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2018 Rewind: Our Most-Read Blog Posts of the Year

By Emily Wilson • December 21, 2018

Photo by NordWood Themes on Unsplash

Throughout the year, we post blog content covering topics like job searching tips to alumni stories to lessons from our Sr. Data Scientists and more. These posts represent our top 10 most-read blogs of 2018. We hope you enjoy them again or for the first time – and hope you visit our blog again in the new year for more content! 

1. Navigating the Data Science Job Market
Metis Sr. Career Advisor Andrew Savage wrote this year's most popular post based on two talks he gave at ODSC West and the Global AI Conference, where he shared information about the data science job market. Because of the positive reception, he wanted to share his perspective more widely with the goal of helping anyone looking to break into the world of data science as a job applicant.

2. Dear Aspiring Data Scientist, Skip Deep Learning for Now
There's no arguing it – deep learning can do some truly awesome stuff. But as our former Sr. Data Scientist Zach Miller points out, when training to be an employable data scientist, these skills aren't necessary – at least not right away. Read his post to learn why.

3. Using Scrum for Data Science Project Management
In all lines of work, good project management can make the difference between failure and success, but data science projects present some unique challenges. What are they and how should you handle them? Read Metis Sr. Data Scientist Brendan Herger's post on how to use the Scrum paradigm to get projects finished on time and with desired results.

4. Five Passion Projects by Metis Sr. Data Scientists
Metis Sr. Data Scientists teach our 12-week data science bootcamps, work on curriculum development, present at conferences, perform corporate training, and more throughout a rotating yearly schedule. Built into that is time to work on passion projects, tackling whatever suits their interests and allows them to dig deeply into a facet of data science. In this post, read about five such passion projects.

5. What is a Monte Carlo Simulation?
One of the most powerful techniques in any data scientist's tool belt is the Monte Carlo Simulation. It's flexible and powerful since it can be applied to almost any situation if the problem can be stated probabilistically. However, former Metis Sr. Data Scientist Zach Miller found that for many, the concept of using Monte Carlo is obscured by a fundamental misunderstanding of what it is. To address that, he put together a series of small projects demonstrating the power of Monte Carlo in a few different fields.

6. Frequently Asked Bootcamp Questions Answered by a Sr. Data Scientist
In this post, Metis Sr. Data Scientist Roberto Reif answers the most frequently asked questions he gets about our data science bootcamp. When should you apply? How can you brush up on your stats skills? What kind of job should you expect to get after the bootcamp? Get answers to these questions and more.

7. Tips for Maintaining a Positive Attitude in the Job Hunt
Finding a job is hard. Finding a job when transitioning to a new field – specifically data science – can be even tougher. In this post, Metis Career Advisor Ashley Purdy shares some ways to keep yourself sane and motivated throughout your job search.

8. Sr. Data Scientist Roundup: Climate Modeling, Deep Learning Cheat Sheet, and NLP Pipeline Management
When our Sr. Data Scientists aren't teaching bootcamps , they're working on a variety of other projects. This monthly blog series tracks some of their recent activities and accomplishments. This time around, read about projects covering climate modeling, deep learning, and NLP pipeline management.

9. Bootcamp Hidden Benefits
You may already know the basics about our bootcamp. It's intensive, lasts 12 weeks, and is project-focused, for instance. But did you know there are many hidden benefits of the bootcamp? This post will give you a better idea of everything the bootcamp has to offer.

10. Academia to Data Science - Where does Bootcamp Fit in?
To transition from academia to industry, many choose bootcamps as a way to bridge the gap between the theory-heavy rigor of academia and the practicality of industry experience. In this post, hear from three such students who made the transition via bootcamp and who are now working in the field.

__________

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