GPU Programming Specialization

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Course Features

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Duration

5 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Teaching Type

Self Paced

Course Description

This specialization is for data scientists and software engineers who want to create software that makes use of commonly available hardware. Students will be introduced CUDA and libraries that enable them to perform multiple computations simultaneously and quickly. These skills can be used for machine learning, image/audio processing, and data processing.

Course Overview

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Virtual Labs

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Human Interaction

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

What You Will Learn

Develop CUDA software for running massive computations on commonly available hardware

Utilize libraries that bring well-known algorithms to software without need to redevelop existing capabilities

Students will learn how to develop concurrent software in Python and C/C++ programming languages

Students will gain an introductory level of understanding of GPU hardware and software architectures

Course Instructors

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Chancellor Thomas Pascale

Instructor and Software Engineer

Chancellor Pascale has been an instructor in the Johns Hopkins University's Whiting School of Engineering for over 10 years, teaching in the Computer Science department. He received an undergraduate ...
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