Pragmatic Institute

The curriculum is good but basically whatever you learn, you learn on your own from resources available online. The big disappointment was finding jobs. They say they have 200+ partners but in fact most of them are not "Active in hiring". I only found 5 partners to apply from their CRM. Overall, they highly exaggerate their stats in every aspect. It doesn't worth 10 grands at all. And if you are a fellow, you definitely can find better positions on your own, don't bind yourself to their contract. 

Completing miniprojects on diverse and up-to-date topics really helped me to be confident about how to apply my technical skills on solving problems in practical situations. The hands-on experience from end to end, especially the relevance of the techniques to that in industry, is going to be a long term benefit for me and certainly for any previous and current fellow. 

The opportunity to have conversation and build relationship with different companies. This is not only for landing a job but more for a healthy business relationship in a long term. Getting the benefit from the bridge built up by The Data Incubator between fellows and partners is one thing. Another important goal of networking is for future communication and collaborations. Here comes our Fellows. I kept in touch with some of the fellows after we finish the program and we keep each other posted. It is invaluable having fellows experience the transition from academia to industry together including sharing thoughts and helping each other.

I attended the Data Science Foundation Class in winter 2018. The class was held online using Go to Meeting and Slack. Average class attendance was around 20. The teacher was always on time and there were very few technical inconveniences during lectures. The Data Science Foundation provided each student with a virtual server with class projects already loaded which greatly improved on-boarding times at the beginning. We were able to jump right into the material and not spend a lot of time trying to make everyone’s machines work.

The class content was organized well. We started by reviewing python and learned pandas and other libraries required by the class. We then moved to statistics and probability. Then back to additional python libraries and finished up with a very brief introduction to machine learning. It being a foundation class it moves very quickly across the top of a wide variety of topics. Having come from a background in programming I felt very comfortable throughout the entire class. I did struggle with some of the math concepts. I felt that more time could have been spent in that area.

Overall the class gave me an excellent foundation on which to continue learning data science. I use the tools and concepts learned in the class everyday at work and it has helped to advance me in my field. You won’t regret taking this course.

Since I had always been in academic before taking TDI, 
TDI is like a window to the industry, a bridge walking 
me smoothly from the academic world to the industry one. 
Through a series of activities like panel discussion and alumni party, 
TDI offered me a great platform to know what kind of problems 
companies are trying to solve, what skills they are looking for, 
how the daily life looks like, etc. Moreover, TDI provides valuable 
guidance in the whole process of job search, and last but not 
the least, the chance to work with a bunch of very smart people.

TDI gave me a lot of experience handling data in a way that I didn't get in an academic environment. The data sets were big, messy, and realistic. In addition, I thought that the capstone was an excellent way to get into a more industrial environment. The Data Incubator required a lot of database management, web scraping, and the like, which I didn't get in the academic setting I came from.

I also felt that TDI gave me a number of excellent opportunities. It may seem frustrating at times, but the partners really do want to hire Fellows, and TDI's salary and compensation ranges are very accurate (in my experience). I'm not sure I would have gotten the same response rate and offers if I hadn't been applying through TDI.

I participated in The Data Incubator's Spring 2015 cohort concurrently with finishing my PhD in physics at Penn State.  Through TDI I landed a job at Optoro, an e-commerce start-up in Washington, DC.  

The course was amazingly comprehensive in covering the tools and techniques most in-demand in industry today. Many of the topics we covered came up in interviews and problem sets during my job applications, and I wouldn’t have done nearly as well as I did in my job search without the skills I gained in the course. 

Another great thing about the program was the opportunity to hear directly from company representatives during the panel discussions. This helped me get a feel for the lay of the land and discover what types of jobs were out there. There were a lot of companies where I never would have considered applying, but once I heard what they were doing with data and about the scope of their technical ambitions, I became really interested.

If you're thinking of applying, be persistent - it's quite common to apply several times before being admitted (I applied twice).  Overall the program is a lot of work but it is worth every hour you put into it.  

 

 

At the end of my Computer Science PhD program, I attended the Data Incubator session in NYC in early-2015. I am very satisfied with my experience and recommend it to those with academic/research background looking for next steps.
The greatest benefit of The Data Incubator is in the ability to ramp-up your job search very quickly and take it to the next level. The partner companies come to the program ready to interact with Fellows and to find good hiring matches that satisfy their needs. The Fellows come ready to demonstrate their abilities, to show how they can add value, and to jump into new opportunities. This convergence of interests is very special and benefits everyone involved. I know that I benefited from the opportunity to interact so intensively with the wide variety of partner companies in my own search process.
Also, I especially enjoyed participating as part of the cohort in the NYC Data Incubator. Being located in NYC and interacting with the other fellows was very valuable. It helped me to understand my own strengths relative to others looking for similar opportunities. Coming together as a group all at once with similar goals to a new city helped to turn what is usually an individual effort into a more collaborative process. The connections formed within the group will help us far into our future careers.

I was a fellow during the summer of 2015 in DC. The Data Incubator helped me become a much more competitive applicant for jobs in the data science industry. By completing a collection of projects, I became much more proficient in the tools a data scientist needs to know and had multiple points to show off during job interviews. I also got to network with and befriend many other bright fellows who have since moved on to great jobs. I myself was hired at my current job through the Incubator, so it's hard to argue with results. 

To those considering the incubator, you will definitely benefit from the experience, but be prepared to work ~12-14 hour days throughout most of the program. It's hard work, but it pays off.

The Data Incubator surrounded me with incredibly smart, motivated Fellows who all had similar goals and backgrounds. Being in that environment, and having the structure of the program and the demands of my project, were essential to my education.

A talented instructor is not supposed to implant information into your mind, but rather function as a tour guide in a difficult landscape of concepts of varying relevance. The Data Incubator team did an incredible job of emphasizing the most important and fundamental concepts that a data scientist needs to know in his career – I know, because all of these things were confirmed in my first week at my new job.

I can't imagine having tried to find a job without The Data Incubator faciliating all of the connections we made.

I was in the Spring 2015 cohort in NYC. I was very happy with the program. In two months, I was able to learn a ton, and ultimately land a job I am very happy with at Capital One Labs.

The most valuable thing I got out of The Data Incubator was the ability to meet people from industry through the partner panels and happy hours. For me this served two purposes. First, it was an extremely efficient way to do a lot of networking in a short amount of time, which greatly increases the chance of finding a job. It is much easier to initiate a dialogue with a hiring partner if you have already met someone from the company in person.

Second, I learned a lot about the landscape of the industry, which helped me figure out what I was looking for in a job. Over the course of the program, I was introduced to companies that weren’t on my radar and found myself very interested in them. Once you are in The Data Incubator program, there are too many partner companies on the list to be able to seriously pursue them all. You have to know what you are looking for in order to focus your efforts, and I definitely gained that focus over the course of the program.