Summer Computer Science Camp

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Join us for Summer Computer Science Camp

2025 Summer Camp Dates | June 15-20, 2025

Dive into the exciting world of python programming, game creation, and introductory web design as you embark on a captivating journey of discovery and innovation. With expert guidance, you'll master the art of coding, unlock the secrets of game design, and turn your ideas into interactive realities.

Don't miss out on this unique opportunity to blend education with fun. It’s the perfect opportunity to kickstart your coding journey, make friends and enjoy a memorable summer adventure. 

Register for Camp

Total Camp Cost: $530

  • Base Cost: $480
  • Registration Fee (non-refundable): $50

Register

Cost includes resident hall lodging, three meals a day, snacks, and all major aspects of the camp. Our dining hall has many options for those with food allergies. However, we encourage you to bring appropriate snacks since not all snack options will meet all dietary needs.

Note:   The $50 non-refundable registration fee is due at the time of registration. No student will be considered registered until they have submitted this fee. Balance of tuition and fees are due by May 31, 2025. Any registrations after June 1, 2025 will incur an additional $50 late registration fee.

Meet the Camp Director

Kenny Ayano, Ph.D.

Kenny Ayano is an Assistant Professor of Computer Science at Indiana Wesleyan University. He obtained his doctoral degree in Computer and Information Technology from Purdue University after his master’s degree in information technology and Post Graduate Diploma in Computer Science from Ladoke Akintola University of Technology, Lautech Nigeria. Prior to his PhD, He has over 15 years of experience in Network and IT Support. He is also a certified Information Systems Security Professional (CISSP). He is passionate about teaching and imparting knowledge into younger generations. His research interest is in data analytics, cybersecurity, malware detection and anomaly detection in network traffic using deep learning techniques.


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