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Our Streams

provide a comprehensive treatment of a particular engineering area such as Machine Learning or Computer Engineering. Streams are divided into a collection of courses called Flows. Each Flow deals with a specific topic related to the main engineering area. For example, the first Flow in our Machine Learning Stream is "Intro to Machine Learning". Courses are further divided into units (lessons), assignments and hands-on projects. Hands-on projects are designed to give our students a practical understanding of the theory covered in the units.

Enrollment in each Stream is offered through a monthly subscription program. A subscription to a particular Stream gives students access to all the material in that entire Stream. Additionally, students will choose a weekly 1.5hr timeslot to attend one of our Instructor Assisted Project Sessions (IAPS). During each IAP Session, students will get to participate in technical challenges, interact with other students and seek help/guidance from our Instructors, Instructor Assistants (IA) and Stream Assistants (SAs) on their lessons and hands-on projects.

Before a student can enroll in a subscription program, they are required to take an introductory course, called NexStarter™, in the Stream of their choice. They are encouraged to sample from as many NexStarter™ courses as they like. Each NexStarter™ course is designed to provide students with a basic introduction in one particular Stream. Our goal is to provide students the option of sampling our Streams before selecting one (or many) of interest to subscribe in. NexStarter™ courses are offered seasonally; please check the Seasonal Programs section of this page for more info.

For additional information, please see our FAQ page or send us your question.


NexStarter™ courses are designed to give students an introduction to a particular Stream (e.g. Machine Learning or Computer Engineering).

Computer Engineering

The Computer Engineering (CE) Stream exposes students to a comprehensive, project-based Flow of courses starting with fundamentals of electricity and DC & AC electronics.

Machine Learning

The Machine Learning (ML) Stream exposes students to a comprehensive, project-based flow of courses starting with introductory, conceptual-based topics in classification, object detection and neural networks.