Computer Programming for Beginners: Coding in Java

Open to students entering grades 9 through 12 or freshman year of college in the fall
I - June 25–July 13, 2018
II - July 17–August 3, 2018
Days & Time:
Monday–Friday, 11:10 a.m.–1:00 p.m. and 3:10–5:00 p.m.
Tanweer Haroon, Leighanne Hsu, Pratik Karnik, Brandon Mazey, Arunima Sharma

No previous programming experience is required, but participants should have an aptitude for logical reasoning and systematic thinking.

Course Description

An introductory course designed to develop logical reasoning and computer programming skills through immersion in the fundamentals of Java. Programming projects involving mathematical problems and logic games challenge students to develop their logical reasoning, systematic thinking, and problem-solving skills. Students become familiar with fundamental object-oriented programming concepts, algorithms, and techniques. This course covers an overview of introductory material through hands-on labs and individual and collaborative projects. Labs are carried out in the cross-platform Java environment, which will be set up on students' personal laptop computers.

Participants are expected to bring laptops for this class. Laptops can either be a PC or a Mac, but should have 8GB – 10GB of free space.

Students who already have some background with programming might consider taking Introduction to Programming in C.


Tanweer Haroon

Tanweer Haroon is a full-time faculty member at City University of New York (Bronx Community College). He holds a master’s degree in system science from Louisiana State University, Baton Rouge, and a bachelor’s degree in electrical engineering from JMI, New Delhi. He has more than twenty years of experience in teaching and developing computer science and technology courses. Tanweer's areas of interest include computer programming, Web design, cyber-security, and database systems.

Leighanne Hsu

Leighanne Hsu holds a master’s degree in computer science from Columbia University and is currently a Ph.D. student at the University of Delaware. She holds a bachelor's degree from The College of New Jersey, where she tutored computer science for three years. Her areas of interest include natural language processing, particularly machine translation, speech processing, and dialogue systems, as well as other fields in artificial intelligence.

Pratik Karnik

Pratik Karnik will be completing his M.S. in computer science at New York University’s Courant Institute of Mathematical Sciences in May of 2018. He has nearly three years of full-time software development experience across several multinational organizations. Throughout his graduate and undergraduate years he has taught, tutored, and graded multiple computer science courses. Pratik's interests include big data analytics and FinTech software development. He has a passion for enabling students to develop their critical and logical reasoning skills through the medium of computer science. 

Brandon Mazey

Brandon Mazey joins us from the Royal Bank of Canada where he has spent the past three years designing and implementing RBC's cloud computing platform as a Senior Software Engineer. A New York University graduate with a double major in computer science and journalism, Brandon is the recipient of the 2017 Brian Dougherty community service award issued by the Boys and Girls Club of America for two outstanding years of STEM education in New York and New Jersey public schools. His interests include microservice architecture and cryptocurrency.

Arunima Sharma

Arunima Sharma is a Columbia University graduate student in management science and engineering and holds an undergraduate degree in computer science engineering from Guru Gobind Singh Indraprastha University in New Delhi. She is a Google Scholar and was recently recognized as one of three inspiring young women in tech in the Google Women Techmakers newsletter. She has taught students from underprivileged backgrounds in India and continues to find time to teach and mentor students today. Arunima's areas of interest in computer science are machine learning, artificial intelligence, and computer vision.

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Specific course detail such as hours and instructors are subject to change at the discretion of the University. Not all instructors listed for a course teach all sections of that course.