The Data Incubator
The Data Incubator Reviews and Key Information
The Data Incubator is a data science bootcamp for STEM degree holders and professional data scientists or data analysts looking to upskill. While headquartered in Boston, the Data Incubator also has campuses in New York City, Washington D.C., and San Francisco.
Known to be one of the best data science bootcamps, the Data Incubator is a top pick for a higher level of data science training. If the Data Incubator is one of your prospective bootcamps, then you’ve come to the right place.
This Data Incubator review will walk you through the key features of the bootcamp. That includes its programs, curricula, tuition costs, and even its job placement services. By the end of this guide, you will have a better grasp of whether the Data Incubator is the right coding bootcamp for you.
The Data Incubator at a Glance
| Cost of Tuition | $2,895 – $17,000 |
| Financing Options | Income Share Agreement, Upfront Payment, Private Student Loans, Scholarships |
| Courses Offered | Data Science Essentials, Data Science Fellowship |
| Career Services and Job Assistance | Career Coaching, Network of Industry Partners |
What Can You Learn at Data Incubator?
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Data Incubator has two major programs: Data Science Essentials and Data Science Fellowship. Both programs work with real-world datasets, allowing students to gain hands-on experience as they learn the fundamental theories and principles of the field.
Data Science Essentials
This is an eight-week online program for people who don’t have prior work experience in data science but want to get into the Data Incubator’s Data Science Fellowship program. It’s also perfect for data analysts or software engineers who wish to switch to enter the data science field.
The program includes instructor-led classes that cover the fundamental aspects of data science, preparing students for more advanced studies. There are classes dedicated to teaching you the fundamentals of quantitative analysis, data statistics, data extraction, object-oriented programming, and Python for data science.
Despite being a foundations course, interested applicants must have basic knowledge of statistics and programming to excel in the class. The program also does not hold out on hands-on training courtesy of short projects that require the use of real-world datasets.
Data Science Fellowship
This is a certificate fellowship program that runs for eight weeks full-time and 20 weeks part-time. The program is perfect for professionals looking for a skill-boost for career advancement or individuals who wish to transition from academia.
Topics include data visualization, data structures, algorithms, navigating data science tools like Hadoop, and applying machine learning and big data analysis techniques. You will also learn Python and SQL, both of which are known as the resident data science programming languages.
Being an immersive program, taking the full-time option means hitting a pause on other commitments as you are expected to commit 45 hours of your week studying. If that doesn’t sound like a feasible option, consider taking the part-time option.
The schedule is flexible enough to maintain your studies without compromising other responsibilities. Just put aside eight hours of your time per week to attend evening classes.
Admissions: How Do You Get Accepted to the Data Incubator?
The Data Incubator has an acceptance rate of a mere two percent, so getting into the bootcamp will not be easy. This isn’t unusual for a fellowship program that only admits students with advanced STEM degrees or extensive experience in a data-related role. The requirements are looser for the bootcamp’s Data Essentials program.
Having these credentials is only the tip of the iceberg. You should still go through the Data Incubator’s application process.
The Data Incubator Application Process
The application process at The Data Incubator happens in stages, with the completion of the entire process taking about six weeks. It starts with filling an online application form on the bootcamp’s website. The website is intuitive so you should not run into any trouble filling in the required details.
After filling in your details, wait for an advisor to send you the coding test. This stage is crucial since failing the test means you cannot move on to the next stage. The advisor will give you 72 hours to complete the test and submit it.
Students who pass the coding test can move on to the next stage of the admissions process, which will see you sitting through an interview with a school representative. This is the last stage of the application process.
The Data Incubator Interview
The interview stage is vital in informing the decision of the admissions board. The interviewer will ask you questions about your experience with data science. You will also be asked questions about why you chose data science and how far you intend to push for a career in the field.
Keep in mind that the interviewer’s goal is to find out more about you, your goals, and your motivations to see if you are a good fit for the bootcamp. At the same time, your goal is to determine whether the bootcamp’s programs and teaching style meet your learning needs. So, don’t hesitate to ask questions of your own during the interview.
Paying for the Data Incubator
Attending the Data Incubator’s fellowship program generally costs $10,000 when taken online and $17,000 when taken in person. The foundations program, meanwhile, costs $2,895. You can pay for your tuition through one of four options: upfront payment, private loans, income share agreements, and scholarships.
Upfront Payment
With this option, you can enjoy the early registration discount of $2,000. Even when you pay during the regular registration timeline, you will get a tuition discount that ranges from $1,000 to $1,400. You will not qualify for the discount if you opt for any of the other payment plans.
Income Share Agreement (ISA)
This works like every other ISA: you attend the program without paying the full tuition and pay later when you’ve landed a job that pays at least $40,000. You can pay monthly percentages from your salary.
Once you hit the income threshold, you are expected to pay a particular percentage of your income. While an ISA means that you do not have to pay upfront, you may need to make a small deposit before attending lectures.
Private Student Loans
Private loans are the perfect option for people who cannot afford to pay upfront and are not comfortable with an ISA. You can take out a loan via the Data Incubator’s loan provider partner Ascent Funding.
If you opt for a Ascent Funding loan, you may choose among three repayment options: deferred repayment, interest-only repayment, or immediate repayment.
Scholarships
The Data Incubator offers fully-funded scholarships to fellows with exceptional backgrounds in data science. Only a few people qualify for this scholarship, so you can apply if you believe your credentials are impressive enough.
What Makes the Data Incubator Unique?
The Data Incubator has a proven track record as one of the most successful data science bootcamps for individuals with advanced STEM degrees. Even if all its programs are delivered online, the quality of education it delivers remains high. One of its defining features is the heightened focus on providing hands-on training.
The Data Incubator has many hiring partners that tap into the bootcamp’s graduate pool. Students who get jobs with The Data Incubator’s hiring partners get 50 percent of their tuition back as a placement fund. Only a few bootcamps offer placement funds to candidates after helping them get jobs.
Thanks to bootcamp’s career coaching and mentorship programs as well as its extensive employer network, Data Incubator reports a job placement rate of 82 percent. Most Data Incubator graduates get their first job within six months after they finish the program.
Price Range
$0-$3,4956 Reviews
6 Reviews
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Anonymous
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 before (or really had been aware of such services), but I realized it was an important part of going all in. While this can be expensive, Fellows who successfully join a partner company are reimbursed for the head shot (I was).
Structured curriculum and weekly miniprojects:
The data science curriculum includes lectures, daily coding challenges, and miniprojects. Weekly lectures are accompanied by IPython notebooks mixing text exposition with runnable code. There is a lot of lecture material to master every week, and persevering here helps with interviews and the miniprojects. The notebooks encapsulate the advanced features of scikit-learn, SQL, and big data tools (Hadoop, Spark), and they make for indispensable reference material after the program. The miniprojects are essentially problem sets and provide hands-on experience with these tools.
The capstone project:
This is meant to be an application of data science to a publicly available (or scrapable) data set that is ultimately presented as a web application. It is adisable to have a rough draft, or at least a strong start, on the project before beginning the program, so start thinking about this before applying. There are several upshots to doing well on the capstone: 1) You have a recent data project to talk about in interviews that is more substantive than any of the individual miniprojects, 2) Practice building a web app (e.g., with Flask) for deployment on cloud services (e.g., Heroku), 3) Practice pitching your project in weekly video updates; for these videos, I learned how to edit video/sound with Openshot and to splice in images and screen capture footage of my project.
Soft skills lectures and interview practice:
Soft skills lectures provide coaching for resume writing, onsite interviews, and salary negotiations. Weekly interview practice covers computer science and statistics problems of varying difficulty, both on pen/paper and in front of a whiteboard.
Summary:
The Data Incubator is an extremely worthwhile experience. The components of the program outlined above have a snowball-like cumulative effect at turning academics into viable industry job candidate, commensurate with the effort they put into preparation before and during the program.
June 13, 2020
Anonymous
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.
June 14, 2020
Anonymous
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!
July 16, 2020
Anonymous
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.
August 20, 2020
Anonymous
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.
September 17, 2020
Anonymous
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 week there are dedicated sessions on how to tackle interview questions, how to sell yourself, and how to navigate opportunely the recruiting process, complementing TDI rigorous technical curriculum.
Going to the TDI was I not only enriching but also enjoyable. You come out of the program with a powerful network of top-notch data scientist, a second to none skillset and the toolkit to navigate the corporate world.
October 10, 2020