Admissions at SPARK Institute

Welcome to the admissions portal of SPARK Institute of Data Science and Applied Statistics. We're excited about your interest in joining our community of data innovators.

Application Process

Submit Application

Complete the online form with your personal and academic details.

Upload Documents

Submit transcripts, CV, letters of recommendation, and statement of purpose.

Pay Fee

Complete the $10 non-refundable application fee via secure payment.

Interview

Shortlisted candidates will be invited for a virtual interview.

Application Deadlines

Semester	Deadline
Fall Semester	June 1
Spring Semester	November 1
Summer Semester	March 1

Frequently Asked Questions

What are the admission requirements?

Applicants must have a strong background in mathematics. Some programs may require prerequisite coursework in calculus, linear algebra, or programming.

Is there an application fee?

Yes, there is a $10 non-refundable application fee. Fee waivers are available for eligible candidates based on financial need or participation in partner programs.

Can I apply for financial aid or scholarships?

Yes! We offer merit-based scholarships, need-based aid, and research assistantships. All admitted students are automatically considered for funding opportunities.

What if English is not my first language?

Non-native English speakers must submit TOEFL (minimum 90 iBT) or IELTS (minimum 6.5) scores. Waivers may be granted for applicants who completed prior education in English.

Ready to Apply?

Take the next step toward your data science career.

Start Your Application

Contact Admissions

Have questions? Our team is here to help.

Email: sparkinstitute2025@outlook.com

Phone: +256 706507280

Location: Namugere Arcade, Plot 204, Jinja City, Uganda

Technologies You'll Master

Our curriculum integrates industry-leading tools and platforms used by data scientists worldwide.

Python

Whether you're new to programming or an experienced developer, it's easy to learn and use Python. It compiles and runs on a wide variety of platforms and is the most popular language in data science and machine learning.

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R

R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS, making it ideal for academic and industry research.

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MySQL

Use automated and integrated generative AI and machine learning (ML) in one cloud service for transactions and lakehouse scale analytics. Get faster insights from all your data with unmatched performance.

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TensorFlow

Whether you're new to programming or an experienced developer, it's easy to learn and use TensorFlow for building and deploying ML models at scale.

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Tableau

Fuel faster data, insights, and action with Tableau Next. Turn trusted insights into autonomous action anytime, anywhere, with the world's first agentic analytics platform.

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