II - July 21–August 7, 2020
No previous programming experience is required, but participants should have an aptitude for logical reasoning and systematic thinking.
“We were encouraged to take different approaches to a code, which promoted creativity as well as problem-solving.” – Agustina G. | Purchase, New York
An intensive course designed to develop logic and programming skills through immersion in the fundamentals of C. Programming projects involving mathematical problems and word games challenge students to develop their logical reasoning, systematic thinking, and problem-solving skills. Students learn the structure and features of a fundamental programming language as they implement solutions in C. In addition to teaching programming techniques, the course will cover an overview of fundamental computing concepts such as data structures, library design, and memory management.
Participants are expected to bring laptops for this class. Laptops can either be a PC or a Mac, but should have at least 10GB of free space.
Students who have no programming background might consider taking Computer Programming for Beginners: Coding in Java.
Abhinav Gupta has industry experience ranging from building multiple platforms for an e-commerce start-up to contributing to the financial modelling group at BlackRock. In the teaching arena, he is at present the section leader of a data structures course at New York University. He has contributed to conferences held at Princeton University and AUT University, New Zealand. Abhinav is pursuing his masters degree in computer science at New York University. He holds a bachelor’s degree in information technology from Delhi Technological University. His areas of interests include software development, data science, and machine learning.
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.
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.