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Data Science Fellowships for Non-Profits

Benefit from our fellowships for non-profits and use the power of data science for the good of society.

Empowering the Non-Profit Organizations

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From women’s education and health to relief work and conservation of resources, non-profit organizations are doing remarkable work in the world. Unlike for-profit companies, these organizations do not have enough resources to upskill their workforce. Data Science Dojo brings this unique opportunity for employees of non-profit organizations to learn the latest techniques in data science and contribute toward the social good. We aim to create future leaders with a passion for employing data-driven solutions for social good.

We firmly believe that data science skills can be used for making a social impact. Check out this talk on AI for Social Good.

Health

Research and treatment for physical and mental well being.

Environment

Conservation and restoration of natural resources and habitats.

Humanity

Promoting social justice, education, public welfare, and more.

Fellowship Areas

We offer fellowships to non-profit professionals dedicated to using the power of data science for the betterment of society.

How It Works

Application Form

Fill out the application form to show your interest in the Data Science Bootcamp.

Interview Phase

Succeed in a series of interviews to benefit from our comprehensive training.

The Bootcamp

Attend the Bootcamp in an interactive environment with live instructions.

Review the Bootcamp

Participate in a short interview and write a blog post about  your experience.

Meet Past Fellows

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Shaena Montanari

Newton International Fellow at the University of Edinburgh

ENVIROMENT

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Rebecca Chapman

Program Manager at Equal Access International

HUMANITY

FAQs

You must be employed at a non-profit organization, or make a strong case (backed up by your resume) as to how your current work will serve social good.

Post-doctoral researchers are also welcome to apply, but preference is given to non-profit employees.

We select outstanding candidates with a passion for data science and a track record of community service.

Preference is also given to applicants that have clear goals about how to use data science to give back to their communities.

We select fellows once per quarter. This is done on a “rolling deadline” basis, meaning that we will review applications in the order that they are submitted to us. Even if you apply in a different quarter, you may still be considered for the next quarter.

Selected fellows will be notified 3-4 weeks prior to the bootcamp.

Applicants are encouraged to submit their fellowship application at least one month prior to their targeted bootcamp. For example, if you want to go to the data science bootcamp starting March 28th, you should apply before February 28th.

If you are not selected for your targeted bootcamp, you remain eligible for the next bootcamp. For example, if you are not selected for the March 28th fellowship, you remain eligible for the next bootcamp fellowship.

  • Fully covered tuition at a 16-week bootcamp
  • Access to the learning portal
  • Books and other course materials

At the end of the bootcamp, we ask our fellows to write a blog post describing their experience at the bootcamp and how they plan to apply their learning in the respective industry. Fellows are also encouraged to use social media during the bootcamp to describe their experience.

We also like to stay connected to Data Science Dojo fellows. 3-6 months after the bootcamp, we will ask you to explain how you used data science to solve any problems, especially those related to social good.

If you are not selected for a fellowship, your application remains active. We will consider it again for the next fellowship selection.

You can also consider a paid bootcamp. Our prices start at $2,799. You can also explore our financing plans.

Feel free to reach out to us through our Contact Us page.

Can’t find what you’re looking for? Ask here.

Apply Now

Submit your resume and cover letter to be considered for Data Science Fellowship.

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