GPU Programming Specialization

This specialization is intended for data scientists and software developers to create software that uses commonly available hardware. Students will be introduced to CUDA and libraries that allow for performing numerous computations in parallel and rapidly. Applications for these skills are machine learning, image/audio signal processing, and data processing.
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
- S​tudents will learn how to develop concurrent software in Python and C/C++ programming languages.
- S​tudents will gain an introductory level of understanding of GPU hardware and software architectures.

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Introduction to Concurrent Programming with GPUs (Coursera)

Apr 29th 2024
Introduction to Concurrent Programming with GPUs (Coursera)
Course Auditing
Coursera
Johns Hopkins University
Categories
CS: Programming
CS: Software Engineering
Effort
Beginner
4 Weeks
5-10 Hours/Week
Languages
English
English
Introduction to Concurrent Programming with GPUs (Coursera)
This course will help prepare students for developing code that can process large amounts of data in parallel. It will focus on foundational aspects of concurrent programming, such as CPU/GPU architectures, multithreaded programming in C and Python, and an introduction to CUDA software/hardware.
GPU Programming Specialization
Concurrent Programming
GPU
CUDA
Programming
C/C++ Programming
Python
Python Programming
Parallel Programming
GPU Programming
Coursera Plus
View more details
Apr 29th 2024
Course Auditing
Coursera
Johns Hopkins University
CS: Programming
CS: Software Engineering
Beginner
4 Weeks
5-10 Hours/Week
44.00 EUR/month
English
English

Introduction to Parallel Programming with CUDA (Coursera)

Apr 29th 2024
Introduction to Parallel Programming with CUDA (Coursera)
Course Auditing
Coursera
Johns Hopkins University
Categories
CS: Programming
CS: Software Engineering
Effort
Intermediate
5-12 Weeks
5-10 Hours/Week
Languages
English
English
Introduction to Parallel Programming with CUDA (Coursera)
This course will help prepare students for developing code that can process large amounts of data in parallel on Graphics Processing Units (GPUs). It will learn on how to implement software that can solve complex problems with the leading consumer to enterprise-grade GPUs available using Nvidia CUDA. They will [...]
GPU Programming Specialization
Parallel Programming
CUDA
GPU
C/C++ Programming
NVIDIA GPUs
Coursera Plus
View more details
Apr 29th 2024
Course Auditing
Coursera
Johns Hopkins University
CS: Programming
CS: Software Engineering
Intermediate
5-12 Weeks
5-10 Hours/Week
44.00 EUR/month
English
English

CUDA Advanced Libraries (Coursera)

Apr 29th 2024
CUDA Advanced Libraries (Coursera)
Course Auditing
Coursera
Johns Hopkins University
Categories
Computer Science
Effort
Intermediate
5-12 Weeks
5-10 Hours/Week
Languages
English
English
CUDA Advanced Libraries (Coursera)
This course will complete the GPU specialization, focusing on the leading libraries distributed as part of the CUDA Toolkit. Students will learn how to use CuFFT, and linear algebra libraries to perform complex mathematical computations. The Thrust library’s capabilities in representing common data structures and associated algorithms will be [...]
GPU Programming Specialization
CUDA
GPU
cuFFT
cuBLAS
Machine Learning
Coursera Plus
View more details
Apr 29th 2024
Course Auditing
Coursera
Johns Hopkins University
Computer Science
Intermediate
5-12 Weeks
5-10 Hours/Week
44.00 EUR/month
English
English

CUDA at Scale for the Enterprise (Coursera)

Apr 29th 2024
CUDA at Scale for the Enterprise (Coursera)
Course Auditing
Coursera
Johns Hopkins University
Categories
CS: Software Engineering
Effort
Intermediate
5-12 Weeks
5-10 Hours/Week
Languages
English
English
CUDA at Scale for the Enterprise (Coursera)
This course will aid in students in learning in concepts that scale the use of GPUs and the CPUs that manage their use beyond the most common consumer-grade GPU installations. They will learn how to manage asynchronous workflows, sending and receiving events to encapsulate data transfers and control signals. [...]
GPU Programming Specialization
CUDA
CPU
GPU
C/C++ Programming
Image Processing
Coursera Plus
View more details
Apr 29th 2024
Course Auditing
Coursera
Johns Hopkins University
CS: Software Engineering
Intermediate
5-12 Weeks
5-10 Hours/Week
44.00 EUR/month
English
English