CUDA Course
Start Date:
10/04
35
academic hours
Final Project
CUDA Course
In recent years, with the advancement of technology in the IT industry, we can see that several breakthrough domains have emerged, to which significant resources are directed for intensive and complex developments across a wide range of life areas.
Today, tech companies in both local and international markets are striving to provide advanced solutions for problem-solving, process optimization, and the creation of new products.
The challenge is that such advanced solutions, which take technology's involvement in our lives and its effectiveness to the next level, often require substantial resources and intensive computational power to deliver relevant services. This is where the CUDA platform comes into play.
The CUDA platform was developed by NVIDIA to harness the computing power of GPUs for performing tasks that demand intensive computation, performance, and more. In many fields, particularly image and video processing, the CPU's power is insufficient.
When developing solutions in fields like autonomous transportation, automated medical treatments, and more, we frequently need to bridge the gap between the code we've developed and the graphic card to obtain robust resources for software operations. Through learning development with the CUDA platform, we can precisely achieve this goal and explore a new realm of software development and IT work opportunities.
The CUDA course includes lectures and practical exercises:
- Classroom exercises accompanied by explanations, assignments, and solutions on the course website.
- Course booklet.
- Videos and presentations on the course website.
- Lectures take place once a week during evening hours.
- Total academic study hours: 35 hours.
Course Structure
Ch. 1
Introduction to GPU Computing
Ch. 2
Installing and first program development
Ch. 3
CUDA API
Ch. 4
Simple Matrix Multiplication
Ch. 5
CUDA Memory Model
Ch. 6
Accelerated Code on GPUs
Ch. 7
Additional CUDA API Features
Ch. 8
Useful Information on CUDA Tools
Ch. 9
Threading Hardware
Ch. 10
Memory Hardware
Ch. 11
Linux GPU Debugging
Ch. 12
Parallel Thread Execution
Ch. 13
Precision
Meet your instructor
Alex Shoihat
Head of Machine Learning
Alex holds a B.Sc. in Information Systems and an M.A. in Electrical and Electronic Engineering.
As a Machine Learning Engineer at Embedded Academy, Alex specializes in the field of artificial intelligence, applying over 13 years of experience in project development, management, and transitioning from development to production in various domains such as Linux Embedded.
Throughout his career, Alex developed his expertise working with the integration of Machine Learning and Deep Learning in the Computer Vision and Data Analysis field.
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What our graduates say
Sarah L.
Machine Learning course graduate
AI/ML developer
The Machine Learning course was super practical, from hardcore algorithms to the ethics of AI. Thanks to the professional connections I met during school got me several job offers to check right after I graduate
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Paul N.
Machine Learning course graduate
Machine Learning Engineer
I was initially intimidated by the prospect of learning AI and machine learning because I thought I didn’t have enough mathematical knowledge, but throughout the course my instructor made sure I wouldn’t follow behind. It made a huge difference from other times I experienced with online courses.
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Howard E.
AI course graduate
AI Product Manager
As a business leader, the AI/ML program has been instrumental in helping me identify opportunities to leverage intelligent technologies. I've been able to upskill my team and implement data-driven strategies that have given us a significant competitive advantage in the market.
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Greg B.
Machine Learning course graduate
Robotics and Automation Specialist
I was impressed by the breadth and depth of the AI/ML curriculum. The hands-on projects, mentorship from industry experts, and exposure to real-world case studies have given me the confidence to apply advanced machine learning methodologies to solve real-world problems.
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Leonard H.
AI course graduate
Natural Language Processing (NLP) Specialist
As someone with a background in data analysis, the AI/ML course provided me with the selected skills to take my career forward. I'm now fluent in building and deploying sustainable predictive models that drive strategic decision-making paths.
