Everything You Need To Know About TDI Programs

If the only thing holding you back from applying to a TDI fellowship is uncertainty, then this blog is written just for you. We’re going to dive into the specifics of the interview process starting with what you should expect as a student in a TDI program.

You should expect:

• An Intense Learning Environment
  Prepare to learn many data focused skills from an intense, hands-on curriculum.
• Thorough Instruction
  We believe in fostering an interactive learning environment. During each week of our programs, our students will work on projects that focus on a data tool or approach.
• Collaboration Opportunities
  We want students not only to work with their colleagues and instructors, but also have the opportunity to network and connect with our hiring partners.
• Career-Focused Skills
  We’ll have career coaches that help you succeed in your data-focused careers. You’ll not only learn how to present your best self by attending our career search workshops, but you’ll also have the opportunity to work with one of the number one resume writing companies that actually specialize in data science. You’ll receive a polished resume and cover letter at the end of the program.
• Interactive Tools and Teaching
  Lastly, all of our programs are interactive. Every student in all of our programs is provided a Jupiter server for the duration of the course. So students can follow along with the lecture and edit raw code, and you’ll receive immediate feedback via our interactive grader.

The Difference Between a Fellows and Scholars

We admit two types of students into our data science and data engineering programs: Fellows and Scholars. If you’re brand new to The Data Incubator programs, you may be wondering what’s the difference?

What is a fellow?
Highly qualified candidates are offered tuition-free scholarships to our full-time program. These are our fellows.

A big component of the fellowship spots is that we are looking to place you with one of our hiring partners and you’ll be interviewing exclusively with them during the program and for three months after. You want to make sure it is your goal to find new employment at the end of the program.

What is a Scholar?
Scholars are the students admitted to our programs who pay tuition.

They are not required to interview solely with our hiring department network and they maintain any current employment. Scholars have the same access to curriculum, resources and tools as our fellow students

The difference between a part-time and full-time program

In both programs, you’ll work on projects that showcase your data science skills using real-world data to solve business problems, but there are some key differences between the part-time and full-time options.

1. Weeks Spent Doing Coursework
   Since both programs provide the same hands-on, in-depth training, it’s no surprise the full-time program takes fewer weeks than the part-time program. Full-time students spend 8 weeks in the program and part-time students spend 20 weeks in the program.
2. The Ability to Work While in the Program
   Since the part-time students aren’t investing 40 hours a week on study, they have the ability to maintain employment outside of the program.
3. Class Times and Days
   Full-time coursework is scheduled for Monday through Friday from 9 AM EST to 5 PM EST. Part-time coursework is scheduled in the evenings twice a week from 7 PM EST to 9:30 PM EST.
4. Scholarship Opportunities
   We’re thrilled to offer a small number of full-tuition scholarships for the data science program. However, since there are only a few available spots, only full-time data students can apply.

The Application Process

The application process consists of three sections for data science fellowships (application, coding challenge and interview) and two sections for data analytics (application and interview).

The Application
We’ll ask you all the usual questions about your education, work experience and other details that help us determine if you meet the basic qualifications for the program.

You must have at least one of the following:

• A master’s degree completed before the program begins
• A Ph.D. degree completed before the program begins
• A Ph.D. degree completed within 3 months of the conclusion of the program
• A bachelor’s degree and extensive experience in a data-related field.

All of our applications are reviewed on a first-come, first-served basis, so the sooner you get yours in, the better chance you have of moving forward.

The Challenge

For Data Science Fellowship applications, the next step after the application is the coding challenge.

You’ll have 72 hours to complete the challenge once you start, so make sure you are prepared to give it your all. Keep in mind: you don’t have to finish all the challenges, but you do need to complete as much as you can. We evaluate quality and quantity when selecting the best applicants for the upcoming cohort.

While the challenge is open, you’ll have the chance to save and come back to continue your work, but the last time you save is the version we’ll evaluate.

The Interview

We’ll contact the most promising candidates to set up time for an online interview with our instructors and staff.

Interviews will take place in groups of 3-5 students. Each interview will take approximately 30 minutes to an hour, depending on the group size.

You’ll have 2-3 minutes to pitch a project and show your initial findings, and you’ll have an opportunity to share a link to your work and deliverables if you have them.

If you prepared a project for the interview you should:

• Discuss your motivation for selecting this project
• Share your dataset
• Provide the analysis you’re performing

After you’ve presented, the instructors will ask you technical questions about your project: the scope, audience, business application and takeaways.

Then if time permits, other students may ask you questions about your projects as well.

Here are tips for interviewing well:

• Conduct a Tech Check Before the Big Day
  Your pitch and the interview time goes by fast, so make sure that you test your technology beforehand.

  If for some reason, you can’t get connected or you’re not able to find the link make sure you reach out to us at least 30 minutes before your interview so we can help.

  Also, test your project links to ensure they’re working properly and familiarize yourself with the chat and interface in zoom.

• Promptly Schedule Your Interview
  Once you have access to schedule your interviews, we encourage you to schedule them as soon as possible. Spots are first-come, first-served and spots fill up quickly. We’re unable to grant additional spots or extend the interview schedule.
• Practice and Prepare
  Practice your pitch and create an outline to ensure that you are able to clearly speak and present your project in the time presented. But still be natural, not heavily scripted or robotic. It also helps to limit your distractions to ensure you are focused on your interview.

  Arrive early so you feel confident and not rushed. Have a compelling intro and interesting takeaways. Be specific and concise to make the most of your minutes.

Want to see more about our curriculum and what it entails for each program?

• Download our Data Science Syllabus
• Check out our Data Science Curriculum Outline
• Check out our Data Engineering Curriculum Outline