I mentor new (💫) and aspiring data scientists enter (🚪) and level up (📈) in the field. I help data pros find work they love (❤️) and that loves them back.
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Source: Author’s rendition of Integrated Postsecondary Education Data (IPEDS) data collected and assembled by this article’s code. An excerpted view.

TLDR: This guide puts together a three-year data panel (also known as longitudinal data) using public data available from the US Department of Education. Use the techniques in this article to prepare data that you can analyze on your own. Tell me in the comments what other federal data sources I should build similar guides for next.

Introduction

Are you any of the following?

  • Working for a client that needs to understand the landscape of higher education institutions throughout the United States?
  • A researcher (graduate student, university faculty) looking to study higher education institutions?
  • A current or aspiring data professional looking for new data to explore? …


Across LinkedIn and Facebook, data science users report preferring LinkedIn as the place to go when looking for others in the field they know, like, and trust.

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Image Credit: Author’s visualization of social media poll results. This visual shows that LinkedIn seems to be the most popular platform among Data Scientists when looking for others in the field they know, like, and trust.

Even among Twitter users, LinkedIn is the second most preferred platform.

Across LinkedIn and Facebook, data science users report preferring LinkedIn as the place to go when looking for others in the field they know, like, and trust.

If you are looking to enter or level up as a data professional, let me know. You can reach out my way on any of these three platforms.

Thanks For Reading

If you like what I have to say, find more at: adamrossnelson.medium.com. Check out my Udemy courses. …


TLDR: Now that I have ProWritingAid.com it is time for me to go back to my GitHub profile, find those ReadMe.md files (plus other markdown files) and fix my atrocious writing! This article contains affiliate marketing links.

Introduction, A Confession

Confession, as a data scientist, I do not always follow my own advice. I constantly tell myself and others that the most important skill as a data scientist is to communicate. This includes writing well.

One of my favorite tweets shows the importance of writing well. This tweet shows how modest efforts and self-editing can improve your presentation.

To find evidence that I do not always follow my own advice, I looked no further than my GitHub repositories. They are full of incorrect spelling, split infinitives, and other writing problems. I recently wrote about these common writing problems. …


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Image Credit: Author’s illustration or worksheet from Data Science Quick Start on a whiteboard. Teaser visual from the Data Science Quick Start Course.

TLDR: This article previews a course I recently made available on Udemy. If you’re a classroom teacher (at any level), scroll to the bottom of this article where I discuss offering this course to you and your students for discounted rates. On a first-come-first serve basis, a select few classrooms will be eligible to enroll in the course for no charge.

Introduction

Everyone needs to start some place. This Data Science Quick Start course is for folks who think they might be interested in data science but are not yet sure. …


Image of text from an academic journal.
Image of text from an academic journal.
Writing is not easy. Keeping these ideas in mind will help in the drafting and editing process. Image credit: Author’s photograph of a page from an article in an academic journal.

Introduction

Communicating about your work, your findings, and other aspects of your science is more difficult than many appreciate. More difficult than I once did! I base this article on the written communication errors I have made in the past. Listed in alphabetical order.

Administrate

This one sounds harsh to my ears. For better or worse, I can find this word in multiple dictionaries. There is an alternate choice that has been in use much longer: administer.

An advantage of using administer over administrate is that the conjugations of administer are more regular and more well understood:

Think about, for example: Administer, Administering, Administered, Administers. …


Office Hours

Introduction

Some data driven thoughts for anyone that wonders how important salary is in the mind of candidates that are or who have recently participated in a job search. I recently conducted and published the results of a poll that indicate salary is not the most important consideration on the mind of job seekers. A smart candidate will carefully consider all aspects of a job offer including health insurance, employer contributions to retirement, paid leave (vacation, sick time, time to care for sick family), the opportunity for tuition support, etc.

A candidate who is worried when she gets a question from a recruiter about salary expectations.
A candidate who is worried when she gets a question from a recruiter about salary expectations.
Image credit: Author’s illustration of a candidate who is worried when she gets a question from a recruiter about salary expectations.

The problem for candidates, who might not consider salary to be the most important factor when evaluating a job offer, is that recruiters often demand to know a salary expectation during the first conversation. Sometimes even before the first conversation. And worse, recruiters will screen candidates based on salary. A companion article talks about why asking and screening questions on the basis of salary is a mistake. …


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Image Credit: Adapted from Wikimedia Commons.

Introduction

Whoa, the blogs and support forums are blowing up with users that are having trouble getting Anaconda to install on a Mac.

Anaconda Mac Installation that will (likely) be glitch free.

These two steps will help you avoid seeing: -bash: jupyter: command not found after installing Jupyter Notebook.

Step One

Download the command line installer. Here is what that looks like:


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Image from the Lucile Vaughan Payne (1969) The Lively Art of Writing. This image is adapted and reproduced below.

Preface

For anyone interested in examining and improving how you write. For audiences who are technical or non-technical, junior or executive, academic or colloquial, business professional or creative casual.

By giving my take on the essay form, I hope others will also consider using this form to improve their writing.

Introduction

Not long ago a reader of one of my articles over at Towards Data Science made a comment on my article’s conclusions. The reader wrote ‘You already told us this’ (gisted). After pushing past the humbling surprise that anyone cared enough to read my entire article. Also, that any cared enough to give feedback. I resisted the urge to comment back “Umm, yeah. You’re point? …


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Photo credit: Tim Mossholder

It’s a mistake that will potentially cost the opportunity to connect well with candidates that really want to work for you. It’s a mistake that will render your company vulnerable to hiring candidates who will be easily poached away by other competing employers. It involves making a faulty assumption about candidates. The faulty assumption is that salary is a candidate’s most important consideration in the job search.

I recently conducted a poll using multiple social media platforms. The combined polls collected 343 responses.

Less than half of the respondents indicated that salary was their most important consideration (47%). This means that more than half of the respondents may consider at least one other factor as more important (53%).


Introduction

While speaking with current, former, and aspiring data scientists I hear a common complaint. Recruiters will screen you based on your salary history or your salary expectations.

I’m troubled when recruiters do this, not only for the candidate’s sake, but also for the recruiter’s sake. To drive the conversation a bit further, I conducted a poll using social media.

I ran this poll in late October and early November of 2020. I posted the poll on LinkedIn, Twitter, and Facebook. I used hashtags, keywords, and forums that I thought would encourage responses from those that work in data science or other research oriented professions. …

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