Got Questions?

Curriculum


How deep does your program go? How much of K2 is in-house curriculum vs. outside resources?

We have developed our own project-based, hand-crafted curriculum to make sure you receive the results you need to be successful. Our program is divided into two sections: curriculum and projects.

The curriculum is designed to teach you the concepts of building a robust machine learning system. Within each project, you will apply the machine learning system concepts in order to build your own work. We offer a combination of comprehensive videos, text-based curriculum, supplemental resources, and structured assignments.

Just as it’s critical to learn how to ride a bike without training wheels, it’s important to learn how to work independently as a data scientist. As you move from the curriculum to the projects, you will begin independently solving open-ended problems as an experienced data scientist would. You will still have opportunities to solve problems through collaborations with an experienced data scientist along the way.

On occasion, we reference external books, video tutorials or courses for further learning.

How is K2's curriculum created?

K2's curriculum is designed and developed in-house by experienced data scientists. Our curriculum development team constantly acquires feedback from students, mentors, and employers to iterate our curriculum. This process ensures that you’re always learning the most up-to-date and relevant skills.

What are the data science projects?

You will work on two projects that simulate real-world projects data scientists deal with. The first project involves independently solving a business question of your choice. During the second project, you will work with your current company or a startup company within our network to tackle an outstanding business problem.

Can I customize the curriculum in any way?

Absolutely! You will work with your designated mentor to choose modules and projects that are tailored to your abilities and areas of focus.

Approach


What do you look for in students?

A number of our K2 students will be current M.S./Ph.D. students or recent graduates. We place value on students that have some level of work experience within a technical or analytical field. We also look for students who have taken the initiative to learn on their own, are enthusiastic about data science, and are committed to excellence. If this sounds like you, then you’ve found the right program!

We look for students who are empowered learners with the following qualities:

  • Passion for Data. You have shown your passion by beginning to learn on your own. You are truly determined to become a data scientist whether you get into K2 or not.
  • Technical Foundation. You have taken quantitative courses and explored computer programming through in-person classes or MOOCs.
  • Growth Mindset. No matter what you have worked on so far, you aimed for excellence. You are targeting growth for yourself and others.

The curriculum does not start at a beginner level, some exposure to the field through academia, work experience or self-study is required to succeed in the course. An ideal candidate will have at least 1-3 years of work experience in an analytical or technical role. Check out our pre-program guide.

How does mentoring work?

At K2, we teach with a flipped classroom model: you learn, complete assignments, and resolve issues on your own. If you have any questions, you can also message a Teaching Assistant through our online platform.

During your weekly video-call sessions, you'll learn about more complex concepts. Your mentor will work with you to develop the best practices of data science and help you through any complicated problems. Feel free to seek professional advice or discuss your progress with your mentor. Your mentor will be there to encourage and help you every step of the way.

Above all, your mentor is committed to your success. Trust your mentor, and you’ll go far!

How do I choose my mentor?

Your program manager will match you up with a mentor based on your location, background and future goals.

If you have a specific career goal post-K2, please let the Program Manager know in order to find a mentor best suited to your needs.

What does the online community consist of?

We believe there are incredible benefits to learning within a community of your peers. To support this, K2 Data Science offers a vibrant online community.

  1. Join our exclusive Slack channel, where we have developed a thriving community. Exchange questions, comments, feedback, and advice with fellow students.
  2. Weekly Office Hours where you can meet other students, talk about that week's assignments, practice your presentation skills, and ask questions about the curriculum over video chat.

Tuition


Can I pay over time?

Yes--you can pay for the Bootcamp in 3 installments. If you opt for the payment plan, your total course price will be $7,000.

What if I don't like it?

If you’re unsatisfied with the program within the first 2 weeks, you can cancel for a full refund. If you decide to cancel later on, you'll receive a prorated refund.

Hiring & Job Prep


How does the job prep work?

The job prep curriculum will prepare you for the technical recruiting process. We walk you through how to navigate the world of predictive analytics, how to prepare a great data science portfolio, how to excel at technical interviews, and how to communicate the results of a machine learning project. The rest of our curriculum prepares you to excel at building end-to-end models.

The program curriculum includes dedicated material to review with an experienced mentor in preparation for the recruiting process to become a data scientist. Students create polished portfolios of projects that demonstrate job-ready analytical skills to prospective employers. Mentors carefully review resumes and cover letters for their students, lead mock phone screens, and conduct practice interviews so students can handle real technical interviews with confidence.

Students receive dedicated support from their mentor, including resume and portfolio critique, and a review of LinkedIn and GitHub profiles to ensure the best possible presentation to prospective employers. We will help you define criteria to guide your job search, and implement a process and cadence for managing the search.

What kind of jobs will I be ready for when I'm done?

Our program trains you to be industry ready for your first position as a data scientist, capable of taking on machine learning work.


How does job prep work for international students?

The job prep works the same for international students, but our industry contacts primarily consist of companies in major U.S. metropolitan areas. Most of our advice will be targeted for the US market but is generally applicable everywhere.

Timing & Policies


What kind of hardware is required? Do I need to purchase any software or tools?

We have 2 strong hardware requirements.

First, all students must have an external monitor serving as a second screen. This is necessary when you are learning data science in a distance learning environment.

Second, we strongly recommend a Mac or Linux-based computer. All our instruction will be for these types of operating systems and we do not have the resources to support issues that may arise with Windows PCs. If you have installed open source software, setup the Python development environment and used the PowerShell console, you should be fine on Windows.

You will not have to purchase any software, however, we may recommend paid apps or services that can enhance your productivity.

How long does the course take to complete?

We have the most comprehensive curriculum of any data science bootcamp. At the minimum, the program will take 600 hours to complete. If you tackle optional assignments, explore electives and go deep into your final projects, the program could easily take 1000+ hours.

If you are a working professional, it will take anywhere from 6-12 months to complete. If you are able to commit to the program on a full-time basis, you should be able to complete it within 4 months depending on your background.

I still have questions...

We’re happy to answer any other questions you might have about K2 Data Science. You can email us here.