Thanks for stopping by! I’m excited to share my Metis NYC Data Science Bootcamp journey to becoming a data scientist. In this “Ribbon Cutting” post, I’ll give you some background on myself, explain what Data Science is, and explain some of details of the Bootcamp. Going forward, I’m planning to write a new post every few weeks.
Along the journey, I’ll fill you in on…
- The Metis Data Science Bootcamp experience
- Tips and techniques for better collecting/analysing/visualizing data
- The NYC experience (hopefully including where to get the best egg sandwich, cheese plate, and milk shake)
For those that don’t know me, perhaps some background on my experience and how I see the world would be useful.
At my core, I consider myself a Maker. More specifically, I am passionate about making a positive impact by creating technology products using my strong blend of technical and business skills.
I was born and raised in the Washington, DC metro area with a passion for technology and sports. I attended the University of Virginia where I built a foundation in both technical and business skills by earning my degree in Systems Engineering and also minoring in Engineering Business and Economics.
Since graduating UVA, I spent the last 6+ years as a technology consultant for Deloitte tackling complex problems in the federal public service industry and consumer products industry focusing on application development, enterprise architecture, and business intelligence. In 6+ years, I wore a combination of hats - 1) Software Engineer, 2) Business Analyst, and 3) Engineering/Product Manager. While I enjoy organizing chaos and leading others, I learned my real passion lies in rolling up my sleeves to build easy to understand visualizations and easy to use technology products that simplify complex problems.
I also enjoy sports / exercise, travel, cooking/eating, and most importantly, learning new things!
Check out the about page for more information about me.
What is Data Science?
The simplest way I can explain Data Science is that it’s the practice of extracting valuable insights from data using a combination of math, computer science, and business domain knowledge, as shown in the following venn diagram.
Perhaps some real-world examples of what Data Scientists do can help you wrap your head around the subject:
- Developing the algorithm for the Facebook News Feed
- Google’s work on image recognition and classification
- Google’s AI Beats Top Player at Game of Go
- Nate Silver’s work on FiveThirtyEight predicting elections, sports, and lots more
- A/B Testing
- Spam filtering
The Bootcamp started April 4th 2016, is in-person in NYC for 12 weeks, Monday through Friday, from 9 am - 6 pm and costs $14,000 (UPDATE: The cost increased to $15,500 on June 20, 2016). Going into the Bootcamp, you are expected to have experience writing code and studying/using statistics. The application process (online application, coding challenge, and Skype interview) helps control for these prerequisites.
Highlights of the curriculum include learning the Data Science toolkit, statistical methods such as regression analysis, machine learning, and data visualization with D3. The program culminates in a 3-week final project that allows you to develop a solution to a problem of your choosing. Here’s the full syllabus.
At the end of the program, the goal is to be “comfortable designing, implementing, and communicating the results of a data science project, including knowing the fundamentals of data visualization and having introductory exposure to modern big data tools and architecture such as the Hadoop stack.”
For more information about the program, check out the Metis site.