Data Incubator is a postgraduate technology bootcamp in Boston that offers courses in data science. So, if you’re wondering how you can become a data scientist, you’ve come to the right place.
With the backing of Cornell University, this eight-week bootcamp will prepare students to start a lifelong career in tech. The school helps all of its graduates navigate through the job search process, whether they enroll in an in-person or online bootcamp.
This Boston-based training institute offers a range of programs in data science, machine learning, and artificial intelligence. Most graduates from Data Incubator already have advanced degrees in STEM before they enroll in the bootcamp.
The data science bootcamp doesn’t just prepare students for work in major tech companies. It also teaches them how to become tech entrepreneurs, equipping them with unique, in-demand skills in a short period of time.
Even though it is based in the US, Data Incubator has partners in Malaysia, Japan, Italy, and Germany. This international collaboration has allowed it to expand its reach and offer students a variety of work opportunities upon graduation.
|Locations||Boston, New York City, Washington DC, San Francisco, Online|
|Tuition||Online Data Science Essentials: $2,895, Online Data Science Fellowship: $10,000 Campus: $17,000|
|Financing Options||Income Share Agreement (ISA), Loan Financing, Scholarships, Upfront Payment|
|Start Dates||March 23|
|Program Types||Online, Full-Time, Part-Time, Self-Paced|
|Courses||Data Science Fellowship, Data Science Essentials|
Data Incubator offers both online and on-site locations around the US to suit all learning styles.
Some of the courses offered by Data Incubator are hosted exclusively onsite, while others are only offered online.
Whether you opt for the online or onsite option, you will benefit from career assistance and will be just as likely to land a high-paying job right after graduation. It is important to note that all onsite courses have been temporarily moved online because of the pandemic.
Many variables influence the tuition cost at Data Incubator. In-person classes start from $17,000, while online classes start from $10,000.
Data Incubator offers many tuition payment plans, as opposed to some other bootcamps in the country. You can choose whether you want to pay upfront, apply for a scholarship, take out a loan, or use an income share agreement.
Candidates with impressive credentials can apply for Data Incubator’s data science fellowship program. Every year, a few students are awarded full scholarships.
Data Incubator also offers two discounts to applicants. The admissions process is divided into three phases: early admission, regular admission, and late admission. Those who enroll early will get a $2,000 tuition discount. Students who apply during regular admissions will get a $1,000 discount.
Students who enroll in the Data Science Essentials program qualify for a discount of up to $1,500 on tuition for the Data Science Fellowship.
Data Incubator’s ISA allows participants to attend its data science bootcamp without paying tuition upfront. They will only be required to pay it back after they have secured a job.
Once you’re working, the bootcamp will take a percentage of your monthly wage for a set number of months, or until you’ve paid back your tuition.
Another popular option to cover tuition is a loan. Data Incubator currently has a lending arrangement with Skills Fund. In this plan, Skills Fund will pay for your tuition once you’ve been admitted, and you will pay back your loan after you’ve graduated.
If you’re not satisfied with the payment plans offered by Skills Fund, you can choose to go with another loan financing firm.
No, Data Incubator doesn’t accept the GI Bill.
Data Incubator offers courses for postgraduate students who want a career in data analysis or another area of data science. Apart from learning new things about Data Science, students with STEM will also be getting real-world data science experience.
The Data Science Essentials program runs for eight weeks and is offered entirely online. Students who want to get admitted into the Data Science Fellowship will benefit from taking this Data Essentials program first to help them brush up on their data analysis and data management skills.
In the course, students will learn the fundamentals of quantitative analysis, data extraction, and statistics. Learning Python for data science is also a core part of the curriculum. Students are also required to complete projects using live data sets as a way to gain hands-on experience.
The online class has live teachers, and learners are encouraged to engage their instructors when they have questions about any topic. However, there are also recorded lectures for those who prefer a self-paced learning option.
This is an extensive data science program for tech professionals interested in advancing their careers. The full-time program runs for eight weeks while the part-time program lasts for 20 weeks. All part-time classes take place in the evening.
The Data Science Fellowship program covers different aspects of data science including software like Spark, TensorFlow, and pandas. It also goes into the vital concepts of data science as students complete several projects. Students will master the programming language Python and will also complete lessons on software deployment and other advanced topics.
Everyone who completes this program will receive a certificate.
Getting into this coding bootcamp isn’t easy. As stated above, the programs are intended for people with advanced STEM degrees. Only the best of the best will be admitted.
The Data Incubator acceptance rate is just two percent.
The application process is your chance to prove to the admissions board that you will be a valuable addition to the school. The whole process usually takes about six weeks and involves an online application, technical challenges, and a coding bootcamp interview.
The interview is one of the most important parts of the admissions process at Data Incubator because it is your opportunity to make a good first impression. The questions will concern your technical skills, your ambitions, and your personality.
If you don’t have a STEM degree, you should not apply for Data Incubator. It is an advanced data science bootcamp that isn’t meant for beginners. Taking the Data Essentials program will help you prepare for the Data Fellowship program but you still need a Stem degree.
If you have a master’s degree or a PhD in a relevant field, you most likely have the knowledge you’ll need to get admitted. Just learn as much as you can about the admissions process to make sure you can meet the requirements.
Yes, Data Incubator is worth it. It is one of the most exclusive bootcamps in the US. The tuition is high if you’re not part of the fellowship program, but if you meet the requirements and can afford it, you should go for it.
The job placement rate at Data Incubator is impressive. After graduating, you are very likely to get a high-paying job in a prestigious firm either in the US or abroad.
No, Data Incubator does not offer a job guarantee. However, it has a reliable hiring network. Companies looking for top-tier data scientists will turn to Data Incubator, or may already be partnered with the bootcamp.
The school’s hiring partners get the first pick of recent graduates. Plus, students that go on to work for one of the bootcamp’s hiring partners get 50 percent of their tuition back.
Data Incubator is one of the most exclusive tech bootcamps around. While many other tech training schools accept students with high school diplomas, only postgraduate students in relevant fields will be admitted to Data Incubator.
If you meet these prerequisites, then joining a program at Data Incubator will prepare you for new opportunities in tech. Whether you already have some work experience or are just about to launch your career, Data Incubator will provide an intensive and exciting learning opportunity.
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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.
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.
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.
April 13, 2020
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.
July 14, 2020
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!
August 16, 2020
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
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.
October 17, 2020
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.
November 12, 2020