes by Datacamp.

community

datacamp

general

News (23)

How to Manage Title Confusion in Data Science

Data Science Resources!

Tutorials (7)

Setup a Data Science Environment on your Computer

How to Speak Data Science

Cheat Sheets (0)

Open Courses (0)

Podcast (0)

Blog Posts (65)

New Hire Spotlight: Creating the Best Platform to Fight Data Illiteracy

Tech Thoughts (0)