cderv
July 19, 2018, 9:13pm
3
In your repo, i can see you have a draft = true in the yaml header of your post.
---
title: "Masters of Analytics at Georgia Tech"
author: "Shoili"
tags: ["Data Science", "Georgia Tech"]
date: 2018-07-18T14:32:29-04:00
draft: false
---
Every year for the last couple of years, I have got a few LinkedIn inmails and a few DMs on Reddit asking about the Georgia Tech Masters in Analytics aka MSA program. Now I am not one of those people who believe that you must have a Masters degree to do Data Science but a Masters program is definitely one way to learn things. There's several of these programs out there now and it's hard to choose, which is largely why people reach out to me about it so I'm going to write down some of my thoughts about program - the pros and cons. FYI, I graduated from this program in 2017 (in case you're reading this in the distant future and things have changed a lot)
## Pros
1. This program is offered jointly by three schools. Operations Research/Industrial Engineering, Computer Science and Business. ISYE and CS at Tech are both top ten ranked departments in the country/world. The business school is also top 50 in the States. You're basically getting to learn from some of the most knowledgeable people in the world. Also your cohort will be a collection of super smart people that you'll learn a lot from.
2. The program is very flexible. Several of the other programs I know about have a fixed curriculum. This one offers three tracks - you take a majority of your classes from one of the three participating schools. A track is for Analytical Tools or those who do more Operations Research classes, B for business and C for computational track or those who took more CS.
3. Not only do you get to pick your track, and change it halfway if you want to, you also get to choose what classes to take from all these departments. The track only dictates how many of each you have to take. There are three or four compulsory classes which are introductory material and can be waived depending on your academic/work background. The rest are up to you.
4. You do a real life data science project in summer which gives you some nice experience. This can be an internship or a project at school. Very valuable if you don't have much work experience.
5. There's a team of lovely people whose job it is to find you a job or internship. Takes a lot of pressure off you.
6. There's a conference budget for each student and they can pick what conference(s) they want to go to. It's a great way to meet cool data scientists, see what they're working on and also find a job.
## Cons
show original
When you serve your site locally during development, draft post are rendered. When you build it with build_site, they are not rendered. I think this is why it does not appear in the index page. Just put draft = false.
see documentation about YAML metadata
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