The Data Incubator

The application process can be daunting and intimidating, however, each step has its reasons. This makes each cohort learn and progress in a homogeneous pace, which is key to a successful completion of the TDI.

I was part of the D.C 2017 winter cohort and the 8 weeks were key to position myself as a Data Scientist in the industry. You share and work collaboratively with the rest of the cohort, making it invaluable because you are not only learning from the diverse curriculum but also from your peers. At the end of the day, Data Science is both a Science and an Art, so different perspectives and approaches to problem-solving definitely enhance your skillset.

Additionally, there is also a focus on soft skills, from getting your resume up to speed to effective communication. Each...

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...

As a recent graduate of the Winter 2018 cohort, going through the 8-week intensive data science training at The Data Incubator has taught me a great deal about various data science tools and has prepared me with the essential skills to thrive at my first data science job. I've gained a full data science stack, such as creating a web application, web-scraping, data cleaning, exploratory analysis and visualization, SQL, machine-learning, big data tools, and cloud computing, as well as a business mindset. More importantly, networking with and learning from other talented and brilliant fellows has taught me a lot about myself and how to become a great data scientist. More importantly, I made a lot of connections that I can see will be long term.

I highly recommend this 8-weeks intensive training at The Data Incubator (TDI), because it really helped me to go deeper into data science field and get fully prepared for the essential skills to work in a big data industry.

As a PhD graduate in chemistry background, the transition from academia to industry is not easy. But fortunately, I attended TDI during Winter 2017, and I gained full stack from the program, including the cutting-edge analytics techniques, programming, machine learning, data visualization as well as business mindset. The networking with all other talented fellows is definitely a plus! Needless to say, my 1st data scientist job with a hiring partner in less than a month from graduation is the most valuable thing I got out of TDI!

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.

I attended The Data Incubator during Spring 2017. I earned a data science position with a hiring partner in the San Francisco financial district within three weeks of graduating. Below I enumerate the many aspects of The Data Incubator I found valuable.

Resume building:
Starting at the semi-finalist level, applicants are provided strategies for resume writing. With some careful thought, I was able to portray seemingly bland parts of my academic background as eye-catching resume bullet points. Time is also dedicated in the first days of the program for polishing resumes yet again before final submission to the employer-facing online resume book.

Professional head shot:
Prior to the program, Fellows and Scholars are advised to get a professional head shot. I had never done this b...

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.

TDI laid the foundation of knowledge for computer science and data science related concepts. The TDI curriculum provided me the breadth and depth of knowledge necessary to understand everything from software engineering and numerical computation to the use of programming tools (including Python and d3 for data visualization), Natural Language Processing, statistics and probability as well as the ability to apply parallel processing to data analysis. Importantly, TDI also prepared me for the technical questions asked during my data science interviews.

Learning:

The Data Incubator was an outstanding experience. I got to know and work with some of the brightest minds there are, the cohort included Ph.D's and Post Docs from Stanford, Duke, Johns Hopkins, Yale among others. We were all gathered in the same place to exchange ideas and tackle our very demanding weekly projects (a different relevant subject each week) while working on our final, capstone project.

I was exposed to so many different technologies, from big data to deep learning, from statistical analysis tools to machine learning, some of them I already knew and some were new to me.

Interviewing:

They have a great list from hiring partners all over the US (and many abroad), including very big names from Silicon Valley and Seattle.
We had weekly interviewing practi...

I learned a lot of tools used by data scientists in day-to-day work, such as supervised and unsupervised machine learning, natural language processing and distributed computing. In addition to that, I made like-minded friends in my cohort

Hi,
I am a PhD student in Mechanical Engineering. For my career, I’ve gave it a lot of thoughts and I chose to be a data scientist, so I got my minor in statistics. I’m going to graduate by the end of 2017. While ago, I received an email about Data incubator. I though it’s a good opportunity for me to learn more about data scientist and it’s going to be great for my resume. The first time that I applied for Data Incubator, it asked for recommendations and resume and the next step was link to a test, when it was the time for the test, the link wasn’t working. They emailed applicants after couple of days and apologized for the technical problem and gave us new timing for the test which didn’t work for me. After 6 months, I received another email from Data Incubator which said they kept m...

I was completely new to coding before this course and it was very hard, one of the hardest things I've done in my life, but I learned an enormous amount and I'm really glad I did it.
Some of the teaching styles really didn't work for me and I gave my feedback to the tutors and they were super quick to change things to help me complete the course.
The course is heavily marketed as being able to land you a job by the end of it, giving statistics that 80-85% of students find a job within 4 months of graduating. However, I find that a bit of an overstatement, given that only a small portion of students in cohorts ahead of me have found jobs. It just doesn't quite line up with the stats. But I think this could be massively remedied by providing graduates with more individualised support a...

I got a job out of The Data Incubator! But in addition to that, I got at least three important things out of The Data Incubator. One, I received comprehensive training in key data science tools. Two, I was able to become a part of a supportive network of fellow PhD data scientists. And three, I came away with a good understanding of what is needed in industry and how I, as a PhD, can be of use.

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 ne...

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 par...

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.

I attended The Data Incubator with a very talented and highly motivated group of recent and soon to be PhDs in engineering, physics, math, neuroscience, psychology, and linguistics. We spent our days working on challenging mini projects and evenings polishing the pitches for our capstone projects. In between we met employers at partner panels, happy hours, and pitch nights. I ended up taking a job from one of the hiring partners and am really glad that I was a fellow at TDI.

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...

I was a tenure-track scientist when I decided to move to a job as a data scientist in industry after I got frustrated with funding issues in academia. I was very happy with the Data Incubator course which met all my expectations an more. I was introduced to many concepts that I had just touched on in some online courses I had taken prior to the course. By having weekly mini projects, I was forced to understand the material more. Whilst there were lectures to accompany the mini-projects, in order to complete them I was forced to do some research on my own which was a valuable thing. We weren’t just fed the answers.

On top of this, as an online Fellow, I appreciated being split into small groups. In my case, this worked really well and I would encourage others in the same situation t...

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.