NVIDIA DLI COURSESAGS, the delivery partner of nvidia
Deep Learning Institute courses, structured for “hands-on” training on Artificial Intelligence (AI) and Accelerated Computing, with content designed for developers, data scientists, and researchers.
FUNDAMENTALS OF DEEP LEARNING FOR COMPUTER VISION
- Implement common Deep Learning workflows, such as image classification and object detection;
- Experiment with data, training parameters, network structure and other strategies to increase performance anda capability;
- Distribute a neural networks to start solving real-world problems
At the end of the course, you can start autonomously to use Deep Learning for the resolution of problems.
FUNDAMENTALS OF DEEP LEARNING FOR NATURAL LANGUAGE PROCESSING
- classify words to understand their meaning accurately
- manage factual queries and their semantic meaning
- enable automatic translators from one language to another
At the end of the course, the participants will be able to elaborate the natural language using neural networks in any application.
FUNDAMENTALS OF DEEP LEARNING FOR MULTIPLE DATA TYPES
- Implementation of Deep Learning workflows such as image segmentation and text generation;
- Comparison and contrast between different data, workflows, and frameworks;
- Combination of Computer Vision and natural language processing.
Once the course is over, it will be possible to solve Deep Learning problems that require different data inputs.
FUNDAMENTALS OF ACCELERATED COMPUTING WITH CUDA C/C++
UDA enables acceleration of CPU applications to run on the world’s fastest massively parallel GPUs.
The course allows you to gain experience with the acceleration of C/C++ applications. In particular, it will deal with the following topics:
- Accelerate CPU applications to run their latent parallelism on the GPU;
- Use of CUDA stream memory management techniques essential to optimize accelerated applications;
- Exposure to the potential of accelerated applications for competition and exploitation with CUD flows;
- How to use the command line and visual profiler to guide and control the work.
At the end of the course, you will be able to accelerate and optimize your existing C/C++ CPU applications using the most essential CUDA tools and techniques. The course also allows you to understand an iterative style of CUDA development that allows you to develop accelerated applications quickly.